Most Cited ICML "strategic agent behavior" Papers
5,975 papers found • Page 4 of 30
Conference
Position: Measure Dataset Diversity, Don't Just Claim It
Dora Zhao, Jerone Andrews, Orestis Papakyriakopoulos et al.
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds
Ben Chugg, Hongjian Wang, Aaditya Ramdas
Automated Red Teaming with GOAT: the Generative Offensive Agent Tester
Maya Pavlova, Erik Brinkman, Krithika Iyer et al.
Light and Optimal Schrödinger Bridge Matching
Nikita Gushchin, Sergei Kholkin, Evgeny Burnaev 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.
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
Han Fang, Zhihao Song, Paul Weng et al.
Towards Efficient Exact Optimization of Language Model Alignment
Haozhe Ji, Cheng Lu, Yilin Niu et al.
Case-Based or Rule-Based: How Do Transformers Do the Math?
Yi Hu, Xiaojuan Tang, Haotong Yang et al.
GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing
Akashah Shabbir, Ilmuz Zaman Mohammed Zumri, Mohammed Bennamoun et al.
Understanding Chain-of-Thought in LLMs through Information Theory
Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu
Q-value Regularized Transformer for Offline Reinforcement Learning
Shengchao Hu, Ziqing Fan, Chaoqin Huang et al.
Conformal Prediction Sets Improve Human Decision Making
Jesse Cresswell, yi sui, Bhargava Kumar et al.
Active Statistical Inference
Tijana Zrnic, Emmanuel J Candes
FourierMamba: Fourier Learning Integration with State Space Models for Image Deraining
Dong Li, Yidi Liu, Xueyang Fu et al.
Class-Imbalanced Graph Learning without Class Rebalancing
Zhining Liu, Ruizhong Qiu, Zhichen Zeng et al.
Representation Surgery: Theory and Practice of Affine Steering
Shashwat Singh, Shauli Ravfogel, Jonathan Herzig et al.
Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification
Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi
Unifying Image Processing as Visual Prompting Question Answering
Yihao Liu, Xiangyu Chen, Xianzheng Ma et al.
C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models
Mintong Kang, Nezihe Merve Gürel, Ning Yu et al.
Overtrained Language Models Are Harder to Fine-Tune
Jacob Mitchell Springer, Sachin Goyal, Kaiyue Wen et al.
Disentangled 3D Scene Generation with Layout Learning
Dave Epstein, Ben Poole, Ben Mildenhall et al.
Graph-enhanced Large Language Models in Asynchronous Plan Reasoning
Fangru Lin, Emanuele La Malfa, Valentin Hofmann et al.
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
Guoxuan Chen, Han Shi, jiawei li et al.
Steer LLM Latents for Hallucination Detection
Seongheon Park, Xuefeng Du, Min-Hsuan Yeh et al.
Efficient Online Reinforcement Learning for Diffusion Policy
Haitong Ma, Tianyi Chen, Kai Wang et al.
Emergent Representations of Program Semantics in Language Models Trained on Programs
Charles Jin, Martin Rinard
UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models
Xin Xu, Qiyun Xu, Tong Xiao et al.
A Statistical Theory of Regularization-Based Continual Learning
Xuyang Zhao, Huiyuan Wang, Weiran Huang et al.
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
Shengjie Wang, Shaohuai Liu, Weirui Ye et al.
Distillation Scaling Laws
Dan Busbridge, Amitis Shidani, Floris Weers et al.
How to set AdamW's weight decay as you scale model and dataset size
Xi Wang, Laurence Aitchison
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
Shashank Agnihotri, Steffen Jung, Margret Keuper
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models
Mingjia Huo, Sai Ashish Somayajula, Youwei Liang et al.
See More Details: Efficient Image Super-Resolution by Experts Mining
Eduard Zamfir, Zongwei Wu, Nancy Mehta et al.
TimeX++: Learning Time-Series Explanations with Information Bottleneck
Zichuan Liu, Tianchun Wang, Jimeng Shi et al.
Automated Statistical Model Discovery with Language Models
Michael Li, Emily Fox, Noah Goodman
Language Models as Semantic Indexers
Bowen Jin, Hansi Zeng, Guoyin Wang et al.
Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing
Zhuoran Zhang, Yongxiang Li, Zijian Kan et al.
LLark: A Multimodal Instruction-Following Language Model for Music
Josh Gardner, Simon Durand, Daniel Stoller et al.
KABB: Knowledge-Aware Bayesian Bandits for Dynamic Expert Coordination in Multi-Agent Systems
Jusheng Zhang, Zimeng Huang, Yijia Fan et al.
Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling
Hongzhi Huang, Defa Zhu, Banggu Wu et al.
Equivariant Deep Weight Space Alignment
Aviv Navon, Aviv Shamsian, Ethan Fetaya et al.
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
Shanglun Feng, Florian Tramer
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
Han Shen, Zhuoran Yang, Tianyi Chen
Revisiting the Power of Prompt for Visual Tuning
Yuzhu Wang, Lechao Cheng, Chaowei Fang et al.
GeoReasoner: Geo-localization with Reasoning in Street Views using a Large Vision-Language Model
Ling Li, Yu Ye, Bingchuan Jiang et al.
Graph Positional and Structural Encoder
Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné et al.
How Smooth Is Attention?
Valérie Castin, Pierre Ablin, Gabriel Peyré
Hybrid Inverse Reinforcement Learning
Juntao Ren, Gokul Swamy, Steven Wu et al.
Do Efficient Transformers Really Save Computation?
Kai Yang, Jan Ackermann, Zhenyu He et al.
Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks
Hojoon Lee, Hyeonseo Cho, Hyunseung Kim et al.
AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang et al.
Towards Scalable and Versatile Weight Space Learning
Konstantin Schürholt, Michael Mahoney, Damian Borth
Diving into Self-Evolving Training for Multimodal Reasoning
Wei Liu, Junlong Li, Xiwen Zhang et al.
BAGEL: Bootstrapping Agents by Guiding Exploration with Language
Shikhar Murty, Christopher Manning, Peter Shaw et al.
Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models
Samira Abnar, Harshay Shah, Dan Busbridge et al.
Selecting Large Language Model to Fine-tune via Rectified Scaling Law
Haowei Lin, Baizhou Huang, Haotian Ye et al.
Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models
Zehan Wang, Ziang Zhang, Tianyu Pang et al.
Training Dynamics of In-Context Learning in Linear Attention
Yedi Zhang, Aaditya Singh, Peter Latham et al.
Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale
Fan Zhou, Zengzhi Wang, Qian Liu et al.
MARS: Unleashing the Power of Variance Reduction for Training Large Models
Huizhuo Yuan, Yifeng Liu, Shuang Wu et al.
TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
Yichuan Mo, Hui Huang, Mingjie Li et al.
RUN: Reversible Unfolding Network for Concealed Object Segmentation
Chunming He, Rihan Zhang, Fengyang Xiao et al.
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
Anian Ruoss, Fabio Pardo, Harris Chan et al.
Learning to Scale Logits for Temperature-Conditional GFlowNets
Minsu Kim, Joohwan Ko, Taeyoung Yun et al.
VisionGraph: Leveraging Large Multimodal Models for Graph Theory Problems in Visual Context
yunxin li, Baotian Hu, Haoyuan Shi et al.
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
Xavi Suau, Pieter Delobelle, Katherine Metcalf et al.
Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads
Siqi Kou, Jiachun Jin, Zhihong Liu et al.
Learning to Intervene on Concept Bottlenecks
David Steinmann, Wolfgang Stammer, Felix Friedrich et al.
Harmonizing Generalization and Personalization in Federated Prompt Learning
Tianyu Cui, Hongxia Li, Jingya Wang et al.
Scalable Equilibrium Sampling with Sequential Boltzmann Generators
Charlie Tan, Joey Bose, Chen Lin et al.
LangCell: Language-Cell Pre-training for Cell Identity Understanding
Suyuan Zhao, Jiahuan Zhang, Yushuai Wu et al.
SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms
Xingrun Xing, Zheng Zhang, Ziyi Ni et al.
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N
Tianyu Zhang, Andrew Williams, Phillip Wozny et al.
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Ryan Liu, Theodore R Sumers, Ishita Dasgupta et al.
Subspace Optimization for Large Language Models with Convergence Guarantees
Yutong He, Pengrui Li, Yipeng Hu et al.
Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks
Linyuan Gong, Sida Wang, Mostafa Elhoushi et al.
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio et al.
MedRAX: Medical Reasoning Agent for Chest X-ray
Adibvafa Fallahpour, Jun Ma, Alif Munim 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.
MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
Justin Chih-Yao Chen, Swarnadeep Saha, Elias Stengel-Eskin et al.
Make-A-Shape: a Ten-Million-scale 3D Shape Model
Ka-Hei Hui, Aditya Sanghi, Arianna Rampini et al.
APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
Bowen Zhao, Hannaneh Hajishirzi, Qingqing Cao
LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models
Parshin Shojaee, Ngoc Hieu Nguyen, Kazem Meidani et al.
Generalized Interpolating Discrete Diffusion
Dimitri von Rütte, Janis Fluri, Yuhui Ding et al.
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
Chentao Cao, Zhun Zhong, Zhanke Zhou et al.
Star Attention: Efficient LLM Inference over Long Sequences
Shantanu Acharya, Fei Jia, Boris Ginsburg
Understanding Finetuning for Factual Knowledge Extraction
Gaurav Ghosal, Tatsunori Hashimoto, Aditi Raghunathan
Simulation of Graph Algorithms with Looped Transformers
Artur Back de Luca, Kimon Fountoulakis
CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay
Natasha Butt, Blazej Manczak, Auke Wiggers et al.
Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations
Yongshuo Zong, Tingyang Yu, Ruchika Chavhan et al.
Structured Chemistry Reasoning with Large Language Models
Siru Ouyang, Zhuosheng Zhang, Bing Yan et al.
Graph Neural Networks Use Graphs When They Shouldn't
Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach et al.
Scaling Down Deep Learning with MNIST-1D
Sam Greydanus, Dmitry Kobak
TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
Yifan Hu, Guibin Zhang, Peiyuan Liu et al.
Autoformulation of Mathematical Optimization Models Using LLMs
Nicolás Astorga, Tennison Liu, Yuanzhang Xiao et al.
Position: Explain to Question not to Justify
Przemyslaw Biecek, Wojciech Samek
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models
Mingrui Wu, Jiayi Ji, Oucheng Huang et al.
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
Hyeong Kyu Choi, Sharon Li
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik et al.
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation
Junjie Zhang, Chenjia Bai, Haoran He et al.
LQER: Low-Rank Quantization Error Reconstruction for LLMs
Cheng Zhang, Jianyi Cheng, George Constantinides et al.
Differentiable Weightless Neural Networks
Alan Bacellar, Zachary Susskind, Mauricio Breternitz Jr et al.
Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment
Harrish Thasarathan, Julian Forsyth, Thomas Fel et al.
EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration
Allen Nie, Yi Su, Bo Chang et al.
Predictive Dynamic Fusion
Bing Cao, Yinan Xia, Yi Ding et al.
Contrastive Localized Language-Image Pre-Training
Hong-You Chen, Zhengfeng Lai, Haotian Zhang et al.
Code as Reward: Empowering Reinforcement Learning with VLMs
David Venuto, Mohammad Sami Nur Islam, Martin Klissarov et al.
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
Yuwei Fu, Haichao Zhang, di wu et al.
MAS-GPT: Training LLMs to Build LLM-based Multi-Agent Systems
Rui Ye, shuo tang, Rui Ge et al.
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
Charlie Hou, Akshat Shrivastava, Hongyuan Zhan et al.
Image Clustering with External Guidance
Yunfan Li, Peng Hu, Dezhong Peng et al.
Thermometer: Towards Universal Calibration for Large Language Models
Maohao Shen, Subhro Das, Kristjan Greenewald et al.
GenMol: A Drug Discovery Generalist with Discrete Diffusion
Seul Lee, Karsten Kreis, Srimukh Veccham et al.
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model
Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu et al.
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
Maciej Wołczyk, Bartłomiej Cupiał, Mateusz Ostaszewski et al.
Asymptotics of feature learning in two-layer networks after one gradient-step
Hugo Cui, Luca Pesce, Yatin Dandi et al.
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning
Xiangzhe Kong, Wenbing Huang, Yang Liu
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics
Noga Mudrik, Yenho Chen, Eva Yezerets et al.
Out-of-Domain Generalization in Dynamical Systems Reconstruction
Niclas Göring, Florian Hess, Manuel Brenner et al.
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models
Jinhao Li, Haopeng Li, Sarah Erfani et al.
Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent
Yongxian Wei, Anke Tang, Li Shen et al.
T-Cal: An Optimal Test for the Calibration of Predictive Models
Donghwan Lee, Xinmeng Huang, Hamed Hassani et al.
PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching
Haitao Lin, Odin Zhang, Huifeng Zhao et al.
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen et al.
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong et al.
Transforming and Combining Rewards for Aligning Large Language Models
Zihao Wang, Chirag Nagpal, Jonathan Berant et al.
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai et al.
EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities
Talor Abramovich, Meet Udeshi, Minghao Shao et al.
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu
How Do Large Language Monkeys Get Their Power (Laws)?
Rylan Schaeffer, Joshua Kazdan, John Hughes et al.
Regression with Multi-Expert Deferral
Anqi Mao, Mehryar Mohri, Yutao Zhong
Emergence of In-Context Reinforcement Learning from Noise Distillation
Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin et al.
Outlier-robust Kalman Filtering through Generalised Bayes
Gerardo Duran-Martin, Matias Altamirano, Alex Shestopaloff et al.
Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning
Jinlong Pang, Na Di, Zhaowei Zhu et al.
ResearchTown: Simulator of Human Research Community
Haofei Yu, Zhaochen Hong, Zirui Cheng et al.
Learning Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter et al.
Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling Evaluators
Yilun Zhou, Austin Xu, PeiFeng Wang et al.
Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation
Xinyi Wang, Alfonso Amayuelas, Kexun Zhang et al.
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu, Chenjia Bai, Jing-Wen Yang et al.
Robust Multi-Task Learning with Excess Risks
Yifei He, Shiji Zhou, Guojun Zhang et al.
Critical windows: non-asymptotic theory for feature emergence in diffusion models
Marvin Li, Sitan Chen
Fewer Truncations Improve Language Modeling
Hantian Ding, Zijian Wang, Giovanni Paolini et al.
Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?
Fan Yao, Chuanhao Li, Denis Nekipelov et al.
Self-Consistency Preference Optimization
Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang et al.
OrcaLoca: An LLM Agent Framework for Software Issue Localization
Zhongming Yu, Hejia Zhang, Yujie Zhao et al.
Fast Exact Unlearning for In-Context Learning Data for LLMs
Andrei Muresanu, Anvith Thudi, Michael Zhang et al.
Decomposing and Editing Predictions by Modeling Model Computation
Harshay Shah, Andrew Ilyas, Aleksander Madry
Accelerating Parallel Sampling of Diffusion Models
Zhiwei Tang, Jiasheng Tang, Hao Luo et al.
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering
Yongxin Guo, Xiaoying Tang, Tao Lin
In-Context Reinforcement Learning for Variable Action Spaces
Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov et al.
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan et al.
A Unified Approach to Routing and Cascading for LLMs
Jasper Dekoninck, Maximilian Baader, Martin Vechev
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener et al.
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
Can Yaras, Peng Wang, Laura Balzano et al.
Towards Certified Unlearning for Deep Neural Networks
Binchi Zhang, Yushun Dong, Tianhao Wang et al.
Stochastic Localization via Iterative Posterior Sampling
Louis Grenioux, Maxence Noble, Marylou Gabrié et al.
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova et al.
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
Learning and Forgetting Unsafe Examples in Large Language Models
Jiachen Zhao, Zhun Deng, David Madras et al.
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Kaiwen Xue, Yuhao Zhou, Shen Nie et al.
The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models Via Visual Information Steering
Zhuowei Li, Haizhou Shi, Yunhe Gao et al.
Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization
Zishun Yu, Tengyu Xu, Di Jin et al.
StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization
Shida Wang, Qianxiao Li
An Empirical Study of Realized GNN Expressiveness
Yanbo Wang, Muhan Zhang
The Entropy Enigma: Success and Failure of Entropy Minimization
Ori Press, Ravid Shwartz-Ziv, Yann LeCun et al.
ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
Alec Helbling, Tuna Han Salih Meral, Benjamin Hoover et al.
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
Learning Iterative Reasoning through Energy Diffusion
Yilun Du, Jiayuan Mao, Josh Tenenbaum
Reinformer: Max-Return Sequence Modeling for Offline RL
Zifeng Zhuang, Dengyun Peng, Jinxin Liu et al.
Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function
Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan
Pairwise Alignment Improves Graph Domain Adaptation
Shikun Liu, Deyu Zou, Han Zhao et al.
PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop
Chenyu Li, Oscar Michel, Xichen Pan et al.
Core Knowledge Deficits in Multi-Modal Language Models
Yijiang Li, Qingying Gao, Tianwei Zhao et al.
Towards a Mechanistic Explanation of Diffusion Model Generalization
Matthew Niedoba, Berend Zwartsenberg, Kevin Murphy et al.
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples
chengqian gao, Haonan Li, Liu Liu et al.
On Discrete Prompt Optimization for Diffusion Models
Ruochen Wang, Ting Liu, Cho-Jui Hsieh et al.
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
Changze Lv, Yansen Wang, Dongqi Han et al.
On Mechanistic Knowledge Localization in Text-to-Image Generative Models
Samyadeep Basu, Keivan Rezaei, Priyatham Kattakinda et al.
Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging
Shiqi Chen, Jinghan Zhang, Tongyao Zhu et al.
Position: Why We Must Rethink Empirical Research in Machine Learning
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger et al.
Designing Decision Support Systems using Counterfactual Prediction Sets
Eleni Straitouri, Manuel Gomez-Rodriguez
InferCept: Efficient Intercept Support for Augmented Large Language Model Inference
Reyna Abhyankar, Zijian He, Vikranth Srivatsa et al.
Matrix Information Theory for Self-Supervised Learning
Yifan Zhang, Zhiquan Tan, Jingqin Yang et al.
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?
Andreas Opedal, Alessandro Stolfo, Haruki Shirakami et al.
Self-Correcting Self-Consuming Loops for Generative Model Training
Nate Gillman, Michael Freeman, Daksh Aggarwal et al.
Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases
Ziyi Zhang, Sen Zhang, Yibing Zhan et al.
Comparing Graph Transformers via Positional Encodings
Mitchell Black, Zhengchao Wan, Gal Mishne et al.
Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search
Boyan Li, Jiayi Zhang, Ju Fan et al.
Clifford-Steerable Convolutional Neural Networks
Maksim Zhdanov, David Ruhe, Maurice Weiler et al.
Chain-of-Thought Predictive Control
Zhiwei Jia, Vineet Thumuluri, Fangchen Liu et al.
Position: Key Claims in LLM Research Have a Long Tail of Footnotes
Anna Rogers, Sasha Luccioni
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
Ignat Georgiev, Krishnan Srinivasan, Jie Xu et al.
Stable Differentiable Causal Discovery
Achille Nazaret, Justin Hong, Elham Azizi et al.
LLM-Empowered State Representation for Reinforcement Learning
Boyuan Wang, Yun Qu, Yuhang Jiang et al.
Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention
Zhen Qin, Weigao Sun, Dong Li et al.
Discrepancy Minimization in Input-Sparsity Time
Yichuan Deng, Xiaoyu Li, Zhao Song et al.
Teaching Language Models to Critique via Reinforcement Learning
Zhihui Xie, Jie chen, Liyu Chen et al.
ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning
Hongyin Zhang, Zifeng Zhuang, Han Zhao et al.
On the Implicit Bias of Adam
Matias Cattaneo, Jason Klusowski, Boris Shigida