babytreecc/ICLR2025review · Datasets at Hugging Face

xUHL8mtSUL

Scalable Gaussian Process via Hilbert-Schmidt Singular Value Decomposition

main

Active

Scalability;Gaussian process regression;Hilbert Schmidt singular value decomposition;compact Mat\'ern

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

3;3;3;5;5

4;3;4;4;5

2;2;2;2;2

2;2;1;1;2

2;2;2;3;2

3.8

4

2

1.6

2.2

0.645497

[ { "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":...

xUMI52rrW7

Structural-Entropy-Based Sample Selection for Efficient and Effective Learning

main

Active

Sample selection;graph;structural entropy;blue noise sampling

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

3;5;5;8

3;4;4;4

2;2;2;3

3;3;3;3

5.25

3.75

2.25

3

0.727607

[ { "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":...

xVOMtecrAS

See Further When Clear: Adaptive Generative Modeling with Curriculum Consistency Model

main

Active

adaptive curriculum learning;noise schedule;flow matching;consistency models

generative models

3;3;5;5

5;4;4;3

2;2;2;4

2;2;3;2

2;1;2;3

4

2.5

2.25

2

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

xVU6rY37X9

Partial Channel Dependence with Channel Masks for Time Series Foundation Models

main

Active

Time Series;Foundation Model;Channel Dependence;Transformer

learning on time series and dynamical systems

3;3;5;5;6

5;3;4;4;3

2;1;2;3;2

2;2;2;2;3

2;2;3;3;3

4.4

3.8

2

2.2

2.6

-0.356348

[ { "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":...

xVefsBbG2O

Diffusion Models are Evolutionary Algorithms

main

Active

Machine learning;evolutionary computation;Evolutionary Algorithms;Diffusion Models;Optimization

generative models

3;3;6;8

4;4;3;4

2;2;3;3

2;2;3;2

2;2;3;3

5

3.75

2.5

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

xVw8YNEtH3

Reset Method based on the Theory of Manifold Optimization on Real Manifolds

main

Active

Manifold Optimization;Real Manifolds;Method;Deep Learning.

optimization

1;3;5

4;5;3

1;2;3

1;2;2

1;1;2

3

4

2

1.666667

1.333333

-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":...

xW4J2QlqRx

Context Matters: Leveraging Contextual Features for Time Series Forecasting

main

Active

Time series forecasting;Contextual features;Predictive modeling

learning on time series and dynamical systems

3;5;5;5

4;3;5;4

2;3;3;3

2;2;1;1

2;3;3;2

4.5

4

2.75

1.5

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

xXTkbTBmqq

OLMoE: Open Mixture-of-Experts Language Models

main

Active

large language models;mixture-of-experts;open-source

foundation or frontier models, including LLMs

8;8;10

2;3;5

4;4;4

3;4;4

4;4;4

8.666667

3.333333

4

3.666667

4

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":...

xYquBPHppn

A VARIATIONAL FRAMEWORK FOR GRAPH GENERATION WITH FINE-GRAINED TOPOLOGICAL CONTROL

main

Active

Controlled Graph Generation

generative models

3;3;5;6

5;4;5;2

3;1;2;3

2;2;2;3

3;2;2;3

4.25

4

2.25

2.5

-0.628539

[ { "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":...

xYzOkOGD96

Grounded Video Caption Generation

main

Withdraw

vision-language models;VLM;LLM;video grounding;automatic annotation;pseudo-labeling

datasets and benchmarks

Evangelos Kazakos;Cordelia Schmid;Josef Sivic

~Evangelos_Kazakos2;~Cordelia_Schmid1;~Josef_Sivic1

3;3;3;3;5;6

3;3;4;5;4;4

2;2;2;2;2;2

3;2;2;2;2;3

2;2;1;2;4;3

3.833333

2

2.333333

0.166574

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xZ2lTzfyFv

Improving Generalization with Flat Hilbert Bayesian Inference

main

Active

Bayesian Inference;Sharpness-aware Minimization

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

3;6;8;8

4;3;3;3

2;2;3;3

3;3;3;3

6.25

3.25

2.5

3

-0.916949

[ { "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":...

xaXvHdH9Y4

P-BERT: Hardware-Aware Optimization of BERT Using Evolutionary Techniques

main

Active

Model Compression;Large Language Models;Computation Complexity;BERT;Hardware-Aware

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

3;3;3;5;5

1;5;4;3;3

3;1;2;2;2

1;1;2;2;2

3;2;2;2;3

3.8

3.2

2

1.6

2.4

-0.123091

[ { "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":...

xaYlO03tIk

Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion

main

Active

Robotics;Imitation Learning;Visual Imitation Learning;Robustness;Diffusion Model;Diffusion Inversion

applications to robotics, autonomy, planning

3;6;6;6

3;4;3;3

1;3;3;3

3;3;3;3

2;3;4;2

5.25

3.25

2.5

3

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

xaafWdM5jI

UFGTime: Reforming the Pure Graph Paradigm for Multivariate Time Series Forecasting in the Frequency Domain

main

Active

Multivariate Time Series Forecasting;GNN;Pure Graph Paradigm

learning on time series and dynamical systems

1;3;5;5

4;4;4;4

1;1;2;3

1;1;2;2

2;1;3;2

3.5

4

1.75

1.5

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

xajif1l65R

Rethinking Dataset Quantization: Efficient Core Set Selection via Semantically-Aware Data Augmentation

main

Active

Coreset Selection;Dataset Quantization;Data Augmentation;Efficient Deep Learning;Semantically-Aware Augmentation

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

3;5;5;5

5;4;4;4

2;3;2;2

3;2;2;2

2;3;2;3

4.5

4.25

2.25

2.5

-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":...

xak8c9l1nu

Computational Explorations of Total Variation Distance

main

Active

total variation distance;TV distance;mixtures of products;equivalence checking;Ising models;computational complexity;FPRAS

learning theory

5;6;8;8;8

3;4;3;4;3

3;3;4;4;3

2;2;3;3;3

3;3;3;4;3

7

3.4

2.6

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":...

xam3sR3ffY

Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges

main

Active

LLMs;NLP;LLM Evaluation;LLM-as-a-Judge;Benchmarks

generative models

3;3;3;5;8

4;3;4;4;4

1;2;2;3;4

1;2;2;3;3

2;2;3;3;3

4.4

3.8

2.4

2.2

2.6

0.357217

[ { "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":...

xao3fIJC6M

ChipVQA: Benchmarking Visual Language Models for Chip Design

main

Active

Multimodal LLM; Chip Design and Manufacturing; VQA

datasets and benchmarks

3;3;3

5;5;4

3;2;2

2;2;2

4;2;2

3

4.666667

2.333333

2

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":...

xawA8X5dHq

Multiple Choice Questions and Large Languages Models: A Case Study with Fictional Medical Data

main

Active

large language models;medicine;benchmark;evaluation;clinical knowledge;multiple choice questions

datasets and benchmarks

3;3;5;5

4;5;4;4

2;2;2;3

2;1;2;2

2;2;3;2

4

4.25

2.25

1.75

2.25

-0.57735

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xayT1nn8Mg

Deep Signature: Characterization of Large-Scale Molecular Dynamics

main

Active

Molecular dynamics; representation learning; graph neural network; path signature

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

3;5;6

3;2;3

2;2;3

2;3;2

3;3;3

4.666667

2.666667

2.333333

3

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

xbW6EGve6a

Energy and Memory-Efficient Federated Learning with Ordered Layer Freezing and Tensor Operation Approximation

main

Active

Federated Learning;Resource-Constrained devices;Computation and Communication Overheads;Layer Freezing;Tensor Operation Approximation

optimization

3;5;6

4;3;3

2;2;2

3;3;3

4.666667

3.333333

2

3

-0.944911

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xbXydoejvY

CWPS: Efficient Channel-Wise Parameter Sharing for Knowledge Transfer

main

Active

Transfer Learning;Multi-Domain Learning;Multi-Task Learning

transfer learning, meta learning, and lifelong learning

3;5;5;6

4;2;4;3

2;2;2;3

2;2;2;2

4.75

3.25

2.25

2

-0.4842

[ { "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":...

xcHIiZr3DT

Vision-Based Pseudo-Tactile Information Extraction and Localization for Dexterous Grasping

main

Active

Pseudo-Tactile Information;Dexterous Grasping;Vision-Based Perception;Robotic Localization

applications to robotics, autonomy, planning

1;3;3;3

4;3;3;4

1;2;2;1

1;1;1;1

1;2;2;2

2.5

3.5

1.5

1

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":...

xcPN6Or88c

ImputeINR: Enhancing Time Series Imputation with Adaptive Group-based Implicit Neural Representations

main

Active

time series imputation;implicit neural representations

learning on time series and dynamical systems

3;3;5;6

4;5;4;3

1;2;3;3

2;2;3;3

2;3;3;3

4.25

4

2.25

2.5

2.75

-0.816497

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xdGsiYNfje

LLMScan: Causal Scan for LLM Misbehavior Detection

main

Active

Large Language Model;LLM Safety;LLM Misbehavior Detection;Causality Analysis;Model Scan

causal reasoning

3;3;5

4;4;3

1;2;3

2;2;3

1;2;3

3.666667

2

2.333333

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":...

xeP03R58RH

Rethinking Uncertainty Estimation in Natural Language Generation

main

Active

llm;nlg;uncertainty estimation;uncertainty measures;proper scoring rules

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

3;3;3;5;6

4;3;3;3;3

2;1;2;3;2

1;2;2;3;3

1;1;2;3;3

4

3.2

2

2.2

2

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

xfw92pDy2u

Distilled Diffusion Language Models

main

Active

diffusion language models;discrete diffusion;distillation

generative models

3;3;3;5

4;4;4;2

3;2;3;2

2;2;2;2

3.5

2.5

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":...

xgQfWbV6Ey

Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting

main

Active

generative model;retrieval augmented generation

generative models

3;5;6;6

4;4;4;4

3;3;3;3

2;2;3;3

3;2;3;3

5

4

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":...

xgtXkyqw1f

MindSearch: Mimicking Human Minds Elicits Deep AI Searcher

main

Active

language model;search engine;multi-agent system

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

5;6;6;6

4;4;3;4

2;3;3;3

2;3;4;3

3;3;3;3

5.75

3.75

2.75

3

-0.333333

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xhtqgW5b93

ToMA: Token Merging with Attention For Diffusion Models

main

Active

Diffusion;Token Merge;Attention

generative models

3;3;5;6;6

5;4;4;2;4

2;2;3;4;3

1;2;2;3;3

2;3;2;2;3

4.6

3.8

2.8

2.2

2.4

-0.662122

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xi3sDtf8A0

L-MSA: Layer-wise Fine-tuning using the Method of Successive Approximations

main

Active

layer-wise finetuning;parameter-efficient fine-tuning;method of successive approximations

foundation or frontier models, including LLMs

3;3;3;3

4;3;4;4

2;3;3;2

2;2;2;2

3;2;1;2

3

3.75

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

xiDJaTim3P

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models

main

Active

Federated learning;prompt learning;vision-language model;mixture of experts

alignment, fairness, safety, privacy, and societal considerations

3;6;6;6

4;3;5;2

2;3;3;3

2;2;3;3

1;2;3;3

5.25

3.5

2.75

2.5

2.25

-0.258199

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xiQNfYl33p

A Generic Framework for Conformal Fairness

main

Active

Fairness;Conformal Prediction;Graph Neural Networks

alignment, fairness, safety, privacy, and societal considerations

5;6;6;6

4;2;2;3

2;3;3;3

2;2;3;3

1;3;2;2

5.75

2.75

2.5

2

-0.870388

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xing7dDGh3

Vector-ICL: In-context Learning with Continuous Vector Representations

main

Active

large language models;in-context learning

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

3;5;6;6

4;4;4;3

2;2;4;3

2;2;3;3

2;2;4;3

5

3.75

2.75

2.5

2.75

-0.471405

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xiyzCfXTS6

Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design

main

Active

Combinatorial Bayesian Optimization;Game Theory;Gaussian Processes;Protein Design

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

3;3;6;8

3;3;3;4

2;2;3;3

2;2;2;4

2;3;3;3

5

3.25

2.5

2.75

0.816497

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xizpnYNvQq

Revisiting In-context Learning Inference Circuit in Large Language Models

main

Active

In-context Learning; Induction Circuit; Mechanistic Interpretability

interpretability and explainable AI

6;6;6;8

3;3;3;3

3;2;2;3

4;2;2;4

6.5

3

2.5

3

0

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xjKz6IxgCX

SafeWatch: An Efficient Safety-Policy Following Video Guardrail Model with Transparent Explanations

main

Active

Video Guardrail Model;Safe Foundation Models;Efficient LLMs Inference;LLM Safety;Multimodal Foundation Models

alignment, fairness, safety, privacy, and societal considerations

3;6;6;6

3;3;3;3

1;3;3;3

2;3;3;3

2;3;2;4

5.25

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

xjornbs7aT

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints

main

Active

Constrained MDPs;continuous action space;deep reinforcement learning

reinforcement learning

3;3;5;6

4;4;3;4

2;1;2;3

1;2;3;3

2;1;2;3

4.25

3.75

2

2.25

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

xkR3bcswuC

Generative Models: What Do They Know? Do They Know Things? Let's Find Out!

main

Active

Visual knowledge;Generative models;Intrinsic Images

interpretability and explainable AI

5;5;6;6

4;4;3;4

2;2;3;3

3;2;3;2

3;3;4;3

5.5

3.75

2.5

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":...

xkgfLXZ4e0

Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)

main

Active

brain encoding;fMRI;visual processing;multimodal instruction-tuned models;language decoder;LLMs;MLLMs

applications to neuroscience & cognitive science

5;6;6;6

4;3;2;4

2;3;3;3

3;3;3;3

5.75

3.25

2.75

3

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

xlbXRJ2XCP

MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks

main

Active

Graph neural networks;graph pooling;graph coarsening;maxcut

learning on graphs and other geometries & topologies

3;5;5;6

4;2;3;4

3;3;3;2

1;3;2;3

3;3;3;3

4.75

3.25

2.75

2.25

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

xljPZuprBA

Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms

main

Active

Random graph models;edge dependency;triangle density;subgraph densities;tractability;variability

learning on graphs and other geometries & topologies

3;5;5;6

4;3;3;4

3;3;2;3

2;2;3;3

2;2;2;3

4.75

3.5

2.75

2.5

2.25

-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":...

xlrpVyMIwz

Positional Encoder Graph Quantile Neural Networks for Geographic Data

main

Active

Graph Neural Networks (GNNs); Quantile regression; Geospatial data; Uncertainty quantification; Calibration; Model recalibration.

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

1;3;5;6

4;4;3;4

2;2;3;3

2;1;2;3

2;2;3;3

3.75

2.5

2

2.5

-0.375823

[ { "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":...

xlxDTVAbNM

Lowering Data Diversity can Accelerate Training: Case Studies in Synthetic Tasks

main

Active

synthetic tasks;data diversity;curriculum learning;data filtering;learning plateaus;batch gradients

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

1;3;5;5

4;4;4;3

2;1;3;3

1;1;2;2

1;2;3;3

3.5

3.75

2.25

1.5

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":...

xlxGsX1pc7

U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs

main

Active

Large Language Models (LLMs);Mathematical Reasoning;Benchmarking;University-Level Mathematics;Multimodal;Automatic Evaluation;Solution Assessment

datasets and benchmarks

5;5;5;6

4;3;4;3

2;2;2;2

2;2;2;3

2;2;3;3

5.25

3.5

2

2.25

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":...

xmgvF0sLIn

Elucidating the Design Space of Text-to-Audio Models

main

Active

audio generation;text-to-audio;synthetic data;diffusion;flow matching

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

3;5;5;6

4;5;4;5

2;4;3;4

2;3;2;4

3;4;3;4

4.75

4.5

3.25

2.75

3.5

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

xnF2U0ro7b

Feature-Based Online Bilateral Trade

main

Active

bilateral trade;online learning;contextual bandits

reinforcement learning

6;6;8;8

3;4;3;3

2;3;4;4

2;3;3;3

3;3;3;2

7

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

xnWikQRJBR

M3CoL: Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification

main

Active

Contrastive learning;multimodal learning;representation learning;mutlimodal classification

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

3;5;5;5

4;3;2;3

2;3;3;2

2;2;2;2

3;3;3;2

4.5

3

2.5

2

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":...

xnssGv9rpW

SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models

main

Active

Crystals;Symmetry;Materials;Diffusion;Generative Models;Equivariance

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

6;8;8

3;3;4

3;3;3

2;3;4

4;3;3

7.333333

3.333333

3

3.333333

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":...

xoIeVdFO7U

Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning

main

Active

unsupervised learning;reinforcement learning;mutual information;successor feature

reinforcement learning

5;8;8;8

3;3;3;2

4;4;3;4

1;4;3;4

4;4;3;4

7.25

2.75

3.75

3

3.75

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

xoUUCS9IGl

PoseCheck: Generative Models for 3D Structure-based Drug Design Produce Unrealistic Poses

main

Active

generative models;drug design;benchmarks

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

3;5;5;6

4;5;4;3

2;3;3;3

1;3;3;2

2;4;3;3

4.75

4

2.75

2.25

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

xoW1Cb4MkP

ANYTEXT2: Visual Text Generation and Editing with Customizable Attributes

main

Withdraw

Text-to-Image;Visual Text Generation;Visual Text Editing;Customizable Attributes

generative models

Yuxiang Tuo;Yifeng Geng;Liefeng Bo

~Yuxiang_Tuo2;~Yifeng_Geng2;~Liefeng_Bo1

3;5;5;5

4;4;3;3

4;3;2;3

3;2;2;2

3;3;3;3

4.5

3.5

3

2.25

3

-0.57735

[ { "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...

xoXn62FzD0

Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo

main

Active

Sequential Monte Carlo;Language Models;Semantic parsing;Bayesian inference;Probabilistic programming;SMC

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

5;6;6;8

3;4;3;5

3;3;3;3

2;3;3;3

2;4;3;3

6.25

3.75

3

2.75

3

0.899229

[ { "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":...

xof0bvftR1

Knockout: A simple way to handle missing inputs

main

Active

Applied Machine Learning;Marginalization;Missing inputs;Multi-modality

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

3;3;6;6

3;4;3;3

3;3;3;3

2;2;3;3

3;3;3;4

4.5

3.25

3

2.5

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":...

xom3YUQfbK

A Language Model based Model Manager

main

Active

Large Language Models;Model Manager;Verbalization;Differentiation

interpretability and explainable AI

3;3;3;5

5;3;4;4

3;2;1;2

2;2;2;2

3;3;2;2

3.5

4

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":...

xpmDc76RN2

Understanding Optimization of Operator Networks with Variational Loss for Solving PDEs

main

Active

Restriced Strong Convexity;Operator Learning;Variational Loss;Scientific machine learning

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

1;3;3

3;3;4

2;2;2

2;1;2

2;2;1

2.333333

3.333333

2

1.666667

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

xqEeGja6zq

Components Beat Patches: Eigenvector Removal for Robust Masked Image Modelling

main

Active

Self-supervised Representation Learning; Unsupervised Representation Learning; Visual Representation Learning

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

3;3;8;8

4;2;4;4

2;1;3;4

1;1;3;3

3;3;4;4

5.5

3.5

2.5

2

3.5

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":...

xrWOR5wSOz

Replacing Implicit Regression with Classification in Policy Gradient Reinforcement Learning

main

Active

reinforcement learning; policy gradient RL; actor-critic

reinforcement learning

3;5;5;8

4;4;3;3

2;3;3;3

1;2;2;3

2;3;3;2

5.25

3.5

2.75

2

2.5

-0.70014

[ { "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":...

xrXci5YGm7

Emergent properties with repeated examples

main

Active

transformers;learning on repeated examples;emergence

foundation or frontier models, including LLMs

3;5;5;6

4;3;3;3

2;2;3;3

1;2;3;3

3;3;3;3

4.75

3.25

2.5

2.25

3

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

xrazpGhJ10

SemCLIP: Aligning vision-language encoder models to semantic spaces for stability in retrieval

main

Active

Semantic-preserving queries;Vision-language encoder models;Stability of retrieval;joint embeddings

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

5;5;6;6

4;4;4;4

2;2;3;3

2;3;3;3

2;2;3;3

5.5

4

2.5

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

xreOs2yjqf

EvalAlign: Supervised Fine-Tuning Multimodal LLMs with Human-Aligned Data for Evaluating Text-to-Image Models

main

Active

Text-to-Image Generative Models;Evaluation Metrics;Multimodal Large Language Models (MLLMs);Text-Image Consistency;Image Generation Fidelity;Supervised Fine-Tuning (SFT);Human Evaluative Judgments

datasets and benchmarks

3;5;5;6

5;4;5;4

2;3;2;3

3;2;2;3

4.75

4.5

2.5

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

xrgXaOV6dK

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge?

main

Active

LLM-as-a-Judge;AI annotators;evaluation;tool-use

datasets and benchmarks

3;5;5;8

4;4;5;4

2;2;3;3

2;3;2;4

3;2;3;4

5.25

4.25

2.5

2.75

3

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

xriJVaTh4C

Gaussian Loss Smoothing Enables Certified Training with Tight Convex Relaxations

main

Active

Certified Robustness;Adversarial Robustness;Certified Training;Convex Relaxation;Neural Network Verification

alignment, fairness, safety, privacy, and societal considerations

1;3;6

4;3;4

2;2;3

1;1;3

1;3;3

3.333333

3.666667

2.333333

1.666667

2.333333

0.114708

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xrtM8r0zdU

Sparse Gradient Compression for Fine-Tuning Large Language Models

main

Active

Machine Learning;Large Language Models;Parameter efficient fine-tuning

foundation or frontier models, including LLMs

3;5;5;5;5

5;3;3;4;5

2;3;2;2;3

2;2;2;2;2

3;3;3;2;3

4.6

4

2.4

2

2.8

-0.559017

[ { "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":...

xsELpEPn4A

JudgeLM: Fine-tuned Large Language Models are Scalable Judges

main

Active

LLM Judging

alignment, fairness, safety, privacy, and societal considerations

6;6;8;8

4;3;4;4

3;3;3;4

3;3;2;3

3;3;3;4

7

3.75

3.25

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":...

xsmlrhoQzC

Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty

main

Active

Interpretable belief state;uncertainty estimation;information gathering;intelligent agents;question-asking under uncertainty

interpretability and explainable AI

3;5;6;6

3;4;4;3

2;3;3;3

2;2;3;3

5

3.5

2.75

2.5

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

xsx3Fpo3UD

Advantage-Guided Distillation for Preference Alignment in Small Language Models

main

Active

Preference Alignment; Large language model; Knowledge Distillation; Advantage Function

foundation or frontier models, including LLMs

6;6;8;8

3;3;3;4

3;3;3;3

2;3;3;3

7

3.25

3

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":...

xt3mCoDks7

Unlocking the Power of Gradient Guidance for Structure-Based Molecule Optimization

main

Active

molecule optimization;structure-based drug design;Bayesian flow network

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

3;3;5;6

4;4;2;2

1;2;2;3

1;2;2;2

2;2;2;2

4.25

3

2

1.75

2

-0.96225

[ { "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":...

xtTut5lisc

Iterative Feature Space Optimization through Incremental Adaptive Evaluation

main

Active

Automated Feature Optimization;Incremental Learning;Feature Space Evaluator

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

3;5;5

3;3;4

2;3;2

2;2;2

1;2;3

4.333333

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":...

xtlMtbVfWu

EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models

main

Active

Distributed Training;Large Language Models;Local SGD;Training Acceleration

infrastructure, software libraries, hardware, systems, etc.

3;5;5

4;5;4

2;3;3

2;2;2

2;2;3

4.333333

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

xtp6QPnwLu

Imit-Diff: Semantics Guided Diffusion Transformer with Dual Resolution Fusion for Imitation Learning

main

Active

Imitation learning;Diffusion Policy;Dual Resolution;Semantics Injection

applications to robotics, autonomy, planning

3;3;5;5

4;5;3;3

2;2;3;3

2;2;2;2

3;2;3;3

4

3.75

2.5

2

2.75

-0.904534

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xtzqU9FgSi

Is self-supervision enough for training sentence embeddings?

main

Active

self-supervised learning;language models;contrastive learning;transformers;natural language processing

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

3;3;5

4;4;3

2;2;2

4;2;2

3.666667

2

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":...

xuQSp75HmP

PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions

main

Active

Diffusion Model;Image Generation;Image-to-Image

generative models

5;5;6;6

4;4;4;3

3;3;3;3

2;2;2;2

3;3;3;3

5.5

3.75

3

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

xvUVk9T3kZ

Multi Task Inverse Reinforcement Learning for Common Sense Reward

main

Active

multi task learning;reinforcement learning

reinforcement learning

1;1;5;5

4;3;4;4

1;1;2;2

2;1;2;2

3;3;3;1

3

3.75

1.5

1.75

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

xvhV3LvYTc

InstantSplamp: Fast and Generalizable Stenography Framework for Generative Gaussian Splatting

main

Active

Gaussian Splatting;3D Generation;IP Verfication

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

3;5;5;8

5;3;4;5

2;3;3;3

2;2;2;3

3;1;2;3

5.25

4.25

2.75

2.25

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":...

xvsNb5y9CN

Sample-Imagined Generator: Efficient Virtual Sample Generation Method for Off-policy Reinforcement Learning with Sparse Rewards

main

Active

Off-policy Reinforcement Learning;Sparse Reward Reinforcement Learning;Sample Efficiency

reinforcement learning

3;3;3;3

4;4;3;4

1;2;2;2

2;1;2;2

3

3.75

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":...

xw4jtToUrf

Investigating Online RL in World Models

main

Active

World models;Domain Randomization;Offline RL

reinforcement learning

1;3;3;3;5

3;4;3;4;4

2;2;2;2;3

1;1;3;1;3

3

3.6

2.2

1.8

0.645497

[ { "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":...

xwcCFxIEEL

111

main

Withdraw

11

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

Shilin Yan

~Shilin_Yan1

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...

xwcCFxIEEL

111

main

Withdraw

11

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

Shilin Yan

~Shilin_Yan1

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...

xwcCFxIEEL

111

main

Withdraw

11

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

Shilin Yan

~Shilin_Yan1

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...

xxSK3ZNAhh

HeurAgenix: A Multi-Agent LLM-Based Paradigm for Adaptive Heuristic Evolution and Selection in Combinatorial Optimization

main

Active

Combinatorial Optimization; Heuristic Evolution; Heuristic Selection; Large Language Models

optimization

3;3;3;5;5

4;4;3;4;5

2;2;2;3;3

2;2;3;3;2

2;2;2;2;2

3.8

4

2.4

2

0.645497

[ { "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":...

xxzukMsYs9

3D Object Manipulation in a Single Image Using Generative Models

main

Active

3d object manipulation;diffusion models;image editing;image animation

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

3;5;6;8

4;4;3;4

2;3;3;3

1;3;2;3

3;3;4;3

5.5

3.75

2.75

2.25

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":...

xy6B5Fh2v7

Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models

main

Active

Retrieval Augmented Generation;Knowledge Conflicts

foundation or frontier models, including LLMs

5;5;5;6

3;4;4;4

3;2;3;3

2;2;2;3

2;3;2;3

5.25

3.75

2.75

2.25

2.5

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":...

xy9yv5siYQ

Learning Dynamic 3D Gaussians from Monocular Videos without Camera Poses

main

Active

Dynamic reconstruction;camera pose estimation

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

3;5;5;8

4;4;5;4

2;2;3;4

2;2;3;3

2;1;3;4

5.25

4.25

2.75

2.5

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

xybTwSsdBP

OptBatch: Optimizing Instruction Tuning with Data Selection through Batch Stratified Sampling

main

Withdraw

data selection;coreset;gradients;instruction tuning;large language model

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

run zou;Yifan Ding;Siyu Liu;Jianhang Ding;wenwu;Hao Chen;Beibei Chen;yun lou

~run_zou1;~Yifan_Ding6;~Siyu_Liu7;~Jianhang_Ding1;~wenwu1;~Hao_Chen79;~Beibei_Chen1;~yun_lou2

3;3;5;6

4;4;3;4

2;3;2;4

2;2;2;3

2;2;2;1

4.25

3.75

2.75

2.25

1.75

-0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "Dear Editor,\n\tI would like to express my sincere gratitude to the hardworking staff of you...

xyfb9HHvMe

DSPO: Direct Score Preference Optimization for Diffusion Model Alignment

main

Active

Text-to-image generation

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

5;5

5;3

3;3

2;3

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

xyysYa4YvF

Interpretable Boundary-based Watermark Up to the condition of Lov\'asz Local Lemma

main

Active

Watermark;Model extraction attacks;Intellectual property protection

alignment, fairness, safety, privacy, and societal considerations

1;5;6

5;5;3

2;4;3

1;3;3

2;3;4

4

4.333333

3

2.333333

3

-0.654654

[ { "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":...

xz3dmxfFva

Video Representation Learning Without Natural Videos

main

Active

video representation learning;learning from synthetic data

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

1;5;5

4;4;4

1;3;3

2;2;2

2;3;3

3.666667

4

2.333333

2

2.666667

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...

xzKFnsJIXL

Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model

main

Active

Differential Privacy;Privacy Auditing;Machine Learning

alignment, fairness, safety, privacy, and societal considerations

5;5;6;8

3;2;3;4

2;3;4;3

2;3;3;3

3;3;4;3

6

3

2.75

3.25

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

xzSUdw6s76

PALMBENCH: A COMPREHENSIVE BENCHMARK OF COMPRESSED LARGE LANGUAGE MODELS ON MOBILE PLATFORMS

main

Active

Mobile Platforms;Large Language Models;Quantization;Benchmark

datasets and benchmarks

5;5;5;6;8

3;4;5;4;4

2;3;2;3;4

2;2;2;2;3

3;3;3;3;4

5.8

4

2.8

2.2

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

y10AP0BkID

Towards Realistic Example-based Modeling via 3D Gaussian Stitching

main

Withdraw

Gaussian splatting;Composition;Example-based Modeling

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

Xinyu Gao;Ziyi Yang;Bingchen Gong;Xiaoguang Han;Sipeng Yang;Xiaogang Jin

~Xinyu_Gao1;~Ziyi_Yang4;~Bingchen_Gong1;~Xiaoguang_Han2;~Sipeng_Yang1;~Xiaogang_Jin1

3;3;5;6

4;2;4;3

3;3;3;3

2;2;2;3

2;2;2;4

4.25

3.25

3

2.25

2.5

0.174078

[ { "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...

y15LAM4u0A

EmbodiedCity: A Benchmark Platform for Embodied Agent in Real-world City Environment

main

Active

Embodied intelligence;real-world city environment;large language model agent;benchmark

datasets and benchmarks

3;3;3;6

4;5;4;3

3;2;2;3

1;2;2;2

2;3;2;3

3.75

4

2.5

1.75

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":...

y1UHa9sl2w

OntoFAR: Hierarchical Multi-Ontology Fusion Better Augments EHR Representation

main

Active

Health Informatics;EHR;Diagnosis Prediction;Healthcare Representation

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

3;5;5;5;5

3;4;4;2;5

3;3;3;3;3

2;3;2;3;2

4.6

3.6

3

2.4

0.294174

[ { "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":...

y1iU5czYpE

Auxiliary-Loss-Free Load Balancing Strategy for Mixture-of-Experts

main

Active

mixture of experts;load balancing;auxiliary-loss-free

foundation or frontier models, including LLMs

3;3;3;5

4;4;4;2

1;2;2;3

1;2;2;2

2;1;2;3

3.5

2

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":...

y2ch7iQSJu

Budget-constrained Active Learning to De-censor Survival Data

main

Active

Active Learning;Survival Analysis;Budgeted Constraints;Bayesian Model;Mutual Information;De-censoring Data

learning theory

1;3;3;8

4;4;4;2

2;1;2;4

2;2;2;4

1;2;2;3

3.75

3.5

2.25

2.5

2

-0.948847

[ { "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":...

y3CdSwREZl

MINER: Mining the Underlying Pattern of Modality-Specific Neurons in Multimodal Large Language Models

main

Active

MLLMs;neuron analysis;interpretability

foundation or frontier models, including LLMs

3;5;5;5;6

4;3;4;3;3

3;3;2;3;3

2;3;3;2;3

1;3;3;2;3

4.8

3.4

2.8

2.6

2.4

-0.666667

[ { "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":...

y3jJmrKWQ4

Judging the Judges: A Systematic Investigation of Position Bias in Pairwise Comparative Assessments by LLMs

main

Active

LLM-as-a-Judge;LLM evaluators;position bias;length bias;verbosity bias;pairwise comparison;repetition stability;position consistency;preference fairness

alignment, fairness, safety, privacy, and societal considerations

3;3;5;5

4;4;2;4

3;2;2;3

2;1;2;2

3;2;3;3

4

3.5

2.5

1.75

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":...

y3zswp3gek

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models

main

Active

knowledge distillation;safety guard

foundation or frontier models, including LLMs

5;6;6;8

2;4;4;4

3;4;4;4

2;3;3;3

4;4;3;4

6.25

3.5

3.75

2.75

3.75

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":...

y4DtzADzd1

Boosting Latent Diffusion with Perceptual Objectives

main

Active

diffusion;flows;latent diffusion;LDM;latent generative models;T2I;image generation;generative models.

generative models

3;5;5;6

4;3;4;4

2;3;3;3

1;2;2;3

2;3;3;3

4.75

3.75

2.75

2

2.75

-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":...

y4F2YZxN9T

Temporal Test-Time Adaptation with State-Space Models

main

Active

test-time adaptation;state-space models;probabilistic modelling;dynamical systems

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

3;3;5;6

4;4;4;3

3;1;3;3

2;2;2;3

3;2;3;3

4.25

3.75

2.5

2.25

2.75

-0.777778

[ { "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":...