babytreecc/ICLR2025review · Datasets at Hugging Face

ydw2l8zgUB

EEGTrans: Transformer-Driven Generative Models for EEG Synthesis

main

Active

LLM;EEG;BCI;transformer

applications to neuroscience & cognitive science

3;3;3;5

4;5;3;5

2;1;2;3

2;2;2;2

3;2;2;3

3.5

4.25

2

2.5

0.522233

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ye1mxb79lw

BILBO: BILevel Bayesian Optimization

main

Active

bilevel;Bayesian optimization

probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.)

3;5;5;6;6

3;3;4;3;3

2;2;3;3;3

2;2;2;3;3

3;3;4;3;3

5

3.2

2.6

2.4

3.2

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yeEWZ8qvlS

Learning Interpretable and Influential Directions with Signal Vectors and Uncertainty Region Alignment

main

Active

latent space;interpretability;concepts;directions;signals;patterns;distractors

interpretability and explainable AI

3;5;5;6;6

4;3;3;2;2

2;2;2;4;3

2;2;2;3;3

2;2;2;2;3

5

2.8

2.6

2.4

2.2

-0.9759

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

yeeIGM3N6w

Retraining-Free Merging of Sparse Mixture-of-Experts via Hierarchical Clustering

main

Active

Sparse Mixture-of-Experts;Merging;Compression

other topics in machine learning (i.e., none of the above)

5;5;6;6

3;4;4;3

3;3;3;3

2;3;3;3

3;3;3;3

5.5

3.5

3

2.75

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yf30Al57nu

CodeLutra: Boosting LLM Code Generation via Preference-Guided Refinement

main

Active

large language models; preference learning; code generation

foundation or frontier models, including LLMs

3;3;5;6;8

4;4;4;3;4

2;2;4;3;3

2;1;3;3;3

3;2;4;3;3

5

3.8

2.8

2.4

3

-0.263523

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yfW1x7uBS5

Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI

main

Active

security;adversarial;style mimicry;generative ai

alignment, fairness, safety, privacy, and societal considerations

3;8;8;8

4;4;4;4

2;3;3;4

1;3;3;3

4;3;4;3

6.75

4

3

2.5

3.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yfZJdCijo6

Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures

main

Active

maximum coverage;turnstile streams;sketching

optimization

5;5;5;6

3;3;4;2

2;2;2;3

3;2;2;3

1;2;1;3

5.25

3

2.25

2.5

1.75

-0.816497

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yfkvUJEY6i

Learning Disease Progression Models That Capture Health Disparities

main

Active

fairness;equity;bias;health disparities;disease progression;bayesian model

alignment, fairness, safety, privacy, and societal considerations

3;3;3;8

4;4;3;3

1;3;1;3

2;3;2;3

3;3;2;3

4.25

3.5

2

2.5

2.75

-0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ygtmPu0xZy

Scalable Exploration via Ensemble++

main

Active

Bandit;Scalable Exploration;Function Approximation

reinforcement learning

5;5;5;5

3;4;4;3

3;3;3;2

2;3;2;3

2;2;3;3

5

3.5

2.75

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yhKNCvYlCr

Transfering Knowledge into Efficient Tiny Models for Object Detection with Dual Prompt Distillation

main

Withdraw

knowledge distillation;object detection

unsupervised, self-supervised, semi-supervised, and supervised representation learning

Feng Zhao;Yukun Qi;Jiahao Chang;Lin Chen;Kun Li;Tianyou Song;Zehui Chen

~Feng_Zhao6;~Yukun_Qi1;~Jiahao_Chang2;~Lin_Chen18;~Kun_Li13;~Tianyou_Song1;~Zehui_Chen1

3;3;3;6

4;5;4;4

2;3;2;2

1;3;2;2

3;3;2;2

3.75

4.25

2.25

2

2.5

-0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": null, "confidence": null, "contribution": null, "desk_reject_comments": null, "details_of_ethi...

yheQRc5xWB

Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models

main

Active

Time Series; State-space Models; Treatment Effect Estimation

causal reasoning

5;5;5;6;6

4;4;3;3;2

2;3;2;3;2

3;2;3;3;3

3;3;3;3;2

5.4

3.2

2.4

2.8

-0.763763

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yhmVrA8W0v

The Convergence of Second-Order Sampling Methods for Diffusion Models

main

Active

diffusion models;reserve SDE

generative models

3;3;5;6;6

4;5;4;4;3

3;2;2;3;4

2;1;2;3;3

2;3;2;2;2

4.6

4

2.8

2.2

-0.699379

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yi3QcCGfP1

Enhancing Certified Robustness via Block Reflector Orthogonal Layers

main

Active

Certified robustness;Adversarial

alignment, fairness, safety, privacy, and societal considerations

3;5;6;6;6

4;4;3;3;2

1;3;2;3;3

1;2;2;3;3

1;3;3;3;3

5.2

3.2

2.4

2.2

2.6

-0.733359

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yiGSI7Ou3i

Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization

main

Active

diffusion model;parameter generation;personalization

foundation or frontier models, including LLMs

3;5;5;6

3;2;3;4

2;3;3;3

3;2;3;3

4.75

3

2.75

0.324443

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": null, "confidence": null, "contribution": null, "desk_reject_comments": null, "details_of_ethi...

yiQCeXdPvs

DIRECT: Deep Active Learning under Imbalance and Label Noise

main

Active

Deep Learning;Active Learning

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;3;3;6

4;4;4;3

2;3;2;2

2;1;2;2

2;2;2;2

3.75

2.25

1.75

2

-1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yitH9xAHQs

Forewarned is Forearmed: Harnessing LLMs for Data Synthesis via Failure-induced Exploration

main

Active

data synthesis;preference learning;LLM alignment

applications to computer vision, audio, language, and other modalities

3;5;5;6

3;4;4;4

2;2;2;3

3;3;2;3

2;2;3;3

4.75

3.75

2.25

2.75

2.5

0.927173

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yizEOJVFFd

Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment

main

Active

Large Language Model;Fine-tuning;Self-play

alignment, fairness, safety, privacy, and societal considerations

3;3;5;6

4;4;4;4

2;2;2;3

2;2;2;2

2;3;3;3

4.25

4

2.25

2

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yj6P8OdWyj

Open-Set Learning for Addressing Label Skews in One-Shot Federated Learning

main

Active

federated learning;open-set learning

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;5;5;5

4;3;4;3

2;3;3;2

2;2;3;2

3;3;3;2

4.5

3.5

2.5

2.25

2.75

-0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yj9lLwMjnE

UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation

main

Active

speech foundation model;generative pre-training;self-supervised learning;speech generation;speech tokenization

applications to computer vision, audio, language, and other modalities

3;5;6;6;8

4;3;5;4;3

2;3;3;3;3

2;3;2;2;3

3;3;3;3;4

5.6

3.8

2.8

2.4

3.2

-0.230283

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ykD8a9gJvy

Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation

main

Active

generative keyframe interpolation;image-to-video diffusion models

applications to computer vision, audio, language, and other modalities

6;6;6;6

4;4;4;3

3;3;4;3

3;3;3;2

6

3.75

3.25

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yklJpvB7Dq

Label-Free Coreset Selection with Proxy Training Dynamics

main

Active

Coreset Selection;Data pruning;Label free coreset selection

other topics in machine learning (i.e., none of the above)

5;6;6;8

4;3;2;3

3;3;3;4

2;2;3;3

3;3;2;4

6.25

3

3.25

2.5

3

-0.324443

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ykt6I21YQZ

Ensemble Kalman Diffusion Guidance: A Derivative-free Method for Inverse Problems

main

Active

inverse problem;diffusion model;derivative-free

other topics in machine learning (i.e., none of the above)

3;3;5;6

5;3;4;3

1;3;2;3

2;2;4;2

2;3;3;3

4.25

3.75

2.25

2.5

2.75

-0.406181

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ykuc5q381b

BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval

main

Active

Retrieval benchmark;Reasoning

datasets and benchmarks

3;5;6;8;10

4;3;4;4;4

3;2;3;3;4

3;3;3;3;4

3;4;3;3;4

6.4

3.8

3

3.2

3.4

0.289662

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ylgg2RE7ub

IF-MODGS : INITIAL FREE MONOCULAR DYNAMIC GAUSSIAN SPLATTING

main

Withdraw

novel view synthesis;4D rendering;camera pose estimation;3D reconstruction

applications to computer vision, audio, language, and other modalities

Yeomsuwoong;Jimin Roh;Eunho Shin;Kyeongbo Kong;Joonsoo Kim;Songju Na;Suk-Ju Kang

~Yeomsuwoong1;~Jimin_Roh1;~Eunho_Shin1;~Kyeongbo_Kong1;~Joonsoo_Kim2;~Songju_Na3;~Suk-Ju_Kang1

3;3;5;5

4;4;5;4

3;3;2;3

2;2;1;2

3;3;2;2

4

4.25

2.75

1.75

2.5

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "We thank the reviewers for reviewing our paper. After careful consideration, we think our pa...

ylhKbwJrjC

Mechanism design with multi-armed bandit

main

Active

mechanism design;incentive compatibility;efficiency;individual rationality;budget balance;multi-armed bandit;probably approximately correct

other topics in machine learning (i.e., none of the above)

3;5;6

3;2;2

2;3;3

1;2;3

3;2;3

4.666667

2.333333

2.666667

2

2.666667

-0.944911

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "> Although the paper provides an approach with computational efficiency, the LP studied in t...

ym1dS37mZE

Efficient Multi-modal Large Language Models via Visual Token Grouping

main

Active

Large Language Model;Multi-modal Learning

applications to computer vision, audio, language, and other modalities

3;5;6

4;5;4

2;3;3

2;2;3

4.666667

4.333333

2.666667

2.333333

0.188982

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ym7pr83XQr

DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training

main

Active

3D Molecular pre-training via denoising;Molecular property prediction

applications to physical sciences (physics, chemistry, biology, etc.)

5;5;6;6

5;2;4;3

2;2;3;4

2;2;3;3

4;2;3;4

5.5

3.5

2.75

2.5

3.25

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

ymqLAmqYHW

K&L: Penetrating Backdoor Defense with Key and Locks

main

Active

backdoor attack;backdoor defense;AI security

alignment, fairness, safety, privacy, and societal considerations

1;5;5;6

5;4;5;3

1;3;3;2

1;3;2;2

1;2;3;2

4.25

2.25

2

-0.667308

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ymt4crbbXh

AutoBencher: Towards Declarative Benchmark Construction

main

Active

automatic evaluation;language models

foundation or frontier models, including LLMs

3;5;6;8

2;5;3;3

2;3;3;4

3;3;4;4

5.5

3.25

3

3.5

0.190885

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

yougZBoUY3

Attacking Audio Language Models with Best-of-N Jailbreaking

main

Active

adversarial robustness;jailbreaks;audio language model;speech language model;multimodal;adversarial attack;audio jailbreak;safety;trustworthy;robustness

alignment, fairness, safety, privacy, and societal considerations

3;3;5

4;4;4

3;1;3

2;1;3

2;1;4

3.666667

4

2.333333

2

2.333333

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yp95goUAT1

SiReRAG: Indexing Similar and Related Information for Multihop Reasoning

main

Active

Retrieval-augmented generation (RAG);RAG indexing;Multi-hop question answering

applications to computer vision, audio, language, and other modalities

3;5;6;8

4;4;4;4

2;3;4;3

2;2;3;3

5.5

4

3

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ypBYdetYd9

Measuring and Controlling Solution Degeneracy across Task-Trained Recurrent Neural Networks

main

Active

Recurrent Neural Network;Dynamical System;Neural Computation;Computational Neuroscience

applications to neuroscience & cognitive science

3;3;5;5;5

4;3;2;4;5

3;2;3;2;2

2;1;2;2;3

4;3;3;3;4

4.2

3.6

2.4

2

3.4

0.080064

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

yqJoqtUwSI

Collaborative Hybrid Propagator for Temporal Misalignment in Audio-Visual Segmentation

main

Active

audio-visual video segmentation

applications to computer vision, audio, language, and other modalities

3;5;5;5;8

4;3;4;4;5

1;3;3;3;3

3;2;3;3;3

1;3;3;4;3

5.2

4

2.6

2.8

0.592927

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yqST7JwsCt

Entropy-Based Aggregation for Fair and Effective Federated Learning

main

Active

Fairness;Heterogeneous Federated Learning

alignment, fairness, safety, privacy, and societal considerations

5;5;5;6;8

4;3;3;4;4

2;2;3;4;4

2;3;3;3;4

2;2;3;3;4

5.8

3.6

3

2.8

0.560112

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yqaN7MfkFU

Regularized Maximum Mean Discrepancy for Variable Selection

main

Active

Variable selection;Maximum mean discrepancy;Two-sample tests;Binary classification

other topics in machine learning (i.e., none of the above)

3;3;5;6;6

2;4;4;3;3

3;2;2;2;3

2;2;3;2;3

3;2;3;3;3

4.6

3.2

2.4

2.8

0.078811

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yr0l1IoyzV

A GPU-accelerated Large-scale Simulator for Transportation System Optimization Benchmarking

main

Active

microscopic traffic simulator;transportation system optimization;GPU acceleration

infrastructure, software libraries, hardware, systems, etc.

5;5;5;6

4;2;3;4

2;2;3;3

2;2;2;3

3;2;3;4

5.25

3.25

2.5

2.25

3

0.522233

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "Thank you for your review.\nI will list the responses to your questions as follows:\n\n**To ...

yr7PjzmkQ6

On the utility of Equivariance and Symmetry Breaking in Deep learning architectures on point clouds

main

Active

deep learning architectures;geometric deep learning;equivariance;group convolutional networks;generative modeling

unsupervised, self-supervised, semi-supervised, and supervised representation learning

5;5;6;6

2;4;3;3

2;3;2;3

2;3;3;3

5.5

3

2.5

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yrf5RmaHfG

JuxtAlign: A Foundational Analysis on Alignment of Certified Reinforcement Learning

main

Active

alignment;juxtaposition;reinforcement learning

alignment, fairness, safety, privacy, and societal considerations

3;5;5

3;3;3

2;2;3

2;3;2

1;3;2

4.333333

3

2.333333

2

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yrnrvfXFaV

Low-cost Enhancer for Text Attributed Graph Learning via Graph Alignment

main

Active

Text-attributed Graphs

foundation or frontier models, including LLMs

3;3;5;6

4;4;5;3

2;2;2;3

1;2;2;3

2;2;2;3

4.25

4

2.25

2

2.25

-0.272166

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

ys16t9FcLN

Distribution-Dependent Rates for Multi-Distribution Learning

main

Active

multi-distribution learning;distributionally robust optimization;pure exploration multi-armed bandits

learning theory

3;5;6;6

3;4;2;2

2;3;3;3

3;2;3;3

2;4;3;2

5

2.75

-0.492366

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ys3eqxzkeN

Efficient Gun Detection in Real-World Videos: Challenges and Solutions

main

Active

Image-augmented training;transfer learning

applications to computer vision, audio, language, and other modalities

3;3;3;5

4;4;5;4

2;2;2;2

2;1;2;2

2;2;2;3

3.5

4.25

2

1.75

2.25

-0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

ysAX5ORQoX

R2C: Mapping Room to Chessboard to Unlock LLM As Low-Level Action Planner

main

Active

Embodied AI;Large Language Model;Embodied Instruction Following;Robotic Planning

applications to robotics, autonomy, planning

3;3;5;6

4;4;4;4

2;3;3;3

2;1;3;2

2;3;3;3

4.25

4

2.75

2

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ysQiaWhnCN

Autoverse: an Evolvable Game Language for Learning Robust Embodied Agents

main

Active

open-ended learning;reinforcement learning;imitation learning;evolution;search

reinforcement learning

3;3;3;5

3;4;4;3

2;1;1;2

3;2;2;3

2;1;1;1

3.5

1.5

2.5

1.25

-0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ysZvK6b60c

CALoR: Towards Comprehensive Model Inversion Defense

main

Active

Privacy Leakage;Model Inversion;Defense

alignment, fairness, safety, privacy, and societal considerations

3;5;5;5

4;5;5;4

1;2;3;2

1;2;2;2

1;3;3;2

4.5

2

1.75

2.25

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yspBoIZJ9Z

Enhancing Video Understanding with Vision and Language Collaboration

main

Active

Video understanding;video pre-trained model;vision-language model;collaboration learning

applications to computer vision, audio, language, and other modalities

3;5;5;6

4;4;4;4

2;3;2;3

2;2;2;3

2;3;3;3

4.75

4

2.5

2.25

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yt7nxONs3J

Prioritize Alignment in Dataset Distillation

main

Active

dataset distillation

applications to computer vision, audio, language, and other modalities

3;5;5;6

4;4;4;5

3;3;3;3

2;3;2;2

3;3;3;3

4.75

4.25

3

2.25

3

0.662266

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ytn0rbIfOx

Formulating AutoML as a Variable-Length Optimization Problem: A Tree of Thought Approach with LLM-Driven Code Generation

main

Active

AutoML;Tree of Thought;LLM

optimization

3;3;8

5;4;4

1;2;4

2;2;4

2;2;3

4.666667

4.333333

2.333333

2.666667

2.333333

-0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ytvWZEiywp

EVINCE: Optimizing Adversarial LLM Dialogues via Conditional Statistics and Information Theory

main

Active

LLM;GAI;AGI

foundation or frontier models, including LLMs

3;3;3;5;6

4;4;4;3;4

2;2;2;3;3

1;2;2;2;3

3;2;2;2;3

4

3.8

2.4

2

2.4

-0.395285

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yu1vqQqKkx

LICO: Large Language Models for In-Context Molecular Optimization

main

Active

large language models;molecular optimization;black-box optimization;foundation models;in-context learning

foundation or frontier models, including LLMs

3;5;6;6

3;5;4;3

2;3;3;2

2;4;3;3

3;4;3;3

5

3.75

2.5

3

3.25

0.246183

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

yuuyPlywuO

Distilling an End-to-End Voice Assistant Without Instruction Training Data

main

Active

Multi-Modal LLMs;Voice Assistants;Distillation

foundation or frontier models, including LLMs

3;3;5;6

4;4;4;4

2;3;3;3

2;2;1;4

3;3;2;4

4.25

4

2.75

2.25

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yuymgwkjj1

Correcting the Bias of Normalizing Flows by Synthetic Outliers for Improving Out-of-Distribution Detection

main

Active

OOD Detection;Normalizing Flow

applications to computer vision, audio, language, and other modalities

3;5;5;5

3;5;4;4

2;3;3;2

1;2;2;2

3;3;3;2

4.5

4

2.5

1.75

2.75

0.816497

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yvxpHbydFx

Understanding Diffusion-based Representation Learning via Low-Dimensional Modeling

main

Active

diffusion representation learning;representation learning;diffusion model;denoising auto-encoder

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;3;5;6

4;3;3;4

3;1;3;2

1;1;2;2

2;1;3;2

4.25

3.5

2.25

1.5

2

0.19245

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ywFOSIT9ik

Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations

main

Active

zeroth-order optimization;SGD;convergence analysis

optimization

5;5;5;6;8

3;3;3;2;5

2;3;3;3;3

2;4;3;3;3

5.8

3.2

2.8

3

0.735147

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

ywHOnGOLb1

A Competitive-Cooperative Actor-critic Framework for Reinforcement Learning

main

Active

Deep reinforcement learning; Double-actor framework; Competition and Cooperation

reinforcement learning

3;5;6

3;4;5

2;3;3

4.666667

4

2.666667

0.981981

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ywKlmMor0f

MMA: Benchmarking Multi-Modal Large Language Model in Ambiguity Contexts

main

Active

Multi-Modal Large Language Model;Ambiguity;Benchmark

datasets and benchmarks

3;5;5;5

4;4;3;4

2;3;3;3

2;3;2;3

2;3;2;2

4.5

3.75

2.75

2.5

2.25

-0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ywgwArtbDq

Seeing Through the Mask: Rethinking Adversarial Examples for CAPTCHAs

main

Withdraw

CAPTCHAs;Adversarial examples;Vision models;Robust models

other topics in machine learning (i.e., none of the above)

Andreas Plesner;Yahya Jabary;Turlan Kuzhagaliyev;Roger Wattenhofer

~Andreas_Plesner1;~Yahya_Jabary1;~Turlan_Kuzhagaliyev1;~Roger_Wattenhofer1

1;3;3;5

5;4;4;3

1;2;2;2

2;1;2;2

2;2;2;3

3

4

1.75

2.25

-1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": null, "confidence": null, "contribution": null, "desk_reject_comments": null, "details_of_ethi...

yx8bU8T5ZN

A Unified View of Delta Parameter Editing in Post-Trained Large-Scale Models

main

Active

Large Language Models;Delta Parameters Editing

foundation or frontier models, including LLMs

1;3;3

4;4;5

1;2;1

1;1;2

3;1;2

2.333333

4.333333

1.333333

2

0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

yyIHdaSDUU

Adaptive Vision Encoders: Balancing Efficiency and Robustness in Vision-Language Models

main

Active

large vision-language models;multimodal learning;continual learning

transfer learning, meta learning, and lifelong learning

1;3;3;3

3;3;4;4

1;2;2;2

1;1;2;2

1;3;1;2

2.5

3.5

1.75

1.5

1.75

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

yzloNYH3QN

Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers

main

Active

Large Language Model;Information Retrieval

applications to computer vision, audio, language, and other modalities

3;5;6;6

4;4;4;5

2;3;3;3

3;2;3;3

3;3;3;3

5

4.25

2.75

3

0.471405

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z0B7A6Dh1H

High Probability Contextual Bandits for Optimal Dosage Selection

main

Active

Linear Bandits;Dosage Selection;Contextual Bandits

applications to physical sciences (physics, chemistry, biology, etc.)

3;5;6;8

4;4;3;4

2;3;4;3

2;3;3;3

2;3;4;4

5.5

3.75

3

2.75

3.25

-0.160128

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z0hUsPhwUN

Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaption

main

Active

image compression;vqgan;generative compression model;multi-grained representation

applications to computer vision, audio, language, and other modalities

5;5;6;6;6

4;5;5;5;5

3;2;3;3;3

3;1;3;3;2

2;2;3;3;3

5.6

4.8

2.8

2.4

2.6

0.612372

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

z1Jq1PLQWs

Dueling in the Dark: An Efficient and Optimal $O(\sqrt{T})$ Mirror Descent Approach for Competing against Adversarial Preferences

main

Active

Large Language Models (LLMs);Reinforcement Learning from Human Feedback (RLHF);gradient descent-based algorithm;theoretical foundations;active no-regret learning;preference feedback;trajectory preferences;multi-way feedback;human-AI alignment;practical impact.

learning theory

5;5;5;6;6;6

4;3;2;2;4;3

3;2;3;3;3;3

3;2;2;3;3;2

3;3;3;3;3;3

5.5

3

2.833333

2.5

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

z1mLNhWFyY

Gradient Routing: Masking Gradients to Localize Computation in Neural Networks

main

Active

representation learning;modularity;unlearning;reinforcement learning;scalable oversight

alignment, fairness, safety, privacy, and societal considerations

3;5;5;6

4;5;3;4

3;2;2;3

2;2;3;3

3;2;4;4

4.75

4

2.5

3.25

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z1nSpA2dAW

FLOPS: Forward Learning with OPtimal Sampling

main

Active

stochastic optimization;gradient estimation

optimization

3;5;5;5

3;3;3;3

2;2;3;3

2;3;3;2

1;1;3;2

4.5

3

2.5

1.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z1ohBxWeL2

SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation

main

Active

LLM;Inference;System;Compression;Distillation

foundation or frontier models, including LLMs

3;5;6;6

4;4;3;4

3;2;3;2

2;2;2;2

4;3;2;2

5

3.75

2.5

2

2.75

-0.471405

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z1pydjd4XQ

YESNO-PRO: A HIGH-PERFORMANCE POINTWISE RERANKING ALGORITHM BRIDGING ENCODERDECODER AND DECODER-ONLY LLMS

main

Active

zero-shot text reranking;Large Language Models

applications to computer vision, audio, language, and other modalities

1;3;3;3

4;4;5;4

1;3;2;2

1;2;2;1

2;3;2;1

2.5

4.25

2

1.5

2

0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z1td6fBKpG

Conjuring Semantic Similarity

main

Active

Semantic Similarity;Interpretability;Diffusion Models

interpretability and explainable AI

3;5;5;6

3;3;3;3

2;2;3;3

2;2;2;2

3;3;3;3

4.75

3

2.5

2

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z1yI8uoVU3

Measuring Effects of Steered Representation in Large Language Models

main

Active

in-context learning;activation steering;large language models

foundation or frontier models, including LLMs

3;3;3;3

3;4;4;4

2;2;2;2

2;1;2;2

2;2;2;2

3

3.75

2

1.75

2

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z21DkDDdgq

Integral Performance Approximation for Continuous-Time Reinforcement Learning Control

main

Active

Continuous-Time Reinforcement Learning (CT-RL);Optimal Control;Integral Performance Approximation (IPA);Adaptive/Approximate Dynamic Programming (ADP);Flight Control;Hypersonic Vehicles (HSVs)

reinforcement learning

5;5;5

3;4;4

2;3;3

2;2;3

3;3;3

5

3.666667

2.666667

2.333333

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z2QdVmhtAP

Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations

main

Active

fMRI;Computational Neuroscience;Neuroimaging;Diffusion;CLIP;alignment;neuroAI

applications to neuroscience & cognitive science

3;3;3

4;5;4

3;1;1

3;1;2

3;2;2

3

4.333333

1.666667

2

2.333333

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z2VBHpRT14

SpaceSet: A Large-scale Realistic Space-based Image Dataset for Space Situational Awareness

main

Active

space situational awareness;object detection and tracking;space image dataset;high resolution image

datasets and benchmarks

5;5;6;10

3;4;2;1

3;2;3;4

2;2;3;4

3;2;3;4

6.5

2.5

3

2.75

3

-0.867722

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

z2WCyBO923

Four eyes see more than two: Dataset Distillation with Mixture-of-Experts

main

Active

dataset distillation;mixture-of-experts

unsupervised, self-supervised, semi-supervised, and supervised representation learning

5;5;5;5

4;5;4;4

2;2;2;3

2;2;2;2

3;2;3;3

5

4.25

2.25

2

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z2z9suDRjw

GOAL: A Generalist Combinatorial Optimization Agent Learning

main

Active

neural combinatorial optimization;generalist models;transfer learning;fine tuning

foundation or frontier models, including LLMs

5;5;6;8

4;4;4;4

3;2;3;4

2;3;3;4

3;3;3;3

6

4

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z3DMFpaP6m

On the Entropy of Language Models in Getting Semantic from Tokens

main

Active

LLM evaluation

foundation or frontier models, including LLMs

1;3;5

3;3;2

1;1;3

1;2;2

1;1;2

3

2.666667

1.666667

1.333333

-0.866025

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z3KmG5JIN4

CodeCloak: A Method for Mitigating Code Leakage by LLM Code Assistants

main

Active

privacy;DRL;LLM;code assistant;generative models

alignment, fairness, safety, privacy, and societal considerations

3;5;5

3;3;3

2;2;2

2;2;1

4.333333

3

2

1.666667

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z3vplLsIve

Learn to Synthesize Compact Datasets by Matching Effects

main

Active

Deep Learning;Dataset Distillation

unsupervised, self-supervised, semi-supervised, and supervised representation learning

1;3;5;5

5;4;4;4

2;1;2;3

3;2;2;2

2;4;3;2

3.5

4.25

2

2.25

2.75

-0.870388

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z4Ho599uOL

STARJOB: DATASET FOR LLM-DRIVEN JOB SHOP SCHEDULING

main

Active

JSSP;Large Language Models;supervised dataset;Starjob;artificial intelligence;sampling method;LLM

datasets and benchmarks

3;3;3;3

3;4;5;2

2;2;2;3

2;2;1;2

3;2;2;3

3

3.5

2.25

1.75

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

z4bfNsrum4

Decoding Generalization from Memorization in Deep Neural Networks

main

Active

Generalization;Memorization

other topics in machine learning (i.e., none of the above)

1;3;3;6;6

4;3;4;4;4

1;1;2;3;3

1;2;2;3;2

1;2;3;2;3

3.8

2

2.2

0.206284

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z4rBSPep64

DAViD: Domain Adaptive Visually-Rich Document Understanding with Synthetic Insights

main

Active

Visually-Rich Documents;Visually-Rich Document Understanding;Domain Adaption

applications to computer vision, audio, language, and other modalities

3;3;5;5

3;4;4;4

2;3;3;3

3;2;3;3

1;2;2;2

4

3.75

2.75

1.75

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z5Th95xtBW

Hierarchical Frequency Tagging Probe (HFTP): A Unified Approach to Investigate Syntactic Structure Representations in Large Language Models and the Human Brain

main

Desk Reject

Syntactic structure probe;Large language models;stereo-electroencephalography;Syntactic representation alignment

interpretability and explainable AI

Jingmin An;Yilong Song;Ruolin Yang;Nai Ding;Lingxi Lu;Yuxuan Wang;Wei Wang;Chu Zhuang;Qian Wang;Fang Fang

~Jingmin_An2;~Yilong_Song1;~Ruolin_Yang2;~Nai_Ding1;~Lingxi_Lu2;~Yuxuan_Wang6;~Wei_Wang4;~Chu_Zhuang1;~Qian_Wang39;~Fang_Fang1

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": null, "confidence": null, "contribution": null, "desk_reject_comments": { "value": "The pape...

z5UZZjXFc9

Rethinking Fairness Representation in Multi-Task Learning: a Performance-Informed Variance Reduction Approach

main

Active

Multi-Task Learning;Fair Optimization;Dynamic Weighting Strategy

other topics in machine learning (i.e., none of the above)

3;3;6;6

5;4;4;3

2;3;3;3

2;1;2;3

3;3;3;3

4.5

4

2.75

2

3

-0.707107

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z5uVAKwmjf

AFlow: Automating Agentic Workflow Generation

main

Active

LLM Agent; Prompt Optimization; Workflow Generation

applications to robotics, autonomy, planning

5;6;8;8

3;3;3;3

3;4;3;4

1;3;3;3

6.75

3

3.5

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z6qmomJW91

RotRNN: Modelling Long Sequences with Rotations

main

Active

Sequence Modelling;Recurrent Neural Networks;State Space Models;Long Sequences

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;3;5;5

3;2;5;3

3;2;3;3

2;2;1;2

3;3;4;2

4

3.25

2.75

1.75

3

0.688247

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z7JBs8UOLI

Unconstrained Robust Online Convex Optimization

main

Active

online learning;online convex optimization;adversarial corruption;comparator adaptive;parameter-free;unconstrained domain

optimization

5;6;6;6

3;3;4;4

3;3;4;3

2;3;3;3

1;3;4;3

5.75

3.5

3.25

2.75

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z7PhIgVmZU

BAT-CLIP: Bimodal Test-Time Adaptation for CLIP

main

Withdraw

Test-Time Adaptation;CLIP;Robustness

transfer learning, meta learning, and lifelong learning

Sarthak Kumar Maharana;Baoming Zhang;Leonid Karlinsky;Rogerio Feris;Yunhui Guo

~Sarthak_Kumar_Maharana1;~Baoming_Zhang2;~Leonid_Karlinsky3;~Rogerio_Feris1;~Yunhui_Guo2

3;5;6;8

4;4;5;3

2;2;3;3

2;3;3;3

5.5

4

2.5

2.75

-0.392232

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": null, "confidence": null, "contribution": null, "desk_reject_comments": null, "details_of_ethi...

z7QAz5y8Uz

FoGE: Fock Space inspired encoding for graph prompting

main

Active

llm;prefix tuning;graph;graph encoding;geometric algebra;Fock space

learning on graphs and other geometries & topologies

3;5;5;6

4;1;3;3

2;2;3;3

2;2;3;2

2;2;2;2

4.75

2.75

2.5

2.25

2

-0.473684

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z8PcUSKXXN

Random Is All You Need: Random Noise Injection on Feature Statistics for Generalizable Deep Image Denoising

main

Active

Image Denoising;Low-Level Vision;Generalization Problem

applications to computer vision, audio, language, and other modalities

5;5;6;6

4;4;4;3

2;2;3;3

3;2;3;3

5.5

3.75

2.5

2.75

-0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

z8sxoCYgmd

LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models

main

Active

LMMs；Deepfake；Multimodality

datasets and benchmarks

6;8;8;8

4;5;4;5

3;3;3;3

3;4;3;3

3;3;4;3

7.5

4.5

3

3.25

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

z9CCkjVY0h

Augmented Flow Matching via Variance Reduction with Auxiliary Variables

main

Active

generative modeling;flow matching

generative models

1;3;5;6

5;4;4;3

2;2;3;3

2;2;3;2

3;2;3;3

3.75

4

2.5

2.25

2.75

-0.920575

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z9UABOHCZc

GeoTimeCLIP: Unveiling the When and Where of Images

main

Active

time prediction;geolocalization;contrastive learning;metric learning

applications to computer vision, audio, language, and other modalities

3;5;6;6

4;5;5;4

3;3;4;3

1;3;4;3

3;3;4;3

5

4.5

3.25

2.75

3.25

0.408248

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z9UBpl4pv5

Structured Initialization for Attention in Vision Transformers

main

Active

Transformer;Learning theory;Initialization;ConvMixer;Attention map

learning theory

3;5;5

5;4;4

2;3;3

2;2;2

3;3;3

4.333333

2.666667

2

3

-1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

z9j7wctoGV

Non-parametric Kernel Relative Test for Machine-generated Text Detection

main

Active

Large language models;Machine-generated text detection;Relative test

alignment, fairness, safety, privacy, and societal considerations

5;5;6

3;5;3

3;2;3

2;2;2

2;2;3

5.333333

3.666667

2.666667

2

2.333333

-0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

zA0oW4Q4ly

Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training

main

Active

linear regions;activation regions;ReLU network;pretraining;network initialization

other topics in machine learning (i.e., none of the above)

3;3;3;6

3;3;4;2

2;2;2;3

2;2;3;3

3.75

3

2.25

2.5

-0.816497

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

zAogQOIphH

ControlSpeech: Towards Simultaneous Zero-shot Speaker Cloning and Zero-shot Language Style Control

main

Active

text-to-speech;style control;discrete codec model

applications to computer vision, audio, language, and other modalities

3;5;5;5;8

4;5;4;4;4

2;2;3;3;4

2;3;3;2;4

3;2;3;3;4

5.2

4.2

2.8

3

-0.0625

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

zAyS5aRKV8

EgoSim: Egocentric Exploration in Virtual Worlds with Multi-modal Conditioning

main

Active

Controllable video generation;Egocentric video prediction;World model

generative models

5;6;6

4;3;3

2;4;3

2;3;3

2;3;1

5.666667

3.333333

3

2.666667

2

-1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

zAzzMOaisF

LLMs for Generalizable Language-Conditioned Policy Learning under Minimal Data Requirements

main

Active

Large Language Models;Language-conditioned policy;Offline policy learning;Decison Making Agent;Goals generalization;Domain generalization

foundation or frontier models, including LLMs

3;3;5;6

4;3;4;3

2;2;3;3

1;2;3;2

2;3;4;3

4.25

3.5

2.5

2

3

-0.19245

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

zB6uMznFuZ

TimeAutoDiff: Generation of Heterogeneous Time Series Data via Latent Diffusion Model

main

Active

Time series data;Tabular data;Heterogeneous;Diffusion model;VAE;Generative model

generative models

1;3;3;5

1;4;2;3

1;3;3;3

1;3;2;3

1;4;3;3

3

2.5

2.25

2.75

0.632456

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

zBbZ2vdLzH

Joint Graph Rewiring and Feature Denoising via Spectral Resonance

main

Active

GNNs;Rewiring;Denoising;Spectral Resonance;cSBM

learning on graphs and other geometries & topologies

5;5;6;6;8

3;2;3;3;3

3;3;3;3;4

2;2;3;2;4

2;3;3;3;4

6

2.8

3.2

2.6

3

0.456435

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

zBgiCWCxJB

SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning

main

Active

self-supervised learning;orthogonal low-rank embedding

unsupervised, self-supervised, semi-supervised, and supervised representation learning

5;6;6;8

5;3;3;4

2;3;3;3

3;3;3;3

6.25

3.75

2.75

3

-0.207514

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

zBrjRswpkg

Foundation of Scalable Constraint Learning from Human Feedback

main

Active

RLHF;RL;Constraint Learning;Theoretical Analysis

reinforcement learning

3;3;5;5

4;3;3;4

2;3;3;2

1;1;2;3

4

3.5

2.5

1.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...