Most Cited ICML "probability of improvement" Papers
5,975 papers found • Page 3 of 30
Conference
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
Rong-Xi Tan, Ming Chen, Ke Xue et al.
Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss
Abhijeet Mulgund, Chirag Pabbaraju
Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning
Armin Behnamnia, Gholamali Aminian, Alireza Aghaei et al.
Sliding Puzzles Gym: A Scalable Benchmark for State Representation in Visual Reinforcement Learning
Bryan L. M. de Oliveira, Luana G. B. Martins, Bruno Brandão et al.
CALM: Consensus-Aware Localized Merging for Multi-Task Learning
Kunda Yan, Min Zhang, Sen Cui et al.
SPEX: Scaling Feature Interaction Explanations for LLMs
Justin S. Kang, Landon Butler, Abhineet Agarwal et al.
UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model
Timo Kaiser, Thomas Norrenbrock, Bodo Rosenhahn
Blink of an eye: a simple theory for feature localization in generative models
Marvin Li, Aayush Karan, Sitan Chen
SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs
Shibo Jie, Yehui Tang, Kai Han et al.
Focal-SAM: Focal Sharpness-Aware Minimization for Long-Tailed Classification
Sicong Li, Qianqian Xu, Zhiyong Yang et al.
Fast and Low-Cost Genomic Foundation Models via Outlier Removal
Haozheng Luo, Chenghao Qiu, Maojiang Su et al.
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning
Laixi Shi, Jingchu Gai, Eric Mazumdar et al.
FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems
Arya Fayyazi, Mehdi Kamal, Massoud Pedram
Emotional Face-to-Speech
Jiaxin Ye, Boyuan Cao, Hongming Shan
CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation
Minghao Fu, Guo-Hua Wang, Liangfu Cao et al.
Controlled Generation with Equivariant Variational Flow Matching
Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama et al.
X-Hacking: The Threat of Misguided AutoML
Rahul Sharma, Sumantrak Mukherjee, Andrea Šipka et al.
Nested Expectations with Kernel Quadrature
Zonghao Chen, Masha Naslidnyk, Francois-Xavier Briol
Improving Multimodal Learning Balance and Sufficiency through Data Remixing
Xiaoyu Ma, Hao Chen, Yongjian Deng
Dynamic Sparse Training of Diagonally Sparse Networks
Abhishek Tyagi, Arjun Iyer, William Renninger et al.
TruthFlow: Truthful LLM Generation via Representation Flow Correction
Hanyu Wang, Bochuan Cao, Yuanpu Cao et al.
The impact of uncertainty on regularized learning in games
Pierre-Louis Cauvin, Davide Legacci, Panayotis Mertikopoulos
FloE: On-the-Fly MoE Inference on Memory-constrained GPU
Yuxin Zhou, Zheng Li, Jun Zhang et al.
Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models
Jialin Zhao, Yingtao Zhang, Carlo Cannistraci
Design Considerations in Offline Preference-based RL
Alekh Agarwal, Christoph Dann, Teodor Vanislavov Marinov
Overcoming Multi-step Complexity in Multimodal Theory-of-Mind Reasoning: A Scalable Bayesian Planner
Chunhui Zhang, Zhongyu Ouyang, Kwonjoon Lee et al.
NeuronTune: Towards Self-Guided Spurious Bias Mitigation
Guangtao Zheng, Wenqian Ye, Aidong Zhang
Synonymous Variational Inference for Perceptual Image Compression
Zijian Liang, Kai Niu, Changshuo Wang et al.
BiMark: Unbiased Multilayer Watermarking for Large Language Models
Xiaoyan Feng, He Zhang, Yanjun Zhang et al.
Improving Generalization with Flat Hilbert Bayesian Inference
Tuan Truong, Quyen Tran, Ngoc Quan Pham et al.
Test-time Adaptation on Graphs via Adaptive Subgraph-based Selection and Regularized Prototypes
Ming Zhang, Qixin Zhang, Xiao Luo et al.
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
Yuanzhe Hu, Kinshuk Goel, Vlad Killiakov et al.
Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
Zi Liang, Haibo Hu, Qingqing Ye et al.
Universal Approximation of Mean-Field Models via Transformers
Shiba Biswal, Karthik Elamvazhuthi, Rishi Sonthalia
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
Yao Shu, Wenyang Hu, See-Kiong Ng et al.
GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
Kecen Li, Zhicong Huang, Xinwen Hou et al.
Towards Robust Influence Functions with Flat Validation Minima
Xichen Ye, Yifan Wu, Weizhong Zhang et al.
Learning Safe Strategies for Value Maximizing Buyers in Uniform Price Auctions
Negin Golrezaei, Sourav Sahoo
Determining Layer-wise Sparsity for Large Language Models Through a Theoretical Perspective
Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.
A Market for Accuracy: Classification Under Competition
Ohad Einav, Nir Rosenfeld
Reward-free World Models for Online Imitation Learning
Shangzhe Li, Zhiao Huang, Hao Su
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
Ngoc Quan Pham, Tuan Truong, Quyen Tran et al.
Provably Improving Generalization of Few-shot models with Synthetic Data
Lan-Cuong Nguyen, Quan Nguyen-Tri, Bang Khanh et al.
Complex Wavelet Mutual Information Loss: A Multi-Scale Loss Function for Semantic Segmentation
Renhao Lu
Attention-Only Transformers via Unrolled Subspace Denoising
Peng Wang, Yifu Lu, Yaodong Yu et al.
Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance
YUSONG WANG, Shiyin Tan, Jialun Shen et al.
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro et al.
Zero Shot Generalization of Vision-Based RL Without Data Augmentation
Sumeet Batra, Gaurav Sukhatme
Towards an Explainable Comparison and Alignment of Feature Embeddings
Mohammad Jalali, Bahar Dibaei Nia, Farzan Farnia
Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
Thibault de Surrel, Fabien Lotte, Sylvain Chevallier et al.
The Disparate Benefits of Deep Ensembles
Kajetan Schweighofer, Adrián Arnaiz-Rodríguez, Sepp Hochreiter et al.
A Parametric Contextual Online Learning Theory of Brokerage
François Bachoc, Tommaso Cesari, Roberto Colomboni
Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models
Alina Shutova, Vladimir Malinovskii, Vage Egiazarian et al.
Joint Learning of Energy-based Models and their Partition Function
Michael Sander, Vincent Roulet, Tianlin Liu et al.
Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning
Xinrui Wang, Shao-Yuan Li, Jiaqiang Zhang et al.
Hierarchical Refinement: Optimal Transport to Infinity and Beyond
Peter Halmos, Julian Gold, Xinhao Liu et al.
Quantum Optimization via Gradient-Based Hamiltonian Descent
Jiaqi Leng, Bin Shi
Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation
Hoigi Seo, Wongi Jeong, Jae-sun Seo et al.
Learning Gaussian DAG Models without Condition Number Bounds
Constantinos Daskalakis, Vardis Kandiros, Rui Yao
Towards a Unified Framework of Clustering-based Anomaly Detection
Zeyu Fang, Ming Gu, Sheng Zhou et al.
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye et al.
IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling
Kuan Po Huang, Shu-wen Yang, Huy Phan et al.
Graph World Model
Tao Feng, Yexin Wu, Guanyu Lin et al.
Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration Story
Vincenzo De Paola, Riccardo Zamboni, Mirco Mutti et al.
A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment
Edward Chang
Fleet of Agents: Coordinated Problem Solving with Large Language Models
Lars Klein, Nearchos Potamitis, Roland Aydin et al.
Generative Intervention Models for Causal Perturbation Modeling
Nora Schneider, Lars Lorch, Niki Kilbertus et al.
Predicting the Susceptibility of Examples to Catastrophic Forgetting
Guy Hacohen, Tinne Tuytelaars
Understanding the Forgetting of (Replay-based) Continual Learning via Feature Learning: Angle Matters
Hongyi Wan, Shiyuan Ren, Wei Huang et al.
Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search
Ziyad Benomar, Lorenzo Croissant, Vianney Perchet et al.
Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution
Alex Clinton, Yiding Chen, Jerry Zhu et al.
Speeding up Policy Simulation in Supply Chain RL
Vivek Farias, Joren Gijsbrechts, Aryan Khojandi et al.
Efficient Time Series Processing for Transformers and State-Space Models through Token Merging
Leon Götz, Marcel Kollovieh, Stephan Günnemann et al.
BARNN: A Bayesian Autoregressive and Recurrent Neural Network
Dario Coscia, Max Welling, Nicola Demo et al.
PoisonedEye: Knowledge Poisoning Attack on Retrieval-Augmented Generation based Large Vision-Language Models
Chenyang Zhang, Xiaoyu Zhang, Jian Lou et al.
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability
Daiqing Wu, Dongbao Yang, Sicheng Zhao et al.
When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Network
Dong Xiao, Guangyao Chen, Peixi Peng et al.
Towards Practical Defect-Focused Automated Code Review
Junyi Lu, Lili Jiang, Xiaojia Li et al.
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
Jaehyeon Kim, Taehong Moon, Keon Lee et al.
Wasserstein Policy Optimization
David Pfau, Ian Davies, Diana Borsa et al.
Gradient-based Explanations for Deep Learning Survival Models
Sophie Hanna Langbein, Niklas Koenen, Marvin N. Wright
Exploiting Curvature in Online Convex Optimization with Delayed Feedback
Hao Qiu, Emmanuel Esposito, Mengxiao Zhang
SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
Hong-Ming Chiu, Hao Chen, Huan Zhang et al.
LipsNet++: Unifying Filter and Controller into a Policy Network
Xujie Song, Liangfa Chen, Tong Liu et al.
Learning In-context $n$-grams with Transformers: Sub-$n$-grams Are Near-Stationary Points
Aditya Vardhan Varre, Gizem Yüce, Nicolas Flammarion
Projection Pursuit Density Ratio Estimation
Meilin Wang, Wei Huang, Mingming Gong et al.
Measuring Diversity: Axioms and Challenges
Mikhail Mironov, Liudmila Prokhorenkova
A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control
Zilin Kang, Chenyuan Hu, Yu Luo et al.
Implicit Riemannian Optimism with Applications to Min-Max Problems
Christophe Roux, David Martinez-Rubio, Sebastian Pokutta
Temporal Distance-aware Transition Augmentation for Offline Model-based Reinforcement Learning
Dongsu Lee, Minhae Kwon
Token Coordinated Prompt Attention is Needed for Visual Prompting
Zichen Liu, Xu Zou, Gang Hua et al.
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu et al.
Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation
Bowen Zheng, Tianming Yang
Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning
Mehrdad Moghimi, Hyejin Ku
Accelerating Unbiased LLM Evaluation via Synthetic Feedback
Zhaoyi Zhou, Yuda Song, Andrea Zanette
Aligned Multi Objective Optimization
Yonathan Efroni, Ben Kretzu, Daniel Jiang et al.
Linear Bandits with Partially Observable Features
Wonyoung Kim, Sungwoo PARK, Garud Iyengar et al.
Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents
Junyan Liu, Lillian Ratliff
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo et al.
Dueling Convex Optimization with General Preferences
Aadirupa Saha, Tomer Koren, Yishay Mansour
Unbiased Evaluation of Large Language Models from a Causal Perspective
Meilin Chen, Jian Tian, Liang Ma et al.
Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning
Kyowoon Lee, Jaesik Choi
Hybrid Spiking Vision Transformer for Object Detection with Event Cameras
Qi Xu, Jie Deng, Jiangrong Shen et al.
Faster Approximation Algorithms for k-Center via Data Reduction
Arnold Filtser, Shaofeng Jiang, Yi Li et al.
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
Toby Boyne, Jose Pablo Folch, Robert Lee et al.
Faster Sampling via Stochastic Gradient Proximal Sampler
Xunpeng Huang, Difan Zou, Hanze Dong et al.
Isolated Causal Effects of Natural Language
Victoria Lin, Louis-Philippe Morency, Eli Ben-Michael
NegMerge: Sign-Consensual Weight Merging for Machine Unlearning
Hyo Seo Kim, Dongyoon Han, Junsuk Choe
Position: AI Scaling: From Up to Down and Out
Yunke Wang, Yanxi Li, Chang Xu
Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible
Lin-Han Jia, Wen-Chao Hu, Jie-Jing Shao et al.
ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics
Letian Chen, Nina Moorman, Matthew Gombolay
Learning multivariate Gaussians with imperfect advice
Arnab Bhattacharyya, Davin Choo, Philips George John et al.
ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
Zhiyao Ren, Siyuan Liang, Aishan Liu et al.
Ehrenfeucht-Haussler Rank and Chain of Thought
Pablo Barcelo, Alexander Kozachinskiy, Tomasz Steifer
It's My Data Too: Private ML for Datasets with Multi-User Training Examples
Arun Ganesh, Ryan McKenna, Hugh B McMahan et al.
On the Impact of Performative Risk Minimization for Binary Random Variables
Nikita Tsoy, Ivan Kirev, Negin Rahimiyazdi et al.
Nonparametric Teaching for Graph Property Learners
Chen Zhang, Weixin Bu, Zeyi Ren et al.
S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking
Tao Tang, Lijun Zhou, Pengkun Hao et al.
Preference Learning for AI Alignment: a Causal Perspective
Katarzyna Kobalczyk, Mihaela van der Schaar
Simple and Critical Iterative Denoising: A Recasting of Discrete Diffusion in Graph Generation
Yoann Boget
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
Renzhe Xu, Kang Wang, Bo Li
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Demonstration Selection for In-Context Learning via Reinforcement Learning
Xubin Wang, Jianfei Wu, Yuan Yichen et al.
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang, Cheng Long, Yongyi Mao
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
Da Long, Zhitong Xu, Guang Yang et al.
Of Mice and Machines: A Comparison of Learning Between Real World Mice and RL Agents
Shuo Han, German Espinosa, Junda Huang et al.
Distinguishing Cause from Effect with Causal Velocity Models
Johnny Xi, Hugh Dance, Peter Orbanz et al.
Efficient Diffusion Models for Symmetric Manifolds
Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
Simple Path Structural Encoding for Graph Transformers
Louis Airale, Antonio Longa, Mattia Rigon et al.
MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
Fang-Duo Tsai, Shih-Lun Wu, Weijaw Lee et al.
R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning
Harsh Goel, Mohammad Omama, Behdad Chalaki et al.
Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
BOOD: Boundary-based Out-Of-Distribution Data Generation
Qilin Liao, Shuo Yang, Bo Zhao et al.
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
Atsushi Nitanda, Anzelle Lee, Damian Kai et al.
TabFSBench: Tabular Benchmark for Feature Shifts in Open Environments
Zijian Cheng, 贾 子怡, Zhi Zhou et al.
BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference
Wonsuk Jang, Thierry Tambe
PAC Learning with Improvements
Idan Attias, Avrim Blum, Keziah Naggita et al.
PIGDreamer: Privileged Information Guided World Models for Safe Partially Observable Reinforcement Learning
Dongchi Huang, Jiaqi WANG, Yang Li et al.
Beyond One-Hot Labels: Semantic Mixing for Model Calibration
Haoyang Luo, Linwei Tao, Minjing Dong et al.
CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive Perspective
Jiayu Liu, Zhenya Huang, Wei Dai et al.
Finite-Time Analysis of Discrete-Time Stochastic Interpolants
Yuhao Liu, Yu Chen, Rui Hu et al.
TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories
Honghua Dong, Jiacheng Yang, Xun Deng et al.
Federated In-Context Learning: Iterative Refinement for Improved Answer Quality
Ruhan Wang, Zhiyong Wang, Chengkai Huang et al.
Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed Kernel
Carlota Parés Morlans, Michelle Yi, Claire Chen et al.
Enabling Optimal Decisions in Rehearsal Learning under CARE Condition
Wen-Bo Du, Hao-Yi Lei, Lue Tao et al.
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
Junyan Liu, ARNAB MAITI, Artin Tajdini et al.
Learning With Multi-Group Guarantees For Clusterable Subpopulations
Jessica Dai, Nika Haghtalab, Eric Zhao
Variational Counterfactual Intervention Planning to Achieve Target Outcomes
Xin Wang, Shengfei Lyu, Luo Chi et al.
The Role of Randomness in Stability
Max Hopkins, Shay Moran
A Theory for Conditional Generative Modeling on Multiple Data Sources
Rongzhen Wang, Yan Zhang, Chenyu Zheng et al.
MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
Jing Han, Binwei Yan, Tianyu Guo et al.
Efficient Long Context Fine-tuning with Chunk Flow
Xiulong Yuan, Hongtao Xu, Wenting Shen et al.
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel et al.
Layer-wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models
Saketh Bachu, Erfan Shayegani, Rohit Lal et al.
Grokking Beyond the Euclidean Norm of Model Parameters
Pascal Jr Tikeng Notsawo, Guillaume Dumas, Guillaume Rabusseau
LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
Beom Jin Kang, NamJoon Kim, Hyun Kim
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations
Lily Zhang, Hamid Dadkhahi, Mara Finkelstein et al.
Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics
Mohamad Al Ahdab, john leth, Zheng-Hua Tan
FIC-TSC: Learning Time Series Classification with Fisher Information Constraint
Xiwen Chen, Wenhui Zhu, Peijie Qiu et al.
SIMPLEMIX: Frustratingly Simple Mixing of Off- and On-policy Data in Language Model Preference Learning
Tianjian Li, Daniel Khashabi
Towards the Causal Complete Cause of Multi-Modal Representation Learning
Jingyao Wang, Siyu Zhao, Wenwen Qiang et al.
To Steer or Not to Steer? Mechanistic Error Reduction with Abstention for Language Models
Anna Hedström, Salim I. Amoukou, Tom Bewley et al.
Non-asymptotic Error Bounds in $\mathcal{W}_2$-Distance with Sqrt(d) Dimension Dependence and First Order Convergence for Langevin Monte Carlo beyond Log-Concavity
Bin Yang, Xiaojie Wang
SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
Yong Liang Goh, Zhiguang Cao, Yining Ma et al.
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
Zhe Zhang, Mingxiu Cai, Hanxiao Wang et al.
Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant Machines
Sho Sonoda, Yuka Hashimoto, Isao Ishikawa et al.
On the Provable Separation of Scales in Maximal Update Parameterization
Letong Hong, Zhangyang “Atlas” Wang
A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments
Yuchen Wang, Hongjue Zhao, Haohong Lin et al.
Are Large Language Models Ready for Multi-Turn Tabular Data Analysis?
Jinyang Li, Nan Huo, Yan Gao et al.
Bridging Layout and RTL: Knowledge Distillation based Timing Prediction
Mingjun Wang, Yihan Wen, Bin Sun et al.
LieRE: Lie Rotational Positional Encodings
Sophie Ostmeier, Brian Axelrod, Maya Varma et al.
Test-Time Multimodal Backdoor Detection by Contrastive Prompting
Yuwei Niu, Shuo He, Qi Wei et al.
Geometric Algebra Planes: Convex Implicit Neural Volumes
Irmak Sivgin, Sara Fridovich-Keil, Gordon Wetzstein et al.
Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods
Yifan HAO, xingyuan pan, Hanning Zhang et al.
An Entropy-Based Model for Hierarchical Learning
Amir R. Asadi
Hierarchical Masked Autoregressive Models with Low-Resolution Token Pivots
Guangting Zheng, Yehao Li, Yingwei Pan et al.
SPHINX: Structural Prediction using Hypergraph Inference Network
Iulia Duta, Pietro Lió
Concept-Centric Token Interpretation for Vector-Quantized Generative Models
Tianze Yang, Yucheng Shi, Mengnan Du et al.
An in depth look at the Procrustes-Wasserstein distance: properties and barycenters
Davide Adamo, Marco Corneli, Manon Vuillien et al.
Calibrated Language Models and How to Find Them with Label Smoothing
Jerry Huang, Peng Lu, QIUHAO Zeng
No Free Lunch from Random Feature Ensembles: Scaling Laws and Near-Optimality Conditions
Benjamin Ruben, William Tong, Hamza Chaudhry et al.
Contextual Linear Bandits with Delay as Payoff
Mengxiao Zhang, Yingfei Wang, Haipeng Luo
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara et al.
CursorCore: Assist Programming through Aligning Anything
Hao Jiang, Qi Liu, Rui Li et al.
BAnG: Bidirectional Anchored Generation for Conditional RNA Design
Roman Klypa, Alberto Bietti, Sergei Grudinin
UniMate: A Unified Model for Mechanical Metamaterial Generation, Property Prediction, and Condition Confirmation
Wangzhi Zhan, Chen Jianpeng, Dongqi Fu et al.
The Noisy Laplacian: a Threshold Phenomenon for Non-Linear Dimension Reduction
Alex Kokot, Octavian-Vlad Murad, Marina Meila
Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All
Ermis Soumalias, Jakob Heiss, Jakob Weissteiner et al.
LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation
Chen-Chia Chang, Wan-Hsuan Lin, Yikang Shen et al.
Position: A Theory of Deep Learning Must Include Compositional Sparsity
David A. Danhofer, Davide DAscenzo, Rafael Dubach et al.
Imitation Learning from a Single Temporally Misaligned Video
William Huey, Yuki (Huaxiaoyue) Wang, Anne Wu et al.
Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
Arya Mazumdar, Neha Sangwan
Theoretical Limitations of Ensembles in the Age of Overparameterization
Niclas Dern, John Cunningham, Geoff Pleiss
The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
Gül Sena Altıntaş, Devin Kwok, Colin Raffel et al.
Improving the Variance of Differentially Private Randomized Experiments through Clustering
Adel Javanmard, Vahab Mirrokni, Jean Pouget-Abadie
Vision-Language Model Selection and Reuse for Downstream Adaptation
Hao-Zhe Tan, Zhi Zhou, Yu-Feng Li et al.
A Meta-learner for Heterogeneous Effects in Difference-in-Differences
Hui Lan, Chang, Eleanor W Dillon et al.
Robust Reward Alignment via Hypothesis Space Batch Cutting
Zhixian Xie, Haode Zhang, Yizhe Feng et al.
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
Vicente Balmaseda, Bokun Wang, Lin et al.
Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese et al.