Most Cited ICML "global weight shrinking" Papers
5,975 papers found • Page 8 of 30
Conference
NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction
Qichao Wang, Ziqiao Meng, Wenqian Cui et al.
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
Taming Knowledge Conflicts in Language Models
Gaotang Li, Yuzhong Chen, Hanghang Tong
Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detection
Peipeng Yu, Jianwei Fei, Hui Gao et al.
Conformalized Adaptive Forecasting of Heterogeneous Trajectories
Yanfei Zhou, Lars Lindemann, Matteo Sesia
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
KaShun SHUM, Yuzhen Huang, Hongjian Zou et al.
Conditioning Diffusions Using Malliavin Calculus
Jakiw Pidstrigach, Elizabeth Baker, Carles Domingo i Enrich et al.
MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance
Zhixuan Chen, Xing Hu, Dawei Yang et al.
A Universal Class of Sharpness-Aware Minimization Algorithms
Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri et al.
Text-to-LoRA: Instant Transformer Adaption
Rujikorn Charakorn, Edoardo Cetin, Yujin Tang et al.
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
Jeongwhan Choi, Sumin Parksumin, Hyowon Wi et al.
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios et al.
Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation
Juno Kim, Denny Wu, Jason Lee et al.
Minimum-Norm Interpolation Under Covariate Shift
Neil Mallinar, Austin Zane, Spencer Frei et al.
CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models
David Dai, Peilin Chen, Malinda Lu et al.
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
Weixi Song, Zuchao Li, Lefei Zhang et al.
CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD Editing
Yu Yuan, Shizhao Sun, Qi Liu et al.
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis
Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky et al.
Mixture of Experts Made Intrinsically Interpretable
Xingyi Yang, Constantin Venhoff, Ashkan Khakzar et al.
LightningDrag: Lightning Fast and Accurate Drag-based Image Editing Emerging from Videos
Yujun Shi, Jun Hao Liew, Hanshu Yan et al.
WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs
Lukas Thede, Karsten Roth, Matthias Bethge et al.
No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets
Corinna Coupette, Jeremy Wayland, Emily Simons et al.
Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning
Jin Hwa Lee, Stefano Mannelli, Andrew Saxe
S3O: A Dual-Phase Approach for Reconstructing Dynamic Shape and Skeleton of Articulated Objects from Single Monocular Video
Hao Zhang, Fang Li, Samyak Rawlekar 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.
Discounted Adaptive Online Learning: Towards Better Regularization
Zhiyu Zhang, David Bombara, Heng Yang
Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad?
Antonia Wüst, Tim Woydt, Lukas Helff et al.
Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment
Chenghao Fan, zhenyi lu, Sichen Liu et al.
Robustly Learning Single-Index Models via Alignment Sharpness
Nikos Zarifis, Puqian Wang, Ilias Diakonikolas et al.
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
Kevin Rojas, Yuchen Zhu, Sichen Zhu et al.
Exploiting Code Symmetries for Learning Program Semantics
Kexin Pei, Weichen Li, Qirui Jin et al.
Momentum Particle Maximum Likelihood
Jen Ning Lim, Juan Kuntz, Samuel Power et al.
Online Algorithms with Uncertainty-Quantified Predictions
Bo Sun, Jerry Huang, Nicolas Christianson et al.
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
Changdae Oh, zhen fang, Shawn Im et al.
Sparse and Structured Hopfield Networks
Saúl Santos, Vlad Niculae, Daniel McNamee et al.
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation
Jacob Si, Wendy Yusi Cheng, Michael Cooper et al.
The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training
Jinbo Wang, Mingze Wang, Zhanpeng Zhou et al.
Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Models
Ruiyu Wang, Yu Yuan, Shizhao Sun et al.
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
Lin Li, Yifei Wang, Chawin Sitawarin et al.
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
Shiwei Li, Wenchao Xu, Haozhao Wang et al.
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
Sudeep Salgia, Sattar Vakili, Qing Zhao
Speak Easy: Eliciting Harmful Jailbreaks from LLMs with Simple Interactions
Yik Siu Chan, Narutatsu Ri, Yuxin Xiao et al.
Compositional Image Decomposition with Diffusion Models
Jocelin Su, Nan Liu, Yanbo Wang et al.
Certified Unlearning for Neural Networks
Anastasiia Koloskova, Youssef Allouah, Animesh Jha et al.
Neural Collapse in Multi-label Learning with Pick-all-label Loss
Pengyu Li, Xiao Li, Yutong Wang et al.
Strategy Coopetition Explains the Emergence and Transience of In-Context Learning
Aaditya Singh, Ted Moskovitz, Sara Dragutinović et al.
Improving Token-Based World Models with Parallel Observation Prediction
Lior Cohen, Kaixin Wang, Bingyi Kang et al.
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
Jiawei Zhang, Xuan Yang, Taiqi Wang et al.
Mastering Multiple-Expert Routing: Realizable $H$-Consistency and Strong Guarantees for Learning to Defer
Anqi Mao, Mehryar Mohri, Yutao Zhong
Emergent Equivariance in Deep Ensembles
Jan Gerken, Pan Kessel
Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
Yangsibo Huang, Milad Nasr, Anastasios Angelopoulos et al.
Online Linear Regression in Dynamic Environments via Discounting
Andrew Jacobsen, Ashok Cutkosky
PatchPilot: A Cost-Efficient Software Engineering Agent with Early Attempts on Formal Verification
Hongwei Li, Yuheng Tang, Shiqi Wang et al.
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
Jianliang He, Siyu Chen, Fengzhuo Zhang et al.
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
Akhiad Bercovich, Tomer Ronen, Talor Abramovich et al.
Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis
Juyeon Ko, Inho Kong, Dogyun Park et al.
CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models
Guangzhi Sun, Xiao Zhan, Shutong Feng et al.
DiJiang: Efficient Large Language Models through Compact Kernelization
Hanting Chen, Liuzhicheng Liuzhicheng, Xutao Wang et al.
Predictive Linear Online Tracking for Unknown Targets
Anastasios Tsiamis, Aren Karapetyan, Yueshan Li et al.
Reflected Flow Matching
Tianyu Xie, Yu Zhu, Longlin Yu et al.
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance
Yongchao Chen, Yilun Hao, Yueying Liu et al.
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces
Rashid Mushkani, Perampalli Shravan Nayak, Hugo Berard et al.
Hierarchical Equivariant Policy via Frame Transfer
Haibo Zhao, Dian Wang, Yizhe Zhu et al.
MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning
Zihan Chen, Song Wang, Zhen Tan et al.
xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
Maximilian Beck, Korbinian Pöppel, Phillip Lippe et al.
Embodied CoT Distillation From LLM To Off-the-shelf Agents
Wonje Choi, Woo Kyung Kim, Minjong Yoo et al.
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans et al.
Shifted Interpolation for Differential Privacy
Jinho Bok, Weijie Su, Jason Altschuler
Low-Rank Similarity Mining for Multimodal Dataset Distillation
Yue Xu, Zhilin Lin, Yusong Qiu et al.
Self-attention Networks Localize When QK-eigenspectrum Concentrates
Han Bao, Ryuichiro Hataya, Ryo Karakida
Provable Contrastive Continual Learning
Yichen Wen, Zhiquan Tan, Kaipeng Zheng et al.
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
Thomas Schmied, Thomas Adler, Vihang Patil et al.
MUDDFormer: Breaking Residual Bottlenecks in Transformers via Multiway Dynamic Dense Connections
Da Xiao, Qingye Meng, Shengping Li et al.
Learning to Reach Goals via Diffusion
Vineet Jain, Siamak Ravanbakhsh
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning
Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu et al.
MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design
Haojie Duanmu, Xiuhong Li, Zhihang Yuan et al.
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language Models
Akhil Kedia, Mohd Abbas Zaidi, Sushil Khyalia et al.
Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion
Kulin Shah, Alkis Kalavasis, Adam Klivans et al.
Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems
David T. Hoffmann, Simon Schrodi, Jelena Bratulić et al.
Vocabulary for Universal Approximation: A Linguistic Perspective of Mapping Compositions
Yongqiang Cai
Generation from Noisy Examples
Ananth Raman, Vinod Raman
Causal Action Influence Aware Counterfactual Data Augmentation
Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica et al.
Improving Your Model Ranking on Chatbot Arena by Vote Rigging
Rui Min, Tianyu Pang, Chao Du et al.
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical
Wei Wang, Takashi Ishida, Yu-Jie Zhang et al.
Neural operators meet conjugate gradients: The FCG-NO method for efficient PDE solving
Alexander Rudikov, Fanaskov Vladimir, Ekaterina Muravleva et al.
Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity
Xudong Li, Timin Gao, Runze Hu et al.
How Free is Parameter-Free Stochastic Optimization?
Amit Attia, Tomer Koren
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
Changsheng Wang, Yihua Zhang, jinghan jia et al.
Delving into Differentially Private Transformer
Youlong Ding, Xueyang Wu, Yining meng et al.
Understanding Diffusion Models by Feynman's Path Integral
Yuji Hirono, Akinori Tanaka, Kenji Fukushima
CellFlux: Simulating Cellular Morphology Changes via Flow Matching
Yuhui Zhang, Yuchang Su, Chenyu Wang et al.
AlphaPO: Reward Shape Matters for LLM Alignment
Aman Gupta, Shao Tang, Qingquan Song et al.
Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
Luca Masserano, Abdul Fatir Ansari, Boran Han et al.
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
Doron Haviv, Russell Kunes, Thomas Dougherty et al.
How Expressive are Knowledge Graph Foundation Models?
Xingyue Huang, Pablo Barcelo, Michael Bronstein et al.
Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees
Yannis Montreuil, Axel Carlier, Lai Xing Ng et al.
Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models
Som Sagar, Aditya Taparia, Ransalu Senanayake
Improving the Scaling Laws of Synthetic Data with Deliberate Practice
Reyhane Askari Hemmat, Mohammad Pezeshki, Elvis Dohmatob et al.
To the Max: Reinventing Reward in Reinforcement Learning
Grigorii Veviurko, Wendelin Boehmer, Mathijs de Weerdt
Sample Complexity Bounds for Estimating Probability Divergences under Invariances
Behrooz Tahmasebi, Stefanie Jegelka
A Global Geometric Analysis of Maximal Coding Rate Reduction
Peng Wang, Huikang Liu, Druv Pai et al.
SafeMap: Robust HD Map Construction from Incomplete Observations
Xiaoshuai Hao, Lingdong Kong, Rong Yin et al.
GraphGPT: Generative Pre-trained Graph Eulerian Transformer
Qifang Zhao, Weidong Ren, Tianyu Li et al.
I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian et al.
Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
Jaeho Kim, Yunseok Lee, Seulki Lee
Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks
Lorenzo Bardone, Sebastian Goldt
Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments
Allen Tran, Aurelien Bibaut, Nathan Kallus
Enabling Uncertainty Estimation in Iterative Neural Networks
Nikita Durasov, Doruk Oner, Jonathan Donier et al.
Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
Nikita Tsoy, Nikola Konstantinov
Adaptive Self-improvement LLM Agentic System for ML Library Development
Genghan Zhang, Weixin Liang, Olivia Hsu et al.
Beyond Individual Input for Deep Anomaly Detection on Tabular Data
Hugo Thimonier, Fabrice Popineau, Arpad Rimmel et al.
Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization
Ruizhong Qiu, Hanghang Tong
NExtLong: Toward Effective Long-Context Training without Long Documents
Chaochen Gao, Xing W, Zijia Lin et al.
Scaling Trends in Language Model Robustness
Nikolaus Howe, Ian McKenzie, Oskar Hollinsworth et al.
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization
Andrew Lowy, Jonathan Ullman, Stephen Wright
Constrained Reinforcement Learning Under Model Mismatch
Zhongchang Sun, Sihong He, Fei Miao et al.
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
Shuyu Cheng, Yibo Miao, Yinpeng Dong et al.
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin et al.
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret
Han Zhong, Jiachen Hu, Yecheng Xue et al.
Federated Representation Learning in the Under-Parameterized Regime
Renpu Liu, Cong Shen, Jing Yang
Multimodal Medical Code Tokenizer
Xiaorui Su, Shvat Messica, Yepeng Huang et al.
D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
Zijing Hu, Fengda Zhang, Kun Kuang
From Generalization Analysis to Optimization Designs for State Space Models
Fusheng Liu, Qianxiao Li
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.
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Yibo Zhou, Hai-Miao Hu, Yirong Xiang et al.
Exploring Correlations of Self-Supervised Tasks for Graphs
Taoran Fang, Wei Chow, Yifei Sun et al.
Scaling Laws for the Value of Individual Data Points in Machine Learning
Ian Covert, Wenlong Ji, Tatsunori Hashimoto et al.
Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds
Noémie Jaquier, Leonel Rozo, Miguel González-Duque et al.
Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
Shiwei Li, Xiandi Luo, Xing Tang et al.
Expressivity and Generalization: Fragment-Biases for Molecular GNNs
Tom Wollschläger, Niklas Kemper, Leon Hetzel et al.
Position: Insights from Survey Methodology can Improve Training Data
Stephanie Eckman, Barbara Plank, Frauke Kreuter
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li
Diversified Batch Selection for Training Acceleration
Feng Hong, Yueming LYU, Jiangchao Yao et al.
DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers
Xuanlei Zhao, Shenggan Cheng, Chang Chen et al.
How Much Can We Forget about Data Contamination?
Sebastian Bordt, Suraj Srinivas, Valentyn Boreiko et al.
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Guy Bar Shalom, Beatrice Bevilacqua, Haggai Maron
Asymptotics of Learning with Deep Structured (Random) Features
Dominik Schröder, Daniil Dmitriev, Hugo Cui et al.
Allocation Requires Prediction Only if Inequality Is Low
Ali Shirali, Rediet Abebe, Moritz Hardt
Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams
Brian Cho, Kyra Gan, Nathan Kallus
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
Zelin Zang, Hao Luo, Kai Wang et al.
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization
Li Ding, Jenny Zhang, Jeff Clune et al.
Can Transformers Reason Logically? A Study in SAT Solving
Leyan Pan, Vijay Ganesh, Jacob Abernethy et al.
Do Multiple Instance Learning Models Transfer?
Daniel Shao, Richard Chen, Andrew Song et al.
Trained Random Forests Completely Reveal your Dataset
Julien Ferry, Ricardo Fukasawa, Timothée Pascal et al.
Generalization Bound and New Algorithm for Clean-Label Backdoor Attack
Lijia Yu, Shuang Liu, Yibo Miao et al.
FRAG: Frequency Adapting Group for Diffusion Video Editing
Sunjae Yoon, Gwanhyeong Koo, Geonwoo Kim et al.
Retrieval-Augmented Perception: High-resolution Image Perception Meets Visual RAG
Wenbin Wang, Yongcheng Jing, Liang Ding et al.
DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design
Samuel Garcin, James Doran, Shangmin Guo et al.
Understanding Mode Connectivity via Parameter Space Symmetry
Bo Zhao, Nima Dehmamy, Robin Walters et al.
Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
Tao Li, Zhengbao He, Yujun Li et al.
TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks
Mathilde Papillon, Guillermo Bernardez, Claudio Battiloro et al.
Diffusion Rejection Sampling
Byeonghu Na, Yeongmin Kim, Minsang Park et al.
Using Left and Right Brains Together: Towards Vision and Language Planning
Jun CEN, Chenfei Wu, Xiao Liu et al.
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Zongyu Lin, Yao Tang, Xingcheng Yao et al.
Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
Shikai Qiu, Lechao Xiao, Andrew Wilson et al.
Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization
Peiyan Zhang, Haibo Jin, Leyang Hu et al.
Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
Batiste Le Bars, Aurélien Bellet, Marc Tommasi et al.
KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation
Minsik Cho, Mohammad Rastegari, Devang Naik
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning
Heewoong Choi, Sangwon Jung, Hongjoon Ahn et al.
CTBench: A Library and Benchmark for Certified Training
Yuhao Mao, Stefan Balauca, Martin Vechev
Fundamental Benefit of Alternating Updates in Minimax Optimization
Jaewook Lee, Hanseul Cho, Chulhee Yun
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.
Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree
Lang Feng, Pengjie Gu, Bo An et al.
Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?
M. Saquib Sarfraz, Mei-Yen Chen, Lukas Layer et al.
Differentiability and Optimization of Multiparameter Persistent Homology
Luis Scoccola, Siddharth Setlur, David Loiseaux et al.
Reliable and Efficient Amortized Model-based Evaluation
Sang Truong, Yuheng Tu, Percy Liang et al.
Reasoning-as-Logic-Units: Scaling Test-Time Reasoning in Large Language Models Through Logic Unit Alignment
Cheryl Li, Tianyuan Xu, Yiwen Guo
Mean Estimation in the Add-Remove Model of Differential Privacy
Alex Kulesza, Ananda Suresh, Yuyan Wang
Cross-view Masked Diffusion Transformers for Person Image Synthesis
Trung Pham, Kang Zhang, Chang Yoo
PENCIL: Long Thoughts with Short Memory
Chenxiao Yang, Nati Srebro, David McAllester et al.
RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression
Payman Behnam, Yaosheng Fu, Ritchie Zhao et al.
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
Jonas Schweisthal, Dennis Frauen, M van der Schaar et al.
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion
Adeesh Kolluru, John Kitchin
Jacobian Regularizer-based Neural Granger Causality
Wanqi Zhou, Shuanghao Bai, Shujian Yu et al.
Libra: Building Decoupled Vision System on Large Language Models
Yifan Xu, Xiaoshan Yang, Yaguang Song et al.
CuTS: Customizable Tabular Synthetic Data Generation
Mark Vero, Mislav Balunovic, Martin Vechev
Estimating Barycenters of Distributions with Neural Optimal Transport
Alexander Kolesov, Petr Mokrov, Igor Udovichenko et al.
Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
Honghao Chen, Zhang Yurong, xiaokun Feng et al.
Towards Understanding Inductive Bias in Transformers: A View From Infinity
Itay Lavie, Guy Gur-Ari, Zohar Ringel
Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu CHEN, James Kwok
Non-clairvoyant Scheduling with Partial Predictions
Ziyad Benomar, Vianney Perchet
Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI
Julien Pourcel, Cédric Colas, Pierre-Yves Oudeyer
Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
Xinran Li, Zifan LIU, Shibo Chen et al.
Solving Poisson Equations using Neural Walk-on-Spheres
Hong Chul Nam, Julius Berner, Anima Anandkumar
When Do LLMs Help With Node Classification? A Comprehensive Analysis
Xixi Wu, Yifei Shen, Fangzhou Ge et al.
Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds
Emanuele Troiani, Hugo Cui, Yatin Dandi et al.
Differentiable Mapper for Topological Optimization of Data Representation
Ziyad Oulhaj, Mathieu Carrière, Bertrand Michel
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
Haonan Yuan, Qingyun Sun, Junhua Shi et al.
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
Georgios Kaissis, Stefan Kolek, Borja de Balle Pigem et al.
Synthesizing Software Engineering Data in a Test-Driven Manner
Lei Zhang, Jiaxi Yang, Min Yang et al.
On the Calibration of Human Pose Estimation
Kerui Gu, Rongyu Chen, Xuanlong Yu et al.
Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization
Rui Li, Chaozhuo Li, Yanming Shen et al.
Quantum Positional Encodings for Graph Neural Networks
Slimane Thabet, Mehdi Djellabi, Igor Sokolov et al.
Safety Reasoning with Guidelines
Haoyu Wang, Zeyu Qin, Li Shen et al.
Learning Efficient Robotic Garment Manipulation with Standardization
zhou changshi, Feng Luan, hujiarui et al.
Gaussian Mixture Flow Matching Models
Hansheng Chen, Kai Zhang, Hao Tan et al.
On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
Wei Shen, Ruida Zhou, Jing Yang et al.
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages
Andrew Jesson, Christopher Lu, Gunshi Gupta et al.
Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
Xiaoyu Wen, Chenjia Bai, Kang Xu et al.