Most Cited ICML Poster "vision-based reinforcement learning" Papers
5,975 papers found • Page 1 of 30
Conference
WorldSimBench: Towards Video Generation Models as World Simulators
Yiran Qin, Zhelun Shi, Jiwen Yu et al.
From Crowdsourced Data to High-quality Benchmarks: Arena-Hard and Benchbuilder Pipeline
Tianle Li, Wei-Lin Chiang, Evan Frick et al.
SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference
Yuan Zhang, Chun-Kai Fan, Junpeng Ma et al.
Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction
Yiheng Xu, Zekun Wang, Junli Wang et al.
Training Software Engineering Agents and Verifiers with SWE-Gym
Jiayi Pan, Xingyao Wang, Graham Neubig et al.
AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
Anselm Paulus, Arman Zharmagambetov, Chuan Guo et al.
Layer by Layer: Uncovering Hidden Representations in Language Models
Oscar Skean, Md Rifat Arefin, Dan Zhao et al.
Imagine While Reasoning in Space: Multimodal Visualization-of-Thought
Chengzu Li, Wenshan Wu, Huanyu Zhang et al.
Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs
Jan Betley, Daniel Tan, Niels Warncke et al.
Taming Rectified Flow for Inversion and Editing
Jiangshan Wang, Junfu Pu, Zhongang Qi et al.
A General Framework for Inference-time Scaling and Steering of Diffusion Models
Raghav Singhal, Zachary Horvitz, Ryan Teehan et al.
Freeze-Omni: A Smart and Low Latency Speech-to-speech Dialogue Model with Frozen LLM
Xiong Wang, Yangze Li, Chaoyou Fu et al.
AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
Zhengxuan Wu, Aryaman Arora, Atticus Geiger et al.
MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding
Yuxin Zuo, Shang Qu, Yifei Li et al.
OR-Bench: An Over-Refusal Benchmark for Large Language Models
Jiaxing Cui, Wei-Lin Chiang, Ion Stoica et al.
Theoretical guarantees on the best-of-n alignment policy
Ahmad Beirami, Alekh Agarwal, Jonathan Berant et al.
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
Dongzhi Jiang, Renrui Zhang, Ziyu Guo et al.
Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction
Xiang Fu, Brandon Wood, Luis Barroso-Luque et al.
Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation
Fanqing Meng, Jiaqi Liao, Xinyu Tan et al.
Scaling Test-Time Compute Without Verification or RL is Suboptimal
Amrith Setlur, Nived Rajaraman, Sergey Levine et al.
Cradle: Empowering Foundation Agents towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu et al.
History-Guided Video Diffusion
Kiwhan Song, Boyuan Chen, Max Simchowitz et al.
GuardAgent: Safeguard LLM Agents via Knowledge-Enabled Reasoning
Zhen Xiang, Linzhi Zheng, Yanjie Li et al.
SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering?
Samuel Miserendino, Michele Wang, Tejal Patwardhan et al.
LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models
Marwa Abdulhai, Isadora White, Charlie Snell et al.
HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation
Tianwei Lin, Wenqiao Zhang, Sijing Li et al.
Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
Micah Goldblum, Marc Finzi, Keefer Rowan et al.
ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference
Hanshi Sun, Li-Wen Chang, Wenlei Bao et al.
RE-Bench: Evaluating Frontier AI R&D Capabilities of Language Model Agents against Human Experts
Hjalmar Wijk, Tao Lin, Joel Becker et al.
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
Patara Trirat, Wonyong Jeong, Sung Ju Hwang
Sundial: A Family of Highly Capable Time Series Foundation Models
Yong Liu, Guo Qin, Zhiyuan Shi et al.
Inductive Moment Matching
Linqi (Alex) Zhou, Stefano Ermon, Jiaming Song
Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
Swarnadeep Saha, Xian Li, Marjan Ghazvininejad et al.
Flow Q-Learning
Seohong Park, Qiyang Li, Sergey Levine
NoLiMa: Long-Context Evaluation Beyond Literal Matching
Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt et al.
SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
Adam Karvonen, Can Rager, Johnny Lin et al.
VinePPO: Refining Credit Assignment in RL Training of LLMs
Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance et al.
Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning Attack
Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi et al.
Organize the Web: Constructing Domains Enhances Pre-Training Data Curation
Alexander Wettig, Kyle Lo, Sewon Min et al.
EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers
Daiheng Gao, Shilin Lu, Wenbo Zhou et al.
NETS: A Non-equilibrium Transport Sampler
Michael Albergo, Eric Vanden-Eijnden
Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning
Andy (DiJia) Su, Hanlin Zhu, Yingchen Xu et al.
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
Theodoros Kouzelis, Ioannis Kakogeorgiou, Spyros Gidaris et al.
ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
Xingyu Fu, Minqian Liu, Zhengyuan Yang et al.
FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
Roman Bachmann, Jesse Allardice, David Mizrahi et al.
Context is Key: A Benchmark for Forecasting with Essential Textual Information
Andrew Williams, Arjun Ashok, Étienne Marcotte et al.
The Surprising Effectiveness of Test-Time Training for Few-Shot Learning
Ekin Akyürek, Mehul Damani, Adam Zweiger et al.
An Architecture Search Framework for Inference-Time Techniques
Jon Saad-Falcon, Adrian Lafuente, Shlok Natarajan et al.
MoH: Multi-Head Attention as Mixture-of-Head Attention
Peng Jin, Bo Zhu, Li Yuan et al.
ShieldAgent: Shielding Agents via Verifiable Safety Policy Reasoning
Zhaorun Chen, Mintong Kang, Bo Li
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
Dongya Jia, Zhuo Chen, Jiawei Chen et al.
Robust Autonomy Emerges from Self-Play
Marco Cusumano-Towner, David Hafner, Alexander Hertzberg et al.
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian et al.
Improving the Diffusability of Autoencoders
Ivan Skorokhodov, Sharath Girish, Benran Hu et al.
Which Attention Heads Matter for In-Context Learning?
Kayo Yin, Jacob Steinhardt
Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?
Rylan Schaeffer, Hailey Schoelkopf, Brando Miranda et al.
The Diffusion Duality
Subham Sekhar Sahoo, Justin Deschenaux, Aaron Gokaslan et al.
On the Emergence of Position Bias in Transformers
Xinyi Wu, Yifei Wang, Stefanie Jegelka et al.
Time Weaver: A Conditional Time Series Generation Model
Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin et al.
PepTune: De Novo Generation of Therapeutic Peptides with Multi-Objective-Guided Discrete Diffusion
Sophia Tang, Yinuo Zhang, Pranam Chatterjee, PhD
Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries
HUAKUN LUO, Haixu Wu, Hang Zhou et al.
The dark side of the forces: assessing non-conservative force models for atomistic machine learning
Filippo Bigi, Marcel Langer, Michele Ceriotti
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
Siru Zhong, Weilin Ruan, Ming Jin et al.
FlatQuant: Flatness Matters for LLM Quantization
Yuxuan Sun, Ruikang Liu, Haoli Bai et al.
Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads
Siqi Kou, Jiachun Jin, Zhihong Liu et al.
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
Thomas Fel, Ekdeep Singh Lubana, Jacob Prince et al.
From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models
Etowah Adams, Liam Bai, Minji Lee et al.
Overtrained Language Models Are Harder to Fine-Tune
Jacob Mitchell Springer, Sachin Goyal, Kaiyue Wen et al.
RUN: Reversible Unfolding Network for Concealed Object Segmentation
Chunming He, Rihan Zhang, Fengyang Xiao et al.
Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models
Zehan Wang, Ziang Zhang, Tianyu Pang et al.
No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces
Daniel Marczak, Simone Magistri, Sebastian Cygert et al.
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
Anian Ruoss, Fabio Pardo, Harris Chan et al.
Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling
Hongzhi Huang, Defa Zhu, Banggu Wu et al.
DeFoG: Discrete Flow Matching for Graph Generation
Yiming Qin, Manuel Madeira, Dorina Thanou et al.
KABB: Knowledge-Aware Bayesian Bandits for Dynamic Expert Coordination in Multi-Agent Systems
Jusheng Zhang, Zimeng Huang, Yijia Fan et al.
ResearchTown: Simulator of Human Research Community
Haofei Yu, Zhaochen Hong, Zirui Cheng et al.
UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models
Xin Xu, Qiyun Xu, Tong Xiao et al.
Efficient Online Reinforcement Learning for Diffusion Policy
Haitong Ma, Tianyi Chen, Kai Wang et al.
Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment
Harrish Thasarathan, Julian Forsyth, Thomas Fel et al.
Teaching Language Models to Critique via Reinforcement Learning
Zhihui Xie, Jie chen, Liyu Chen et al.
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener et al.
Self-Consistency Preference Optimization
Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang et al.
Towards a Mechanistic Explanation of Diffusion Model Generalization
Matthew Niedoba, Berend Zwartsenberg, Kevin Murphy et al.
Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning
Jinlong Pang, Na Di, Zhaowei Zhu et al.
Mastering Board Games by External and Internal Planning with Language Models
John Schultz, Jakub Adamek, Matej Jusup et al.
Reinforced Lifelong Editing for Language Models
Zherui Li, Houcheng Jiang, Hao Chen et al.
TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems
Si-Yang Liu, Han-Jia Ye
SongGen: A Single Stage Auto-regressive Transformer for Text-to-Song Generation
Zihan Liu, Shuangrui Ding, Zhixiong Zhang et al.
P(all-atom) Is Unlocking New Path For Protein Design
Wei Qu, Jiawei Guan, Rui Ma et al.
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples
chengqian gao, Haonan Li, Liu Liu et al.
ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning
Hongyin Zhang, Zifeng Zhuang, Han Zhao et al.
Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation
Yunheng Li, Zhong-Yu Li, Quan-Sheng Zeng et al.
Is Noise Conditioning Necessary for Denoising Generative Models?
Qiao Sun, Zhicheng Jiang, Hanhong Zhao et al.
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Federico Errica, Henrik Christiansen, Viktor Zaverkin et al.
Pre-training Auto-regressive Robotic Models with 4D Representations
Dantong Niu, Yuvan Sharma, Haoru Xue et al.
CRANE: Reasoning with constrained LLM generation
Debangshu Banerjee, Tarun Suresh, Shubham Ugare et al.
Investigating Non-Transitivity in LLM-as-a-Judge
Yi Xu, Laura Ruis, Tim Rocktäschel et al.
Universal Length Generalization with Turing Programs
Kaiying Hou, David Brandfonbrener, Sham Kakade et al.
A Unified Approach to Routing and Cascading for LLMs
Jasper Dekoninck, Maximilian Baader, Martin Vechev
Reducing Tool Hallucination via Reliability Alignment
Hongshen Xu, Zichen Zhu, Lei Pan et al.
Delta Decompression for MoE-based LLMs Compression
Hao Gu, Wei Li, Lujun Li et al.
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs
Jongwoo Ko, Tianyi Chen, Sungnyun Kim et al.
Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache Sharing
Kaifeng Gao, Jiaxin Shi, Hanwang Zhang et al.
Monte Carlo Tree Diffusion for System 2 Planning
Jaesik Yoon, Hyeonseo Cho, Doojin Baek et al.
Idiosyncrasies in Large Language Models
Mingjie Sun, Yida Yin, Zhiqiu (Oscar) Xu et al.
On the Guidance of Flow Matching
Ruiqi Feng, Chenglei Yu, Wenhao Deng et al.
MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization
Kangyu Zhu, Peng Xia, Yun Li et al.
Reinforce LLM Reasoning through Multi-Agent Reflection
Yurun Yuan, Tengyang Xie
BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute
Dujian Ding, Ankur Mallick, Shaokun Zhang et al.
Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence
Shangbin Feng, Zifeng Wang, Yike Wang et al.
A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression
Victor Dheur, Matteo Fontana, Yorick Estievenart et al.
Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation
Sadegh Mahdavi, Muchen Li, Kaiwen Liu et al.
Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models
Yukang Yang, Declan Campbell, Kaixuan Huang et al.
Position: Editing Large Language Models Poses Serious Safety Risks
Paul Youssef, Zhixue Zhao, Daniel Braun et al.
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems
Maksim Zhdanov, Max Welling, Jan-Willem van de Meent
Wasserstein Flow Matching: Generative Modeling Over Families of Distributions
Doron Haviv, Aram-Alexandre Pooladian, Dana Pe'er et al.
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos
Chris Pedersen, Laure Zanna, Joan Bruna
Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach
Jiancong Xiao, Bojian Hou, Zhanliang Wang et al.
From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications
Ajay Jaiswal, Yifan Wang, Lu Yin et al.
Stochastic Deep Restoration Priors for Imaging Inverse Problems
Yuyang Hu, Albert Peng, Weijie Gan et al.
Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment
Shuo Wang, Bokui Wang, Zhixiang Shen et al.
DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra
Montgomery Bohde, Mrunali Manjrekar, Runzhong Wang et al.
Retrieval Augmented Time Series Forecasting
Sungwon Han, Seungeon Lee, MEEYOUNG CHA et al.
Can Transformers Learn Full Bayesian Inference in Context?
Arik Reuter, Tim G. J. Rudner, Vincent Fortuin et al.
KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference
Xing Li, Zeyu Xing, Yiming Li et al.
Optimizing Temperature for Language Models with Multi-Sample Inference
Weihua Du, Yiming Yang, Sean Welleck
Diffusion on Language Model Encodings for Protein Sequence Generation
Viacheslav Meshchaninov, Pavel Strashnov, Andrey Shevtsov et al.
SITCOM: Step-wise Triple-Consistent Diffusion Sampling For Inverse Problems
Ismail Alkhouri, Shijun Liang, Cheng-Han Huang et al.
ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
Yupeng Hou, Jianmo Ni, Zhankui He et al.
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch
Virginia Aglietti, Ira Ktena, Jessica Schrouff et al.
RelGNN: Composite Message Passing for Relational Deep Learning
Tianlang Chen, Charilaos Kanatsoulis, Jure Leskovec
DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation
Yunbei Zhang, Akshay Mehra, Shuaicheng Niu et al.
LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models
Lukas Helff, Felix Friedrich, Manuel Brack et al.
Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints
Sam Bowyer, Laurence Aitchison, Desi Ivanova
Optimal transport-based conformal prediction
Gauthier Thurin, Kimia Nadjahi, Claire Boyer
How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel Divergence
Hyeong Kyu Choi, Maxim Khanov, Hongxin Wei et al.
Contextual Bandits for Unbounded Context Distributions
Puning Zhao, Rongfei Fan, Shaowei Wang et al.
Temporal Query Network for Efficient Multivariate Time Series Forecasting
Shengsheng Lin, Haojun Chen, Haijie Wu et al.
PILAF: Optimal Human Preference Sampling for Reward Modeling
Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng et al.
Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction
Vaishnavh Nagarajan, Chen Wu, Charles Ding et al.
OWLS: Scaling Laws for Multilingual Speech Recognition and Translation Models
William Chen, Jinchuan Tian, Yifan Peng et al.
RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning
Yuanhuiyi Lyu, Xu Zheng, Lutao Jiang et al.
CROW: Eliminating Backdoors from Large Language Models via Internal Consistency Regularization
Nay Myat Min, Long H. Pham, Yige Li et al.
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
Gabriel Tseng, Anthony Fuller, Marlena Reil et al.
Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies
Yuefan Cao, Xiaoyu Li, Yingyu Liang et al.
Cost-efficient Collaboration between On-device and Cloud Language Models
Avanika Narayan, Dan Biderman, Sabri Eyuboglu et al.
How to Synthesize Text Data without Model Collapse?
Xuekai Zhu, Daixuan Cheng, Hengli Li et al.
CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models
David Dai, Peilin Chen, Malinda Lu et al.
Active Evaluation Acquisition for Efficient LLM Benchmarking
Yang Li, Jie Ma, Miguel Ballesteros et al.
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
Jan Ludziejewski, Maciej Pióro, Jakub Krajewski et al.
Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
Kaiwen Zheng, Yongxin Chen, Huayu Chen et al.
Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
Masatoshi Uehara, su, Yulai Zhao et al.
Accelerating Large Language Model Reasoning via Speculative Search
Zhihai Wang, Jie Wang, Jilai Pan et al.
Patch-wise Structural Loss for Time Series Forecasting
Dilfira Kudrat, Zongxia Xie, Yanru Sun et al.
Minimum-Norm Interpolation Under Covariate Shift
Neil Mallinar, Austin Zane, Spencer Frei et al.
Data-efficient Large Vision Models through Sequential Autoregression
Zhiwei Hao, Jianyuan Guo, Chengcheng Wang et al.
CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance
Yongchao Chen, Yilun Hao, Yueying Liu et al.
Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
Connor Schenck, Isaac Reid, Mithun Jacob et al.
Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong, Minglu Zhao, Dehong Xu et al.
LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
Prasanna Mayilvahanan, Thaddäus Wiedemer, Sayak Mallick et al.
Liger: Linearizing Large Language Models to Gated Recurrent Structures
Disen Lan, Weigao Sun, Jiaxi Hu et al.
HashAttention: Semantic Sparsity for Faster Inference
Aditya Desai, Shuo Yang, Alejandro Cuadron et al.
Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
Zihan Guan, Mengxuan Hu, Ronghang Zhu et al.
ProSec: Fortifying Code LLMs with Proactive Security Alignment
Xiangzhe Xu, Zian Su, Jinyao Guo et al.
Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad?
Antonia Wüst, Tim Woydt, Lukas Helff et al.
Adaptive Self-improvement LLM Agentic System for ML Library Development
Genghan Zhang, Weixin Liang, Olivia Hsu et al.
Scaling Inference-Efficient Language Models
Song Bian, Minghao Yan, Shivaram Venkataraman
Can Transformers Reason Logically? A Study in SAT Solving
Leyan Pan, Vijay Ganesh, Jacob Abernethy et al.
NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction
Qichao Wang, Ziqiao Meng, Wenqian Cui et al.
Unifying 2D and 3D Vision-Language Understanding
Ayush Jain, Alexander Swerdlow, Yuzhou Wang et al.
CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language Models
Qinsi Wang, Hancheng Ye, Ming-Yu Chung et al.
Reliable and Efficient Amortized Model-based Evaluation
Sang Truong, Yuheng Tu, Percy Liang et al.
Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Models
Ruiyu Wang, Yu Yuan, Shizhao Sun et al.
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
Thomas Schmied, Thomas Adler, Vihang Patil et al.
The Double-Ellipsoid Geometry of CLIP
Meir Yossef Levi, Guy Gilboa
DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers
Xuanlei Zhao, Shenggan Cheng, Chang Chen et al.
MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-text Decoding
Weikang Qiu, Zheng Huang, Haoyu Hu et al.
Visual Generation Without Guidance
Huayu Chen, Kai Jiang, Kaiwen Zheng et al.
Understanding Inter-Concept Relationships in Concept-Based Models
Naveen Raman, Mateo Espinosa Zarlenga, Mateja Jamnik
Constrain Alignment with Sparse Autoencoders
Qingyu Yin, Chak Tou Leong, Hongbo Zhang et al.
AlphaPO: Reward Shape Matters for LLM Alignment
Aman Gupta, Shao Tang, Qingquan Song et al.
On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
Wei Shen, Ruida Zhou, Jing Yang et al.
Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
Nadav Timor, Jonathan Mamou, Daniel Korat et al.
Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI
Julien Pourcel, Cédric Colas, Pierre-Yves Oudeyer
PENCIL: Long Thoughts with Short Memory
Chenxiao Yang, Nati Srebro, David McAllester et al.
Graph Generative Pre-trained Transformer
Xiaohui Chen, Yinkai Wang, JIAXING HE et al.
MIB: A Mechanistic Interpretability Benchmark
Aaron Mueller, Atticus Geiger, Sarah Wiegreffe et al.
ReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation
Angxiao Yue, Zichong Wang, Hongteng Xu
MUDDFormer: Breaking Residual Bottlenecks in Transformers via Multiway Dynamic Dense Connections
Da Xiao, Qingye Meng, Shengping Li et al.
Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors
Emile Pierret, Bruno Galerne
How Transformers Learn Structured Data: Insights From Hierarchical Filtering
Jerome Garnier-Brun, Marc Mezard, Emanuele Moscato et al.
Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignment
Yifan Zhang, Ge Zhang, Yue Wu et al.
Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
Shikai Qiu, Lechao Xiao, Andrew Wilson et al.
HybridGS: High-Efficiency Gaussian Splatting Data Compression using Dual-Channel Sparse Representation and Point Cloud Encoder
Qi Yang, Le Yang, Geert Van der Auwera et al.
PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations
Benjamin Holzschuh, Qiang Liu, Georg Kohl et al.
Objective drives the consistency of representational similarity across datasets
Laure Ciernik, Lorenz Linhardt, Marco Morik et al.
Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
Luca Masserano, Abdul Fatir Ansari, Boran Han et al.
Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?
Simon Park, Abhishek Panigrahi, Yun Cheng et al.
When Do LLMs Help With Node Classification? A Comprehensive Analysis
Xixi Wu, Yifei Shen, Fangzhou Ge et al.
Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence
Yuankai Luo, Lei Shi, Xiao-Ming Wu