babytreecc/ICLR2025review · Datasets at Hugging Face

vxutwN3xQN

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?

main

Active

Multimodal Reward Models;Foundation Models Alignment;Reinforcement Learning from Human Feedback

alignment, fairness, safety, privacy, and societal considerations

5;6;6;6

4;4;2;4

2;3;3;3

2;3;1;2

3;2;3;3

5.75

3.5

2.75

2

2.75

-0.333333

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vxvgZ0kTFv

Gradient Descent Converges Linearly to Flatter Minima than Gradient Flow in Shallow Linear Networks

main

Active

Gradient Descent;Implicit Regularization;Shallow Networks;Linear Networks

optimization

3;3;5;5

4;3;3;4

1;3;4;2

1;2;1;2

1;1;3;1

4

3.5

2.5

1.5

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":...

vyF5aim4US

QFree-Det: Query-Free Detector with Transformer and Sequential Matching

main

Active

free-object prediction;query-free;detecting ambiguity;location-deduplication decoder

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

5;5;5;6

5;3;5;4

3;3;3;3

1;3;2;3

3;3;3;2

5.25

4.25

3

2.25

2.75

-0.174078

[ { "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":...

vyFSyfiOIu

Knowledge-enhanced Multimodal ECG Representation Learning with Arbitrary-Lead Inputs

main

Active

Electrocardiogram;healthcare;physiological signals

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

3;3;3;5;5;6

4;5;4;5;4;4

3;3;3;3;3;3

2;1;2;2;3;3

1;2;2;3;2;3

4.166667

4.333333

3

2.166667

-0.097129

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vyHFTsOUWu

Instruction Following without Instruction Tuning

main

Active

instruction tuning;instruction following;ablation;rule-based

foundation or frontier models, including LLMs

3;3;6;10

4;4;4;5

2;2;4;4

2;2;3;4

3;2;4;3

5.5

4.25

3

2.75

3

0.904534

[ { "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":...

vyflgpwfJW

DiscoveryBench: Towards Data-Driven Discovery with Large Language Models

main

Active

data-driven discovery;data analysis;large language models;hypothesis generation;hypothesis verification

datasets and benchmarks

5;8;8

4;4;3

2;4;3

3;3;4

2;3;3

7

3.666667

3

3.333333

2.666667

-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":...

vyzPMQ5weJ

TURNIP: A “Nondeterministic” GPU Runtime with CPU RAM Offload

main

Active

CPU Offload;Memory Management;Nondeterministic Execution;Machine Learning System

infrastructure, software libraries, hardware, systems, etc.

5;5;5;5;6

3;4;3;3;4

3;2;2;2;2

2;2;2;2;3

2;2;2;3;4

5.2

3.4

2.2

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": 3 }, "contribution": { "value":...

vzItLaEoDa

Open-World Reinforcement Learning over Long Short-Term Imagination

main

Active

World models;reinforcement learning;visual control

reinforcement learning

5;6;6;8

3;4;4;4

2;3;3;3

3;3;3;4

3;3;3;3

6.25

3.75

2.75

3.25

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": 3 }, "contribution": { "value":...

vzrs42hgb0

DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks

main

Active

Knowledge Distillation;Hypergraph Neural Networks;Contrastive Learning.

transfer learning, meta learning, and lifelong learning

5;5;6

5;5;4

2;3;2

2;2;3

2;3;3

5.333333

4.666667

2.333333

2.666667

-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":...

w0389y0W9D

Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscape

main

Active

low-rank adaption;flat minima;efficient training

optimization

5;5;6;6

4;4;5;4

3;2;3;3

3;3;4;3

5.5

4.25

2.75

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": 4 }, "contribution": { "value":...

w0MAu8vjwj

MOSLIM:Align with diverse preferences in prompts through reward classification

main

Active

Large Language Models;Multi-objective alignment;Reward modeling

alignment, fairness, safety, privacy, and societal considerations

3;3;5;5

4;3;3;2

2;3;3;2

2;2;2;2

1;2;3;3

4

3

2.5

2

2.25

-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": 2 }, "contribution": { "value":...

w0b7fCX2nN

Leveraging the Context through Multi-Round Interactions for Jailbreaking Attacks

main

Active

LLM jailbreak;trustworthy ML;safety AI

alignment, fairness, safety, privacy, and societal considerations

3;3;3;6

5;5;3;4

2;3;2;3

2;1;2;4

2;3;2;3

3.75

4.25

2.5

2.25

2.5

-0.174078

[ { "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":...

w0es2hinsd

RD2Bench: Toward Data-Centric Automatic R&D

main

Active

Real-world Data-centric automatic R&D Benchmark;data-centric automatic R&D;trustworthy models

datasets and benchmarks

3;3;6;8

3;3;3;4

2;2;3;4

2;3;3;3

5

3.25

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": 3 }, "contribution": { "value":...

w0jk3L3IjV

Breaking the Detection-Generalization Paradox on Out-Of-Distribution Data

main

Active

Trustworthy Machine Learning; Out of distribution data

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

5;5;6

4;2;5

3;2;3

1;2;3

3;2;4

5.333333

3.666667

2.666667

2

3

0.755929

[ { "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":...

w0lhe9prqH

Dual Caption Preference Optimization for Diffusion Models

main

Active

Preference Optimization;Diffusion Models;Alignment

generative models

3;5;6;6

3;3;2;3

2;3;3;3

2;2;2;3

3;2;3;4

5

2.75

2.25

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": 3 }, "contribution": { "value":...

w10KdRwcMk

Revisiting the Variational Information Bottleneck

main

Active

information bottleneck;information theory;representation learning;adversarial attacks;regularization;supervised learning

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

3;3;5;6

5;3;5;4

1;1;2;3

1;2;3;2

1;1;3;3

4.25

1.75

2

0.174078

[ { "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":...

w1MEIGDepc

FlowAgent: a New Paradigm for Workflow Agent

main

Active

workflow;LLM-based agent;task-oriented dialog

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

3;5;5;5

5;3;4;4

2;2;2;2

2;2;3;3

4.5

4

2

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":...

w1Pwcx5hPp

Geometrically Constrained Gaussian Splatting SLAM

main

Active

3DGS;SLAM;Robotics

applications to robotics, autonomy, planning

3;5;5

5;3;4

2;3;2

1;2;2

2;2;2

4.333333

4

2.333333

1.666667

2

-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": 4 }, "contribution": { "value":...

w2BELPYbU0

I-Max: Maximize the Resolution Potential of Pre-trained Rectified Flow Transformers with Projected Flow

main

Active

Diffusion Model;Generative Model;Image Generation;High-resolution

generative models

5;5;5;6

3;4;3;4

2;3;2;3

3;2;3;3

2;2;3;2

5.25

3.5

2.5

2.75

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": 3 }, "contribution": { "value":...

w2C7gJqaai

Integrated Multi-system Prediction via Equilibrium State Evaluation

main

Active

Multi-system;Equilibrium;Prediction

learning on time series and dynamical systems

1;1;5

5;1;4

1;1;2

1;1;3

2.333333

3.333333

1.333333

1.666667

0.27735

[ { "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": 1 }, "contribution": { "value":...

w2HL7yuWE2

Uncertainty-aware Guided Diffusion for Missing Data in Sequential Recommendation

main

Active

Diffusion Models;Recommender Systems;Missing Data

generative models

5;5;6;10

3;4;2;1

3;2;3;4

2;2;2;4

3;2;3;4

6.5

2.5

3

2.5

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":...

w2HYVwXhMh

Unlocking Exocentric Video-Language Data for Egocentric Video Representation Learning

main

Active

video-language pretraining;egocentric video

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

5;5;6;6

4;4;5;4

3;2;3;3

2;2;3;3

3;3;3;3

5.5

4.25

2.75

2.5

3

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":...

w2qzdlvPMK

Decoupled Data Augmentation for Improving Image Classification

main

Active

Data augmentation;Diffusion;Image classification

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

3;5;5;6

4;4;4;4

2;3;3;3

2;2;2;3

3;2;3;3

4.75

4

2.75

2.25

2.75

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": null, "details_of_ethi...

w2uIJiHTIA

Multilayer Correlation Clustering

main

Active

Clustering;Correlation Clustering;Multilayer Networks;Approximation Algorithms

optimization

3;5;5;6

3;4;4;3

2;3;3;3

3;3;3;3

4.75

3.5

2.75

3

0.229416

[ { "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":...

w3iM4WLuvy

Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control

main

Active

Decision Frequency;Action Sequence Generation;Model-Based Training;Model-Free Control;Efficient Learning;Reinforcement Learning

applications to robotics, autonomy, planning

3;3;5;6

4;3;4;2

1;2;3;3

3;2;2;3

2;2;2;3

4.25

3.25

2.25

2.5

2.25

-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":...

w3rbBVJ9Jg

PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Spatiotemporal Prediction

main

Active

PDEs;physics encoding;data-driven modeling

learning on time series and dynamical systems

1;5;5;5

4;4;2;3

2;2;3;3

1;3;2;3

1;3;2;1

4

3.25

2.5

2.25

1.75

-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":...

w4C4z80w59

Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models

main

Active

Stable Diffusion;Text-to-Image Generation;Concept Erasure

alignment, fairness, safety, privacy, and societal considerations

5;5;5;6

2;3;4;4

3;2;3;3

3;2;3;4

3;2;2;3

5.25

3.25

2.75

3

2.5

0.522233

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w4gkS9RsWh

Think or Remember? Detecting and Directing LLMs Towards Memorization or Generalization

main

Active

LLM;generalization;memorization;neuron differentiation;behavior identification;inference-time intervention;behavior control

foundation or frontier models, including LLMs

3;5;5;5

4;4;4;3

2;3;3;3

1;2;2;2

2;3;3;3

4.5

3.75

2.75

1.75

2.75

-0.333333

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w5Q3r8Jq3v

DiffusionTrend: A Minimalist Approach to Virtual Fashion Try-On

main

Active

Virtual Try-on; Diffusion Model; Image Editing

generative models

1;3;5;5

4;5;5;4

1;1;3;3

2;1;2;2

1;3;3;3

3.5

4.5

2

1.75

2.5

0.301511

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w5ZtXOzMeJ

Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation

main

Active

domain adaptation; NLI; RAG; document-grounded; NLP;

alignment, fairness, safety, privacy, and societal considerations

3;6;8

4;3;2

2;3;3

3;3;3

5.666667

3

2.666667

3

-0.993399

[ { "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":...

w5h443GIGo

On the Convergence of Symbolic Pattern Forests and Silhouette Coefficients for Robust Time Series Clustering

main

Active

Data Mining;Time Series;Clustering

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

1;3;3

4;3;4

1;2;2

2;2;1

2.333333

3.666667

1.666667

-0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "We sincerely thank you for your constructive and detailed feedback.\n\nW1. Regarding novelty...

w5pErXbwQl

Noise-Robust Preference Losses for Deep Regression Models

main

Active

Regression;Robustness;Alignment

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

3;3;3

4;3;4

2;2;3

1;2;2

3;2;3

3

3.666667

2.333333

1.666667

2.666667

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": 4 }, "contribution": { "value":...

w6YS9A78fq

A Simple Diffusion Transformer on Unified Video, 3D, and Game Field Generation

main

Active

Diffusion Probabilistic Fields;World Model

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

5;5;6

2;4;4

2;2;3

1;2;3

5.333333

3.333333

2.333333

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":...

w6mjerkePG

Roll-AE: A Spatiotemporal Invariant Autoencoder for Neuronal Electro-Physiology

main

Active

autoencoder;electrophysiology;self-supervised learning

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

3;3;3;5

4;4;3;3

1;2;3;3

1;2;2;2

2;2;1;3

3.5

2.25

1.75

2

-0.57735

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w6nlcS8Kkn

To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

main

Active

Chain-of-Thought;Large Language Models;Textual Reasoning

foundation or frontier models, including LLMs

6;6;8

4;4;3

3;3;4

2;2;4

2;4;4

6.666667

3.666667

3.333333

2.666667

3.333333

-1

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w6rHCuN3YG

In-Context Editing: Learning Knowledge from Self-Induced Distributions

main

Active

Knowledge Editing;In-Context Learning;Language Models

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

5;6;6;8

4;3;4;3

2;2;3;3

3;3;3;3

2;4;2;3

6.25

3.5

2.5

3

2.75

-0.688247

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w7BGq6ozOL

Advancing Algorithmic Trading with Large Language Models: A Reinforcement Learning Approach for Stock Market Optimization

main

Active

Algorithmic trading;Stock market;Large language models;Deep reinforcement learning

foundation or frontier models, including LLMs

1;3;6;8

5;4;4;5

2;2;3;3

1;2;3;4

1;1;3;3

4.5

2.5

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": 5 }, "contribution": { "value":...

w7P92BEsb2

PIED: Physics-Informed Experimental Design for Inverse Problems

main

Active

Physics-Informed Neural Network;PINNs;Experimental Design;AI For Science

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

5;6;6;8

3;3;2;2

3;3;3;3

2;3;3;3

3;3;3;3

6.25

2.5

3

2.75

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": 2 }, "contribution": { "value":...

w7pMjyjsKN

Counterfactual Concept Bottleneck Models

main

Active

Concept Bottleneck Models;Concept Based Model;Counterfactuals;Explainable AI;Interpretability

interpretability and explainable AI

5;6;6;8

3;4;3;4

2;3;3;3

3;4;3;3

6.25

3.5

2.75

3.25

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":...

w7vn6ah0Qg

KokerNet: Koopman Kernel Network for Time Series Forecasting

main

Active

Spectral kernel;Koopman operator;Time series

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

3;3;6;6

4;4;3;4

3;2;3;3

2;2;3;3

3;2;4;2

4.5

3.75

2.75

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": 4 }, "contribution": { "value":...

w8LMtFY97b

Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging

main

Active

Image registration;uncertainty estimation;medical image analysis

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

3;6;8

4;3;4

2;3;4

1;2;3

2;3;4

5.666667

3.666667

3

2

3

-0.114708

[ { "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":...

w9bWY6LvrW

Marvel: Accelerating Safe Online Reinforcement Learning with Finetuned Offline Policy

main

Active

Offline-to-Online Fine-tuning;Safe Reinforcement Learning;Constrained Markov Decision Processes;Reinforcement Learning

reinforcement learning

3;5;5;5;6

3;4;4;4;3

3;2;2;2;3

2;2;2;2;3

2;3;2;2;3

4.8

3.6

2.4

2.2

2.4

0.25

[ { "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":...

w9tS6NRmxX

Few-shot In-context Preference Learning using Large Language Models

main

Active

Large Language Models;Preference-based RL;Reinforcement Learning from Human Feedback;Reward Design

reinforcement learning

3;3;5;5

2;3;5;4

2;3;3;3

2;2;3;2

3;4;3;4

4

3.5

2.75

2.25

3.5

0.894427

[ { "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":...

wA2RMD2AFq

Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training

main

Active

Low-Bit Quantization;Multi-Task Learning;Co-Training;Quantization-Aware Training;Quantization Scale

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

6;6;6

5;3;3

3;3;4

3;3;3

3;4;4

6

3.666667

3.333333

3

3.666667

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":...

wAXsx2MYgV

Modeling dynamic social vision highlights gaps between deep learning and humans

main

Active

NeuroAI;vision;fMRI;deep learning;social perception

applications to neuroscience & cognitive science

5;5;6;6

2;3;3;3

3;3;2;3

3;2;2;3

2;3;2;3

5.5

2.75

2.5

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":...

wAemQcyWqq

Oblivious Unlearning by Learning: Machine Unlearning Without Exposing Erased Data

main

Active

Machine unlearning;Privacy Preserving

alignment, fairness, safety, privacy, and societal considerations

3;5;5;5;6;6

3;5;3;4;3;3

2;2;3;3;3;2

2;3;2;3;3;2

3;3;3;3;2;2

5

3.5

2.5

2.666667

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":...

wCIkU0XR4f

How Does Data Diversity Shape The Weight Landscape of Neural Networks?

main

Active

data diversity;regularization;data augmentation;synthetic data;transfer learning

interpretability and explainable AI

3;3;5;5

3;4;3;3

2;2;3;3

1;2;2;3

2;2;3;3

4

3.25

2.5

2

2.5

-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":...

wCNuEA5MSv

Language Model Empowered Spatio-Temporal Forecasting via Physics-Aware Reprogramming

main

Active

spatio-temporal forecasting;time series forecasting

learning on time series and dynamical systems

3;5;5;8

4;4;4;2

3;3;3;3

2;2;2;4

3;3;3;3

5.25

3.5

3

2.5

3

-0.889297

[ { "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":...

wCO966fAHd

Dual-level Bias Mitigation via Fairness-guided Distribution Discrepancy

main

Active

Fairness;Trust-worthy Machine Learning

alignment, fairness, safety, privacy, and societal considerations

3;3;5

4;4;4

2;2;2

2;2;3

3.666667

4

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":...

wCOJpXm0Me

Is Large-scale Pretraining the Secret to Good Domain Generalization?

main

Active

Domain Generalization;Robustness;CLIP;Pretraining

transfer learning, meta learning, and lifelong learning

3;5;6;6

4;5;5;3

2;2;3;3

2;2;2;3

5

4.25

2.5

2.25

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":...

wCXAlfvCy6

LongVILA: Scaling Long-Context Visual Language Models for Long Videos

main

Active

Large language models;Long context;Multi-modality;Video understanding

generative models

5;6;6

5;4;4

3;3;4

5.666667

4.333333

3.333333

-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":...

wCwz1F8qY8

Prediction of Protein-protein Contacts with Structure-aware Single-sequence Protein Language Models

main

Active

Protein bioinformatics;Protein language models;Protein-protein contact prediction;Protein representations;Deep neural networks

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

3;3;6;6

5;3;3;4

2;2;3;3

1;2;3;3

2;2;3;2

4.5

3.75

2.5

2.25

-0.301511

[ { "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":...

wD2sfTDy1W

LADI v2: Multi-label Dataset and Classifiers for Low-Altitude Disaster Imagery

main

Withdraw

computer vision;dataset;disaster;aerial imagery;multilabel classification;damage assessment

datasets and benchmarks

Sam Scheele;Katherine Picchione;Jeffrey Liu

~Sam_Scheele1;~Katherine_Picchione1;~Jeffrey_Liu1

3;3;3;6

3;5;4;4

3;2;2;3

2;2;1;3

3;2;3;2

3.75

4

2.5

2

2.5

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": null, "details_of_ethi...

wDao6K52aN

Catastrophic Token Leakage in Convolutional Sequence Modeling and How to Mitigate It

main

Withdraw

Convolutional Models;LLMs;Language Modeling;Fast Fourier Transforms

foundation or frontier models, including LLMs

Naman Agarwal;Evan Dogariu;Xinyi Chen;Daniel Suo;Vladimir Feinberg;Elad Hazan

~Naman_Agarwal1;~Evan_Dogariu1;~Xinyi_Chen1;~Daniel_Suo1;~Vladimir_Feinberg2;~Elad_Hazan1

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": null, "details_of_ethi...

wDcunIOAOk

Intrinsic User-Centric Interpretability through Global Mixture of Experts

main

Active

interpretability;human-centric computing;mixture-of-experts

interpretability and explainable AI

5;5;6;8

3;4;3;3

2;3;3;3

2;2;3;3

3;4;3;4

6

3.25

2.75

2.5

3.5

-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": 3 }, "contribution": { "value":...

wE5xp3zBaQ

The Good, the Bad and the Ugly: Watermarks, Transferable Attacks and Adversarial Defenses

main

Active

Watermarks;Adversarial Defenses;Transferable Attacks;Interactive Proof Systems;Cryptography;Backdooring;Game Theory;Learning Theory

alignment, fairness, safety, privacy, and societal considerations

3;5;5;6

3;4;2;4

1;2;3;3

2;3;2;3

2;2;3;3

4.75

3.25

2.25

2.5

0.345857

[ { "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":...

wE8wJXgI9T

It's Not a Modality Gap: Characterizing and Addressing the Contrastive Gap

main

Active

Multi Modal Representation Learning;Contrastive Representation Learning;Modality Gap;CLIP

interpretability and explainable AI

3;3;5;6

4;4;3;5

2;2;2;3

2;2;3;3

4.25

4

2.25

2.5

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": 4 }, "contribution": { "value":...

wElgE9qBb5

Mambular: A Sequential Model for Tabular Deep Learning

main

Active

Tabular Deep Learning;Mamba;Sequential Models;SSM;Recurrent Neural Networks

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

3;3;3;6

4;3;5;5

1;2;3;3

2;2;3;4

3.75

4.25

2.25

2.75

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": 5 }, "contribution": { "value":...

wF8eG12wtw

Understanding Benefit of Personalization: Beyond Classification

main

Active

Explainability;Fairness;Personalization

interpretability and explainable AI

1;3;3;8

3;4;4;4

2;2;1;3

1;2;2;4

2;2;2;4

3.75

2

2.25

2.5

0.61396

[ { "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":...

wF9Cz2PknU

MagicPose4D: Crafting Articulated Models with Appearance and Motion Control

main

Active

4D Generation; 3D Reconstruction; Motion Transfer; Animation; Rigging

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

3;5;5;6

5;3;4;4

2;3;4;3

2;3;3;2

3;2;4;3

4.75

4

3

2.5

3

-0.648886

[ { "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":...

wFAyp2CUnq

AdaptVis: Spatial Understanding in Vision-Language Models Requires Adaptive Attention

main

Active

Vision Language Models;Uncertainty;Mechanistic interpretability;Constrain Decoding;Spatial Understanding

foundation or frontier models, including LLMs

3;3;5;5

4;3;4;4

2;2;3;2

3;2;3;2

2;2;4;1

4

3.75

2.25

2.5

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": 3 }, "contribution": { "value":...

wFD16gwpze

Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra

main

Active

Statistical mechanics;neural scaling laws

learning theory

6;6;6

3;3;4

3;4;4

2;2;3

3;4;3

6

3.333333

3.666667

2.333333

3.333333

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":...

wFIf8zpzTI

Out-Of-Context and Out-Of-Scope: Subliminal Priming for Large Language Models

main

Active

representation learning;generative models;learning theory;applications to neuroscience & cognitive science

applications to neuroscience & cognitive science

1;3;6

3;3;4

1;1;3

1;2;2

2;3;2

3.333333

1.666667

2.333333

0.917663

[ { "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":...

wFg0shwoRe

Expected Return Symmetries

main

Active

multi-agent reinforcement learning;zero-shot coordination

reinforcement learning

5;5;6;8

3;3;1;3

2;3;3;4

2;3;3;3

3;2;2;3

6

2.5

3

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": 1 }, "contribution": { "value":...

wFs2E5wCw6

Tree of Attributes Prompt Learning for Vision-Language Models

main

Active

Prompt Learning;Vision-Language Models;Tree of Attributes

transfer learning, meta learning, and lifelong learning

5;5;5;6;8

5;1;3;4;5

2;2;3;3;4

3;3;3;3;3

5.8

3.6

2.8

3

0.527102

[ { "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":...

wGVOxplEbf

SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation

main

Active

Diffusion Model;Fine-tuning

generative models

5;5;5;5;8

2;3;4;3;5

2;2;2;3;4

2;2;3;3;4

3;3;3;3;4

5.6

3.4

2.6

2.8

3.2

0.784465

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "Dear Authors,\n\nThanks for the interesting work SARA. It is important for the research comm...

wGa2plE8ka

Learning Fine-Grained Representations through Textual Token Disentanglement in Composed Video Retrieval

main

Active

Composed Video Retrieval; Fine-grained Representation; Feature Disentanglement

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

3;5;6;6

4;5;5;5

2;2;3;3

2;3;2;3

5

4.75

2.5

0.942809

[ { "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":...

wGqf7YMF8R

HDFlow: Enhancing LLM Complex Problem-Solving with Hybrid Thinking and Dynamic Workflows

main

Active

Large Language Models (LLMs);Complex Reasoning;Hybrid Thinking;Symbolic Reasoning

foundation or frontier models, including LLMs

3;5;5;6

4;5;4;4

2;3;3;4

2;3;2;4

3;3;3;4

4.75

4.25

3

2.75

3.25

0.132453

[ { "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":...

wH8XXUOUZU

Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

main

Active

efficient high-resolution diffusion models

generative models

5;6;6;6;8

4;4;4;4;2

4;3;3;2;3

3;3;3;2;3

4;2;3;2;4

6.2

3.6

3

2.8

3

-0.918559

[ { "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":...

wHLMsM1SrP

Needle Threading: Can LLMs Follow Threads Through Near-Million-Scale Haystacks?

main

Active

LLMs;Long Context;Evaluation

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

5;6;8

2;4;3

3;3;3

2;3;4

6.333333

3

0.327327

[ { "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":...

wHebuIb6IH

VLMaterial: Procedural Material Generation with Large Vision-Language Models

main

Active

generative model;procedural material;appearance modeling

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

6;6;6;8

4;3;4;5

3;3;4;4

3;3;3;3

3;3;3;4

6.5

4

3.5

3

3.25

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":...

wHsAi8kINK

Fed3+2p: Training different parts of neural network with two-phase strategy

main

Active

Federated Learning;Distributed Machine Learning;Neural Networks;Non-IID Data

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

3;3;5

4;5;4

2;2;3

2;1;2

2;1;3

3.666667

4.333333

2.333333

1.666667

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": 5 }, "contribution": { "value":...

wI5uHZLeCZ

Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs

main

Active

adversarial attacks;adversarial training;jailbreaks;trojans;backdoors;unlearning;robustenss

alignment, fairness, safety, privacy, and societal considerations

3;3;3;5

5;4;3;4

3;3;2;2

3;2;2;2

2;1;2;2

3.5

4

2.5

2.25

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":...

wJ3GeGLFmc

Towards Accurate and Efficient Sub-8-Bit Integer Training

main

Active

Low-precision training; Model compression

optimization

3;5;5;5

4;4;4;4

2;3;2;2

2;2;2;2

2;3;3;2

4.5

4

2.25

2

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":...

wJ6Bx1IYrQ

EEGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training

main

Withdraw

EEG;Brain-computer interface;Representation learning

applications to neuroscience & cognitive science

Tongtian Yue;Shuning Xue;Xuange Gao;Yepeng Tang;Longteng Guo;Jie Jiang;Jing Liu

~Tongtian_Yue1;~Shuning_Xue2;~Xuange_Gao1;~Yepeng_Tang1;~Longteng_Guo1;~Jie_Jiang2;~Jing_Liu1

3;3;5;5

5;5;4;4

2;1;3;3

2;2;3;2

2;3;2;4

4

4.5

2.25

2.75

-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...

wJGXiHQwpZ

MaskTwins: Dual-form Complementary Masking for Domain-Adaptive Image Segmentation

main

Active

domain adaptation;unsupervised learning;masked image modeling;semantic segmentation;complementary masking

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

3;5;6

4;3;3

3;2;3

2;2;3

3;3;3

4.666667

3.333333

2.666667

2.333333

3

-0.944911

[ { "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":...

wJPMe9UKow

Posterior Label Smoothing for Node Classification

main

Active

node classification;label smoothing

learning on graphs and other geometries & topologies

3;5;5;8

4;4;1;3

3;2;3;3

2;2;3;2

2;4;3;3

5.25

3

2.75

2.25

3

-0.228665

[ { "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":...

wJVZkUOUjh

EXAGREE: Towards Explanation Agreement in Explainable Machine Learning

main

Active

Explainable Machine Learning;Explainable Artificial Intelligence;Rashomon Sets

interpretability and explainable AI

1;1;3;3

4;4;4;3

1;1;3;2

1;2;1;1

2

3.75

1.75

1.25

-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": "> As a result, the metrics, which are based on an unsubstantiated assumption that agreement ...

wJlzUR5sFl

MCUCoder: Adaptive Bitrate Learned Video Compression for IoT Devices

main

Active

Efficient Video Compression;IoT Devices;Learned Video Compression;Adaptive Bitrate Compression;Microcontrollers

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

3;5;5;5

4;5;4;4

1;3;3;3

2;2;3;3

1;2;3;3

4.5

4.25

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":...

wJv4AIt4sK

Effective Interplay between Sparsity and Quantization: From Theory to Practice

main

Active

theory of compression;model compression;quantization;max-scaled numerical encoding;sparsity;unstructured sparsity;structured sparsity;N:M sparsity;large language models;magnitude pruning;post-training quantization;efficient inference

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

5;6;8;8

4;4;4;4

2;2;4;3

3;3;3;3

3;3;4;4

6.75

4

2.75

3

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":...

wKOoWTBMZe

KEYPOINT-GUIDED 4D GAUSSIAN SPLATTING WITH DECOUPLED SPATIO-TEMPORAL FLOW REFINEMENT

main

Withdraw

Keypoint;4D Gaussian Splatting

generative models

Jusheng Zhang;Jinzhou Tang;Zhuojie Yang;Sidi Liu;Kaiyu Wu;Mingyan Li;Jian Wang;Keze Wang;Yufeng Yang

~Jusheng_Zhang3;~Jinzhou_Tang1;~Zhuojie_Yang1;~Sidi_Liu1;~Kaiyu_Wu1;~Mingyan_Li2;~Jian_Wang10;~Keze_Wang1;~Yufeng_Yang2

3;3;5

4;5;3

2;1;2

2;2;3

1;1;2

3.666667

4

1.666667

2.333333

1.333333

-0.866025

[ { "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 all very much for the constructive and insightful comments of all the reviewers." ...

wLR9d5ZFpY

No Training Data, No Cry: Model Editing without Training Data or Fine-tuning

main

Active

pruning;model editing;classwise unlearning

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

3;3;3

3;4;3

2;2;3

2;2;2

1;1;1

3

3.333333

2.333333

2

1

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":...

wLmJIs1uqG

LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace

main

Active

Bilevel Optimization;Lanczos Process;Krylov Subspace

optimization

5;5;5;6

3;3;4;3

2;3;3;3

2;2;2;3

3;3;2;3

5.25

3.25

2.75

2.25

2.75

-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":...

wLnls9LS3x

Improved Algorithms for Kernel Matrix-Vector Multiplication

main

Active

Algorithms;Kernel Matrix;Kernel Density Estimation;Locality Sensitive Hashing;Fast Attention

learning theory

5;6;6;8

4;4;4;5

3;3;3;3

2;2;3;3

3;3;2;3

6.25

4.25

3

2.5

2.75

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": 5 }, "contribution": { "value":...

wLzhEQq2hR

Do Vision-Language Models Really Understand Visual Language?

main

Active

vision-language model;visual language;diagram reasoning;evaluation

interpretability and explainable AI

5;5;6;8

2;4;2;3

3;3;3;4

2;2;3;3

3;2;3;4

6

2.75

3.25

2.5

3

0

[ { "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 reviewer for the time! We would kindly point out that there are some misunderst...

wM2sfVgMDH

Diffusion-Based Planning for Autonomous Driving with Flexible Guidance

main

Active

diffusion planning;autonomous driving

applications to robotics, autonomy, planning

5;5;6;8

3;3;3;4

3;3;2;4

3;2;2;4

2;3;3;3

6

3.25

3

2.75

0.942809

[ { "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":...

wMRFTQwp1d

VideoEval: Comprehensive Benchmark Suite for Low-Cost Evaluation of Video Foundation Model

main

Active

Video Understanding;Video Foundation Model;Benchmark

datasets and benchmarks

3;3;5;5

5;4;4;4

2;3;3;2

1;2;2;3

3;2;3;4

4

4.25

2.5

2

3

-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":...

wMSZEP7BDh

Is Pontryagin's Maximum Principle All You Need? Solving optimal control problems with PMP-inspired neural networks

main

Active

prior knowledge;Pontryagin's Maximum Principle;optimal control

learning theory

3;5;5;5

5;4;3;4

3;3;3;2

1;2;3;2

3;3;3;1

4.5

4

2.75

2

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":...

wMgr7wBuUo

Credit-based self organizing maps: training deep topographic networks with minimal performance degradation

main

Active

Computer vision;Neuroscience;Convolutional Networks;topographical organization;self-organizing maps;functional organization

applications to neuroscience & cognitive science

3;6;6;8

4;4;3;4

3;3;3;3

1;2;3;3

3;3;4;3

5.75

3.75

3

2.25

3.25

-0.080845

[ { "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":...

wMj6PgKVuJ

softmax is not enough (for sharp out-of-distribution)

main

Active

softmax;transformers;out-of-distribution;sharpness;entropy

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

3;5;6;6;8

4;3;3;2;3

3;3;2;2;3

2;2;3;2;3

1;2;2;3;3

5.6

3

2.6

2.4

2.2

-0.583874

[ { "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":...

wN3KaUXA5X

Diffusion On Syntax Trees For Program Synthesis

main

Active

neurosymbolic;search;programming languages;inverse graphics

neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.)

6;6;6;8;8

3;3;3;5;4

3;3;4;3;3

2;3;3;3;3

3;2;3;4;4

6.8

3.6

3.2

2.8

3.2

0.918559

[ { "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":...

wNg0LibmQt

Gradient-based Jailbreak Images for Multimodal Fusion Models

main

Active

jailbreak;adversarial examples;multimodal;language models

alignment, fairness, safety, privacy, and societal considerations

3;3;3;6;8

4;4;3;3;4

1;3;2;3;3

1;2;1;3;4

1;3;3;3;4

4.6

3.6

2.4

2.2

2.8

0.039653

[ { "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":...

wNobG8bV5Q

LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases

main

Active

Large Language Models;Commonsense reasoning;Logical inference

foundation or frontier models, including LLMs

3;5;6;6

3;3;4;2

2;2;3;3

2;3;2;3

1;2;3;3

5

3

2.5

2.25

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":...

wO1NJLitPL

A Bregman Proximal Viewpoint on Neural Operators

main

Active

neural operators;proximal optimization;bregman divergence;fourier neural operator

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

3;5;5;8

4;3;2;4

2;3;3;3

1;2;3;3

1;2;1;3

5.25

3.25

2.75

2.25

1.75

0.12666

[ { "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":...

wO8WbhsjNG

Bilevel ZOFO: Bridging Parameter-Efficient and Zeroth-Order Techniques for Efficient LLM Fine-Tuning and Meta-Training

main

Active

Zeroth-order Fine-tuning;Parameter Efficient Fine-tuning;Large Language Models;Bilevel Optimization

foundation or frontier models, including LLMs

5;5;5;5

5;4;3;3

3;3;2;2

3;2;2;2

5

3.75

2.5

2.25

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":...

wP0nDEAlap

Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment

main

Active

Image Quality Assessment;Inductive Bias Regularization;Reference Knowledge

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

3;3;5;5

5;4;5;5

3;2;3;3

2;3;2;2

2;2;2;3

4

4.75

2.75

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": 5 }, "contribution": { "value":...

wPMRwmytZe

Progressive distillation induces an implicit curriculum

main

Active

knowledge distillation;feature learning;curriculum;sparse parity;PCFG;optimization;MLP;Transformer

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

6;6;6;8;8

3;3;3;4;3

4;3;3;3;4

3;3;3;4;3

4;3;3;4;4

6.8

3.2

3.4

3.2

3.6

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": 3 }, "contribution": { "value":...

wPStvOAtjR

LAMDA: Two-Phase Multi-Fidelity HPO via Learning Promising Regions from Data

main

Active

HPO;multi-fidelity;overlapping;promising regions

optimization

3;5;5;6

3;2;4;2

2;3;3;3

2;3;2;2

1;3;2;3

4.75

2.75

2.25

-0.345857

[ { "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":...

wPyTeUMRgh

SEAL: SEmantic-Augmented Imitation Learning via Language Model

main

Active

Large Language Models;Hierarchical Imitation Learning

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

3;3;5;6

4;4;5;4

2;3;4;4

2;2;3;3

2;3;3;3

4.25

3.25

2.5

2.75

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":...

wQEdh2cgEk

Process Reward Model with Q-value Rankings

main

Active

process reward model;reasoning

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

3;3;8;8;8

4;4;3;3;2

3;2;4;3;3

2;2;3;4;3

2;2;4;3;3

6

3.2

3

2.8

-0.872872

[ { "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":...