Most Cited ICML "conditional outcome invariance" Papers
5,975 papers found • Page 12 of 30
Conference
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro et al.
Position: We Need An Algorithmic Understanding of Generative AI
Oliver Eberle, Thomas McGee, Hamza Giaffar et al.
Do Transformer World Models Give Better Policy Gradients?
Michel Ma, Tianwei Ni, Clement Gehring et al.
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
Haoyang Zheng, Hengrong Du, Qi Feng et al.
Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
Qianglin Wen, Chengchun Shi, Ying Yang et al.
Infinite-Horizon Distributionally Robust Regret-Optimal Control
Taylan Kargin, Joudi Hajar, Vikrant Malik et al.
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
Haohui Wang, Yuzhen Mao, Yujun Yan et al.
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity
Erpai Luo, Xinran Wei, Lin Huang et al.
Scaling Laws for Upcycling Mixture-of-Experts Language Models
Seng Pei Liew, Takuya Kato, Sho Takase
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
Shengyao Lu, Bang Liu, Keith Mills et al.
Interacting Diffusion Processes for Event Sequence Forecasting
Mai Zeng, Florence Regol, Mark Coates
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models
Ludwig Winkler, Lorenz Richter, Manfred Opper
Understanding Generalization in Quantum Machine Learning with Margins
TAK HUR, Daniel Kyungdeock Park
Position: The Causal Revolution Needs Scientific Pragmatism
Joshua Loftus
UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs
Xi Han, Fei Hou, Hong Qin
Efficient Length-Generalizable Attention via Causal Retrieval for Long-Context Language Modeling
Xiang Hu, Zhihao Teng, Jun Zhao et al.
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
Inwoo Hwang, Yunhyeok Kwak, Suhyung Choi et al.
Parameter-Efficient Fine-Tuning of State Space Models
Kevin Galim, Wonjun Kang, Yuchen Zeng et al.
HaploVL: A Single-Transformer Baseline for Multi-Modal Understanding
Rui Yang, Lin Song, Yicheng Xiao et al.
$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts
Guanjie Chen, Xinyu Zhao, Tianlong Chen et al.
What can large language models do for sustainable food?
Anna Thomas, Adam Yee, Andrew Mayne et al.
Causal Discovery from Conditionally Stationary Time Series
Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra et al.
REG: Rectified Gradient Guidance for Conditional Diffusion Models
Zhengqi Gao, Kaiwen Zha, Tianyuan Zhang et al.
Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks
Akshay Kumar Jagadish, Julian Coda-Forno, Mirko Thalmann et al.
Minimizing $f$-Divergences by Interpolating Velocity Fields
Song Liu, Jiahao Yu, Jack Simons et al.
Extracting Training Data From Document-Based VQA Models
Francesco Pinto, Nathalie Rauschmayr, Florian Tramer et al.
On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
Undral Byambadalai, Tomu Hirata, Tatsushi Oka et al.
TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision
Zhuo Chen, Jacob McCarran, Esteban Vizcaino et al.
COPAL: Continual Pruning in Large Language Generative Models
Srikanth Malla, Joon Hee Choi, Chiho Choi
Revisiting Character-level Adversarial Attacks for Language Models
Elias Abad Rocamora, Yongtao Wu, Fanghui Liu et al.
SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
Tianshu Chu, Dachuan Xu, Wei Yao et al.
Regress, Don't Guess: A Regression-like Loss on Number Tokens for Language Models
Jonas Zausinger, Lars Pennig, Anamarija Kozina et al.
SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models
Han-Byul Kim, Duc Hoang, Arnav Kundu et al.
Unmasking Vulnerabilities: Cardinality Sketches under Adaptive Inputs
Sara Ahmadian, Edith Cohen
Looking Beyond the Top-1: Transformers Determine Top Tokens in Order
Daria Lioubashevski, Tomer Schlank, Gabriel Stanovsky et al.
Goal-Space Planning with Subgoal Models
Chunlok Lo, Kevin Roice, Parham Mohammad Panahi et al.
Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints
Yunsheng Tian, Ane Zuniga, Xinwei Zhang et al.
Cooperation of Experts: Fusing Heterogeneous Information with Large Margin
Shuo Wang, Shunyang Huang, Jinghui Yuan et al.
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent
Kaan Ozkara, Can Karakus, Parameswaran Raman et al.
InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization
Zhengyang Hu, Song Kang, Qunsong Zeng et al.
Equilibrium of Data Markets with Externality
Safwan Hossain, Yiling Chen
AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
Wenhao SUN, Rong-Cheng Tu, Jingyi Liao et al.
MODULI: Unlocking Preference Generalization via Diffusion Models for Offline Multi-Objective Reinforcement Learning
Yifu Yuan, Zhenrui Zheng, Zibin Dong et al.
Elucidating the design space of language models for image generation
Xuantong Liu, Shaozhe Hao, Xianbiao Qi et al.
Scaling Probabilistic Circuits via Monarch Matrices
Honghua Zhang, Meihua Dang, Benjie Wang et al.
Efficient Multi-modal Long Context Learning for Training-free Adaptation
Zehong Ma, Shiliang Zhang, Longhui Wei et al.
EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations
Haotian Zhai, Connor Lawless, Ellen Vitercik et al.
Understanding the Limits of Deep Tabular Methods with Temporal Shift
Haorun Cai, Han-Jia Ye
When Maximum Entropy Misleads Policy Optimization
Ruipeng Zhang, Ya-Chien Chang, Sicun Gao
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
MoonJeong Park, Jaeseung Heo, Dongwoo Kim
RAPID: Long-Context Inference with Retrieval-Augmented Speculative Decoding
Guanzheng Chen, Qilong Feng, Jinjie Ni et al.
Geometric Representation Condition Improves Equivariant Molecule Generation
Zian Li, Cai Zhou, Xiyuan Wang et al.
Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisition
Michael Valancius, Maxwell Lennon, Junier Oliva
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
Neta Shaul, Uriel Singer, Ricky T. Q. Chen et al.
Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders
Charles O'Neill, Alim Gumran, David Klindt
EditLord: Learning Code Transformation Rules for Code Editing
Weichen Li, Albert Jan, Baishakhi Ray et al.
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers
Brian Chen, Tianyang Hu, Hui Jin et al.
Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation
Randall Balestriero, Romain Cosentino, Sarath Shekkizhar
Learning Optimal Deterministic Policies with Stochastic Policy Gradients
Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli et al.
LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression
Haotian Wu, Gongpu Chen, Pier Luigi Dragotti et al.
Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming
Hany Hamed, Subin Kim, Dongyeong Kim et al.
An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures
Thibaut Boissin, Franck Mamalet, Thomas Fel et al.
AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios
Zhongzhan Huang, Mingfu Liang, Shanshan Zhong et al.
Collapse-Proof Non-Contrastive Self-Supervised Learning
EMANUELE SANSONE, Tim Lebailly, Tinne Tuytelaars
Mixture of Lookup Experts
Shibo Jie, Yehui Tang, Kai Han et al.
Towards Learning to Complete Anything in Lidar
Ayça Takmaz, Cristiano Saltori, Neehar Peri et al.
Error Feedback Can Accurately Compress Preconditioners
Ionut-Vlad Modoranu, Aleksei Kalinov, Eldar Kurtic et al.
Optimal Eye Surgeon: Finding image priors through sparse generators at initialization
Avrajit Ghosh, Xitong Zhang, Kenneth Sun et al.
Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing
Tianci Liu, Ruirui Li, Zihan Dong et al.
Exploring the Benefit of Activation Sparsity in Pre-training
Zhengyan Zhang, Chaojun Xiao, Qiujieli Qin et al.
Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer
Yilun Kong, Guozheng Ma, Qi Zhao et al.
Memorization Sinks: Isolating Memorization during LLM Training
Gaurav Ghosal, Pratyush Maini, Aditi Raghunathan
Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping
Muru Zhang, Mayank Mishra, Zhongzhu Zhou et al.
Predicting mutational effects on protein binding from folding energy
Arthur Deng, Karsten Householder, Fang Wu et al.
Activation Space Interventions Can Be Transferred Between Large Language Models
Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash et al.
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
Wenzhi Gao, Qi Deng
Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
Chen Zhang, Qiang HE, Yuan Zhou et al.
Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation
Jan Pauls, Max Zimmer, Berkant Turan et al.
Persistent Topological Features in Large Language Models
Yuri Gardinazzi, Karthik Viswanathan, Giada Panerai et al.
Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks
Yuhang Cai, Kangjie Zhou, Jingfeng Wu et al.
Reward-Augmented Data Enhances Direct Preference Alignment of LLMs
Shenao Zhang, Zhihan Liu, Boyi Liu et al.
Robust Conformal Outlier Detection under Contaminated Reference Data
Meshi Bashari, Matteo Sesia, Yaniv Romano
Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining
Qi Zhang, Tianqi Du, Haotian Huang et al.
Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing
Zijie Qiu, Jiaqi Wei, Xiang Zhang et al.
Unifying Specialized Visual Encoders for Video Language Models
Jihoon Chung, Tyler Zhu, Max Gonzalez Saez-Diez et al.
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
SADA: Stability-guided Adaptive Diffusion Acceleration
Ting Jiang, Yixiao Wang, Hancheng Ye et al.
One Leaf Reveals the Season: Occlusion-Based Contrastive Learning with Semantic-Aware Views for Efficient Visual Representation
Xiaoyu Yang, Lijian Xu, Hongsheng Li et al.
Hessian Geometry of Latent Space in Generative Models
Alexander Lobashev, Dmitry Guskov, Maria Larchenko et al.
Neighboring Perturbations of Knowledge Editing on Large Language Models
Jun-Yu Ma, Zhen-Hua Ling, Ningyu Zhang et al.
B-score: Detecting biases in large language models using response history
An Vo, Mohammad Reza Taesiri, Daeyoung Kim et al.
Ranked Entropy Minimization for Continual Test-Time Adaptation
Jisu Han, Jaemin Na, Wonjun Hwang
Rethinking Chain-of-Thought from the Perspective of Self-Training
Zongqian Wu, Baoduo Xu, Ruochen Cui et al.
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation
Benjamin Dupuis, Umut Simsekli
Neuro-Symbolic Temporal Point Processes
Yang Yang, Chao Yang, Boyang Li et al.
On the Benefits of Active Data Collection in Operator Learning
Unique Subedi, Ambuj Tewari
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
Chung-En Sun, Sicun Gao, Lily Weng
To Steer or Not to Steer? Mechanistic Error Reduction with Abstention for Language Models
Anna Hedström, Salim I. Amoukou, Tom Bewley et al.
Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models
Pierre Mergny, Justin Ko, FLORENT KRZAKALA
No-Regret is not enough! Bandits with General Constraints through Adaptive Regret Minimization
Martino Bernasconi, Matteo Castiglioni, Andrea Celli
Constrained Belief Updates Explain Geometric Structures in Transformer Representations
Mateusz Piotrowski, Paul Riechers, Daniel Filan et al.
Supercharging Graph Transformers with Advective Diffusion
Qitian Wu, Chenxiao Yang, Kaipeng Zeng et al.
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye et al.
Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance
Lisha Chen, Quan Xiao, Ellen Fukuda et al.
Tuning LLM Judge Design Decisions for 1/1000 of the Cost
David Salinas, Omar Swelam, Frank Hutter
Impact of Decentralized Learning on Player Utilities in Stackelberg Games
Kate Donahue, Nicole Immorlica, Meena Jagadeesan et al.
Smoothing Proximal Gradient Methods for Nonsmooth Sparsity Constrained Optimization: Optimality Conditions and Global Convergence
Ganzhao Yuan
Exploring the LLM Journey from Cognition to Expression with Linear Representations
Yuzi Yan, Jialian Li, YipinZhang et al.
LLMs can see and hear without any training
Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen et al.
Scalable Generation of Spatial Transcriptomics from Histology Images via Whole-Slide Flow Matching
Tinglin Huang, Tianyu Liu, Mehrtash Babadi et al.
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu et al.
On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
Fateme Jamshidi, Luca Ganassali, Negar Kiyavash
Causal Effect Identification in LiNGAM Models with Latent Confounders
Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar et al.
Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation
D. Sculley, William Cukierski, Phil Culliton et al.
A New Computationally Efficient Algorithm to solve Feature Selection for Functional Data Classification in High-dimensional Spaces
Tobia Boschi, FRANCESCA BONIN, Rodrigo Ordonez-Hurtado et al.
First-Order Manifold Data Augmentation for Regression Learning
Ilya Kaufman, Omri Azencot
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
Local Causal Structure Learning in the Presence of Latent Variables
Feng Xie, Zheng Li, Peng Wu et al.
Beyond Entropy: Region Confidence Proxy for Wild Test-Time Adaptation
Zixuan Hu, Yichun Hu, Xiaotong Li et al.
Flexible Tails for Normalizing Flows
Tennessee Hickling, Dennis Prangle
Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments
Antoine Dedieu, Wolfgang Lehrach, Guangyao Zhou et al.
PINNsAgent: Automated PDE Surrogation with Large Language Models
Qingpo Wuwu, Chonghan Gao, Tianyu Chen et al.
How to Explore with Belief: State Entropy Maximization in POMDPs
Riccardo Zamboni, Duilio Cirino, Marcello Restelli et al.
LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
Dachuan Shi, Yonggan Fu, Xiangchi Yuan et al.
Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation
Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov et al.
KIND: Knowledge Integration and Diversion for Training Decomposable Models
Yucheng Xie, Fu Feng, Ruixiao Shi et al.
Selective Response Strategies for GenAI
Boaz Taitler, Omer Ben-Porat
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
Daniil Laptev, Nikita Balagansky, Yaroslav Aksenov et al.
When Bad Data Leads to Good Models
Kenneth Li, Yida Chen, Fernanda Viégas et al.
Dynamic Correlation Clustering in Sublinear Update Time
Vincent Cohen-Addad, Silvio Lattanzi, Andreas Maggiori et al.
Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations
Lucy Farnik, Tim Lawson, Conor Houghton et al.
Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency
Runqi Lin, Chaojian Yu, Bo Han et al.
Aligning Multimodal Representations through an Information Bottleneck
Antonio Almudévar, Jose Miguel Hernandez-Lobato, Sameer Khurana et al.
Enhancing Statistical Validity and Power in Hybrid Controlled Trials: A Randomization Inference Approach with Conformal Selective Borrowing
Ke Zhu, Shu Yang, Xiaofei Wang
Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
Jing Yang
Improving Rationality in the Reasoning Process of Language Models through Self-playing Game
Pinzheng Wang, Juntao Li, Zecheng Tang et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.
Position: AI/ML Influencers Have a Place in the Academic Process
Iain Xie Weissburg, Mehir Arora, Xinyi Wang et al.
Boosting Virtual Agent Learning and Reasoning: A Step-Wise, Multi-Dimensional, and Generalist Reward Model with Benchmark
Bingchen Miao, Yang Wu, Minghe Gao et al.
Features are fate: a theory of transfer learning in high-dimensional regression
Javan Tahir, Surya Ganguli, Grant Rotskoff
LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong et al.
LLMScan: Causal Scan for LLM Misbehavior Detection
Mengdi Zhang, Goh Kiat, Peixin Zhang et al.
Models of Heavy-Tailed Mechanistic Universality
Liam Hodgkinson, Zhichao Wang, Michael Mahoney
DEALing with Image Reconstruction: Deep Attentive Least Squares
Mehrsa Pourya, Erich Kobler, Michael Unser et al.
Provably Better Explanations with Optimized Aggregation of Feature Attributions
Thomas Decker, Ananta Bhattarai, Jindong Gu et al.
CSTrack: Enhancing RGB-X Tracking via Compact Spatiotemporal Features
xiaokun Feng, Dailing Zhang, Shiyu Hu et al.
Understanding Synthetic Context Extension via Retrieval Heads
Xinyu Zhao, Fangcong Yin, Greg Durrett
Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets
Wei Liu, Zhongyu Niu, Lang Gao et al.
Don't be so Negative! Score-based Generative Modeling with Oracle-assisted Guidance
Saeid Naderiparizi, Xiaoxuan Liang, Setareh Cohan et al.
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
Simone Bombari, Marco Mondelli
Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning
Vivienne Wang, Tinghuai Wang, wenyan yang et al.
Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
Yulun Wu, Doron Bergman
Optimization without Retraction on the Random Generalized Stiefel Manifold
Simon Vary, Pierre Ablin, Bin Gao et al.
Representing Molecules as Random Walks Over Interpretable Grammars
Michael Sun, Minghao Guo, Weize Yuan et al.
In-Context Denoising with One-Layer Transformers: Connections between Attention and Associative Memory Retrieval
Matthew Smart, Alberto Bietti, Anirvan Sengupta
Active Fine-Tuning of Multi-Task Policies
Marco Bagatella, Jonas Hübotter, Georg Martius et al.
Exploiting Curvature in Online Convex Optimization with Delayed Feedback
Hao Qiu, Emmanuel Esposito, Mengxiao Zhang
Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization
Taeyoung Yun, Kiyoung Om, Jaewoo Lee et al.
Differentially Private Worst-group Risk Minimization
Xinyu Zhou, Raef Bassily
MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost
Sen Xing, Muyan Zhong, Zeqiang Lai et al.
Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold
Tingting Dan, Ziquan Wei, Won Hwa Kim et al.
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss
Sangyeon Park, Isaac Han, Seungwon Oh et al.
Stochastic positional embeddings improve masked image modeling
Amir Bar, Florian Bordes, Assaf Shocher et al.
Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Seojin Kim, Jaehyun Nam, Sihyun Yu et al.
BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference
Wonsuk Jang, Thierry Tambe
Optimal Transport for Structure Learning Under Missing Data
Vy Vo, He Zhao, Trung Le et al.
A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
Guyard Theo, Cédric Herzet, Clément Elvira et al.
Faster Maximum Inner Product Search in High Dimensions
Mo Tiwari, Ryan Kang, Jaeyong Lee et al.
RZ-NAS: Enhancing LLM-guided Neural Architecture Search via Reflective Zero-Cost Strategy
Zipeng Ji, Guanghui Zhu, Chunfeng Yuan et al.
ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans
Ashkan Shahbazi, Elaheh Akbari, Darian Salehi et al.
A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs
Lars Veefkind, Gabriele Cesa
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
Haotian Sun, Yuchen Zhuang, Wei Wei et al.
BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
Susan Liang, Dejan Markovic, Israel D. Gebru et al.
Autonomy-of-Experts Models
Ang Lv, Ruobing Xie, Yining Qian et al.
Synthetic Text Generation for Training Large Language Models via Gradient Matching
Dang Nguyen, Zeman Li, MohammadHossein Bateni et al.
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features
Simone Bombari, Marco Mondelli
Winner-takes-all learners are geometry-aware conditional density estimators
Victor Letzelter, David Perera, Cédric Rommel et al.
TruthFlow: Truthful LLM Generation via Representation Flow Correction
Hanyu Wang, Bochuan Cao, Yuanpu Cao et al.
The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret
Lukas Fluri, Leon Lang, Alessandro Abate et al.
Dynamic Survival Analysis with Controlled Latent States
Linus Bleistein, Van NGUYEN, Adeline Fermanian et al.
ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data
Carmen Martin-Turrero, Maxence Bouvier, Manuel Breitenstein et al.
Residual Matrix Transformers: Scaling the Size of the Residual Stream
Brian Mak, Jeffrey Flanigan
ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance
Liwen Sun, Abhineet Agarwal, Aaron Kornblith et al.
SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression
Mohammad Mozaffari, Amir Yazdanbakhsh, Maryam Mehri Dehnavi
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
Rohan Deb, Kiran Thekumparampil, Kousha Kalantari et al.
Revisiting the Predictability of Performative, Social Events
Juan Perdomo
Towards Trustworthy Federated Learning with Untrusted Participants
Youssef Allouah, Rachid Guerraoui, John Stephan
Understanding and Mitigating Memorization in Diffusion Models for Tabular Data
Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen et al.
Algorithms with Calibrated Machine Learning Predictions
Judy Hanwen Shen, Ellen Vitercik, Anders Wikum
Spherical Rotation Dimension Reduction with Geometric Loss Functions
Hengrui Luo, Jeremy E. Purvis, Didong Li
IOI: Invisible One-Iteration Adversarial Attack on No-Reference Image- and Video-Quality Metrics
Ekaterina Shumitskaya, Anastasia Antsiferova, Dmitriy Vatolin
Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks
Yixin Cheng, Hongcheng Guo, Yangming Li et al.
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)
Dehao Yuan, Cornelia Fermuller, Tahseen Rabbani et al.
Exploring the Complexity of Deep Neural Networks through Functional Equivalence
Guohao Shen
Robust Offline Reinforcement Learning with Linearly Structured $f$-Divergence Regularization
Cheng Tang, Zhishuai Liu, Pan Xu
On Convergence of Incremental Gradient for Non-convex Smooth Functions
Anastasiia Koloskova, Nikita Doikov, Sebastian Stich et al.
On the Power of Context-Enhanced Learning in LLMs
Xingyu Zhu, Abhishek Panigrahi, Sanjeev Arora
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
Chen-Xiao Gao, Chenyang Wu, Mingjun Cao et al.
Provably Scalable Black-Box Variational Inference with Structured Variational Families
Joohwan Ko, Kyurae Kim, Woo Chang Kim et al.
RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts
Tuan Truong, Chau Nguyen, Huy Nguyen et al.