Most Cited ICML "flow boiling velocity fields" Papers
5,975 papers found • Page 10 of 30
Conference
Learning Latent Graph Structures and their Uncertainty
Alessandro Manenti, Daniele Zambon, Cesare Alippi
DocVXQA: Context-Aware Visual Explanations for Document Question Answering
Mohamed Ali Souibgui, Changkyu Choi, Andrey Barsky et al.
A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals
Yuanchao Xu, Kaidi Shao, Nikos Logothetis et al.
Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren et al.
Whoever Started the interference Should End It: Guiding Data-Free Model Merging via Task Vectors
Runxi Cheng, Feng Xiong, Yongxian Wei et al.
Towards Cost-Effective Reward Guided Text Generation
Ahmad Rashid, Ruotian Wu, Rongqi Fan et al.
WMAdapter: Adding WaterMark Control to Latent Diffusion Models
Hai Ci, Yiren Song, Pei Yang et al.
Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering
Zihan Song, Xin Wang, Zi Qian et al.
video-SALMONN-o1: Reasoning-enhanced Audio-visual Large Language Model
Guangzhi Sun, Yudong Yang, Jimin Zhuang et al.
An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data
Nikita Lagrange, Herve Isambert
Think Twice, Act Once: A Co-Evolution Framework of LLM and RL for Large-Scale Decision Making
Xu Wan, Wenyue Xu, Chao Yang et al.
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.
Learning to Quantize for Training Vector-Quantized Networks
Peijia Qin, Jianguo Zhang
TuCo: Measuring the Contribution of Fine-Tuning to Individual Responses of LLMs
Felipe Nuti, Tim Franzmeyer, Joao Henriques
Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation
Tiansheng Wen, Yifei Wang, Zequn Zeng et al.
GCAL: Adapting Graph Models to Evolving Domain Shifts
Ziyue Qiao, Qianyi Cai, Hao Dong et al.
MP-Nav: Enhancing Data Poisoning Attacks against Multimodal Learning
Jingfeng Zhang, Prashanth Krishnamurthy, Naman Patel et al.
AAAR-1.0: Assessing AI’s Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang et al.
Position: It Is Time We Test Neural Computation In Vitro
Frithjof Gressmann, Ashley Chen, Lily Xie et al.
KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search
Haoran Luo, Haihong E, Yikai Guo et al.
Position: Graph Matching Systems Deserve Better Benchmarks
Indradyumna Roy, Saswat Meher, Eeshaan Jain et al.
Cross-City Latent Space Alignment for Consistency Region Embedding
Meng Chen, Hongwei Jia, Zechen Li et al.
Position: Iterative Online-Offline Joint Optimization is Needed to Manage Complex LLM Copyright Risks
Yanzhou Pan, Jiayi Chen, Jiamin Chen et al.
Position: We Need Responsible, Application-Driven (RAD) AI Research
Sarah Hartman, Cheng Soon Ong, Julia Powles et al.
Masked Autoencoders Are Effective Tokenizers for Diffusion Models
Hao Chen, Yujin Han, Fangyi Chen et al.
Robust Multimodal Large Language Models Against Modality Conflict
Zongmeng Zhang, Wengang Zhou, Jie Zhao et al.
Meta Optimality for Demographic Parity Constrained Regression via Post-Processing
Kazuto Fukuchi
Scaling Probabilistic Circuits via Monarch Matrices
Honghua Zhang, Meihua Dang, Benjie Wang et al.
Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning
Chi Zhang, Ziying Jia, George Atia et al.
Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms
Kei Sen Fong, Mehul Motani
Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
Tyler Kastner, Mark Rowland, Yunhao Tang et al.
Hidden No More: Attacking and Defending Private Third-Party LLM Inference
Rahul Thomas, Louai Zahran, Erica Choi et al.
Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching
Yuchen Zhang, Tianle Zhang, Kai Wang et al.
Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach
Omar Bennouna, Jiawei Zhang, Saurabh Amin et al.
Model-based Reinforcement Learning for Confounded POMDPs
Mao Hong, Zhengling Qi, Yanxun Xu
Star Attention: Efficient LLM Inference over Long Sequences
Shantanu Acharya, Fei Jia, Boris Ginsburg
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng et al.
Understanding the Logic of Direct Preference Alignment through Logic
Kyle Richardson, Vivek Srikumar, Ashish Sabharwal
InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization
Zhengyang Hu, Song Kang, Qunsong Zeng et al.
Evolving Minds: Logic-Informed Inference from Temporal Action Patterns
Chao Yang, Shuting Cui, Yang Yang et al.
Discovering Environments with XRM
Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim et al.
RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation
Xinnuo Xu, Rachel Lawrence, Kshitij Dubey et al.
Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better
Vicente Balmaseda, Ying Xu, Yixin Cao et al.
Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints
Dapeng Jiang, Xiangzhe Kong, Jiaqi Han et al.
Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations
Yongshuo Zong, Tingyang Yu, Ruchika Chavhan et al.
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability
Jiachen Hu, Rui Ai, Han Zhong et al.
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
Chiraag Kaushik, Ran Liu, Chi-Heng Lin et al.
Active Preference Learning for Large Language Models
William Muldrew, Peter Hayes, Mingtian Zhang et al.
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
Hyunsu Kim, Ye Gon Kim, Hongseok Yang et al.
Position: Why We Must Rethink Empirical Research in Machine Learning
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger et al.
Q-value Regularized Transformer for Offline Reinforcement Learning
Shengchao Hu, Ziqing Fan, Chaoqin Huang et al.
Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints
Yunsheng Tian, Ane Zuniga, Xinwei Zhang et al.
Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation
Xinyi Wang, Alfonso Amayuelas, Kexun Zhang et al.
Steering Protein Language Models
Long-Kai Huang, Rongyi Zhu, Bing He et al.
From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation
Kun Su, Xiulong Liu, Eli Shlizerman
Channel Normalization for Time Series Channel Identification
Seunghan Lee, Taeyoung Park, Kibok Lee
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback
Yufei Wang, Zhanyi Sun, Jesse Zhang et al.
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser
Encodings for Prediction-based Neural Architecture Search
Yash Akhauri, Mohamed Abdelfattah
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
Chengshu Li, Jacky Liang, Andy Zeng et al.
Conditional Common Entropy for Instrumental Variable Testing and Partial Identification
Ziwei Jiang, Murat Kocaoglu
Synthesizing Software Engineering Data in a Test-Driven Manner
Lei Zhang, Jiaxi Yang, Min Yang et al.
Online Matrix Completion: A Collaborative Approach with Hott Items
Dheeraj Baby, Soumyabrata Pal
Hypothesis Testing for Generalized Thurstone Models
Anuran Makur, Japneet Singh
NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction
Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman et al.
Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements
Manwen Liao, Yan Zhu, Weitian Zhang et al.
How Language Model Hallucinations Can Snowball
Muru Zhang, Ofir Press, William Merrill et al.
Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg
Yi Feng, Georgios Piliouras, Xiao Wang
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling
Phong Nguyen, Xinlun Cheng, Shahab Azarfar et al.
Unsupervised Concept Discovery Mitigates Spurious Correlations
Md Rifat Arefin, Yan Zhang, Aristide Baratin et al.
Model Assessment and Selection under Temporal Distribution Shift
Elise Han, Chengpiao Huang, Kaizheng Wang
Deep Neural Cellular Potts Models
Koen Minartz, Tim d'Hondt, Leon Hillmann et al.
Sequential Disentanglement by Extracting Static Information From A Single Sequence Element
Nimrod Berman, Ilan Naiman, Idan Arbiv et al.
Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan et al.
Subgoal-based Demonstration Learning for Formal Theorem Proving
Xueliang Zhao, Wenda Li, Lingpeng Kong
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
Alexander Bienstock, Ujjwal Kumar, Antigoni Polychroniadou
Emergence of In-Context Reinforcement Learning from Noise Distillation
Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin et al.
Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
Ya-Chi Chu, Wenzhi Gao, Yinyu Ye et al.
An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective
Xinyue Chen, Jinfeng Peng, Yuhao Li et al.
Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
Hengquan Guo, Lingkai Zu, Xin Liu
Optimally Improving Cooperative Learning in a Social Setting
Shahrzad Haddadan, Cheng Xin, Jie Gao
MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training
Yang Luo, Zangwei Zheng, Ziheng Qin et al.
On Positivity Condition for Causal Inference
Inwoo Hwang, Yesong Choe, Yeahoon Kwon et al.
Equivariant Polynomial Functional Networks
Thieu Vo, Viet Hoang Tran, Tho Tran Huu et al.
Linguistic Calibration of Long-Form Generations
Neil Band, Xuechen Li, Tengyu Ma et al.
MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
Jeffrey A. Chan-Santiago, praveen tirupattur, Gaurav Kumar Nayak et al.
Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers
Katherine Crowson, Stefan Baumann, Alex Birch et al.
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr et al.
A Tale of Tails: Model Collapse as a Change of Scaling Laws
Elvis Dohmatob, Yunzhen Feng, Pu Yang et al.
Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment
Xingyu Zhou, Yulian Wu, Wenqian Weng et al.
Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory
Kai Xu, Hong Ge
Gridded Transformer Neural Processes for Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.
On The Fairness Impacts of Hardware Selection in Machine Learning
Sree Harsha Nelaturu, Nishaanth Kanna, Cuong Tran et al.
ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning
Wei Xiao, Johnson Tsun-Hsuan Wang, Chuang Gan et al.
A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity
Andrew Lee, Xiaoyan Bai, Itamar Pres et al.
Scaling Sparse Feature Circuits For Studying In-Context Learning
Dmitrii Kharlapenko, Stepan Shabalin, Arthur Conmy et al.
Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants
Isabel Chien, Wessel Bruinsma, Javier Gonzalez 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.
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds
Ben Chugg, Hongjian Wang, Aaditya Ramdas
RankSEG: A Consistent Ranking-based Framework for Segmentation
Ben Dai, Chunlin Li
PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency
Yeonsung Jung, Heecheol Yun, Joonhyung Park et al.
Towards Better-than-2 Approximation for Constrained Correlation Clustering
Andreas Kalavas, Evangelos Kipouridis, Nithin Varma
Learning to Continually Learn with the Bayesian Principle
Soochan Lee, Hyeonseong Jeon, Jaehyeon Son et al.
Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models
Xingyu Chen, Jiahao Xu, Tian Liang et al.
Repoformer: Selective Retrieval for Repository-Level Code Completion
Di Wu, Wasi Ahmad, Dejiao Zhang et al.
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
Haonan Yuan, Qingyun Sun, Junhua Shi et al.
On the Generalization of Stochastic Gradient Descent with Momentum
Ali Ramezani-Kebrya, Kimon Antonakopoulos, Volkan Cevher et al.
Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
Tao Li, Zhengbao He, Yujun Li et al.
Leveraging Attractor Dynamics in Spatial Navigation for Better Language Parsing
Xiaolong Zou, Xingxing Cao, Xiaojiao Yang et al.
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
SqueezeLLM: Dense-and-Sparse Quantization
Sehoon Kim, Coleman Hooper, Amir Gholaminejad et al.
In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Shen et al.
An LLM Compiler for Parallel Function Calling
Sehoon Kim, Suhong Moon, Ryan Tabrizi et al.
Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity
Qiuhao Wang, Yuqi Zha, Chin Pang Ho et al.
Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach
Weijia Zhang, Chenlong Yin, Hao Liu et al.
IT$^3$: Idempotent Test-Time Training
Nikita Durasov, Assaf Shocher, Doruk Oner et al.
An Intrinsic Vector Heat Network
Alexander Gao, Maurice Chu, Mubbasir Kapadia et al.
When and How Does CLIP Enable Domain and Compositional Generalization?
Elias Kempf, Simon Schrodi, Max Argus et al.
Enabling Uncertainty Estimation in Iterative Neural Networks
Nikita Durasov, Doruk Oner, Jonathan Donier et al.
MultiMax: Sparse and Multi-Modal Attention Learning
Yuxuan Zhou, Mario Fritz, Margret Keuper
Improving Neural Additive Models with Bayesian Principles
Kouroche Bouchiat, Alexander Immer, Hugo Yèche et al.
Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms
Sho Takemori, Yuhei Umeda, Aditya Gopalan
Implicit meta-learning may lead language models to trust more reliable sources
Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Mlodozeniec et al.
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jimenez Gutierrez, Yiheng Shu, Weijian Qi et al.
Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration
Xiaole Tang, Hu Xin, Xiang Gu et al.
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan et al.
Total Variation Distance Meets Probabilistic Inference
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel et al.
The Underlying Universal Statistical Structure of Natural Datasets
Noam Levi, Yaron Oz
An Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization
Emre Sahinoglu, Shahin Shahrampour
xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
Maximilian Beck, Korbinian Pöppel, Phillip Lippe et al.
Online Cascade Learning for Efficient Inference over Streams
Lunyiu Nie, Zhimin Ding, Erdong Hu et al.
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang et al.
Robustness of Nonlinear Representation Learning
Simon Buchholz, Bernhard Schölkopf
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong et al.
A Dynamical Model of Neural Scaling Laws
Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
Adaptively Perturbed Mirror Descent for Learning in Games
Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto et al.
InfAlign: Inference-aware language model alignment
Ananth Balashankar, Ziteng Sun, Jonathan Berant et al.
FrameQuant: Flexible Low-Bit Quantization for Transformers
Harshavardhan Adepu, Zhanpeng Zeng, Li Zhang et al.
Optimal Coresets for Low-Dimensional Geometric Median
Peyman Afshani, Chris Schwiegelshohn
Learning to Play Atari in a World of Tokens
Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou
Towards Memorization Estimation: Fast, Formal and Free
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
How to Escape Sharp Minima with Random Perturbations
Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra
Not All Wrong is Bad: Using Adversarial Examples for Unlearning
Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran
Nonlinear Filtering with Brenier Optimal Transport Maps
Mohammad Al-Jarrah, Niyizhen Jin, Bamdad Hosseini et al.
UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design
Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.
No Dimensional Sampling Coresets for Classification
Meysam Alishahi, Jeff Phillips
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani et al.
Hyperbolic Optimizer as a Dynamical System
Nico Alvarado, Hans Lobel
LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin et al.
Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised Learning
Konstantinos Ameranis, Adela DePavia, Lorenzo Orecchia et al.
Multi-band Frequency Reconstruction for Neural Psychoacoustic Coding
Dianwen Ng, Kun Zhou, Yi-Wen Chao et al.
Adaptive Hierarchical Certification for Segmentation using Randomized Smoothing
Alaa Anani, Tobias Lorenz, Bernt Schiele et al.
Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts
Jiahai Feng, Stuart Russell, Jacob Steinhardt
Causal Action Influence Aware Counterfactual Data Augmentation
Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica et al.
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
Hilal Asi, Vitaly Feldman, Jelani Nelson et al.
How Free is Parameter-Free Stochastic Optimization?
Amit Attia, Tomer Koren
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Xinyu Yang, Tom Zollo, Benjamin Eyre et al.
Simulation of Graph Algorithms with Looped Transformers
Artur Back de Luca, Kimon Fountoulakis
Disparate Conditional Prediction in Multiclass Classifiers
Sivan Sabato, Eran Treister, Elad Yom-Tov
Constrained Ensemble Exploration for Unsupervised Skill Discovery
Chenjia Bai, Rushuai Yang, Qiaosheng Zhang et al.
BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
Haozhao Wang, Shengyu Wang, Jiaming Li et al.
VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees
Anahita Baninajjar, Ahmed Rezine, Amir Aminifar
Monotone Individual Fairness
Yahav Bechavod
Standardized Interpretable Fairness Measures for Continuous Risk Scores
Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann
Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization
Peiyan Zhang, Haibo Jin, Leyang Hu et al.
Direct Prediction Set Minimization via Bilevel Conformal Classifier Training
Yuanjie Shi, Hooman Shahrokhi, Xuesong Jia et al.
Contour Integration Underlies Human-Like Vision
Ben Lonnqvist, Elsa Scialom, Abdulkadir Gokce et al.
By Tying Embeddings You Are Assuming the Distributional Hypothesis
Bertolotti Francesco, Walter Cazzola
HEAP: Hyper Extended A-PDHG Operator for Constrained High-dim PDEs
Mingquan Feng, Weixin Liao, Yixin Huang et al.
Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation
Luca Beurer-Kellner, Marc Fischer, Martin Vechev
Feature Importance Metrics in the Presence of Missing Data
Henrik von Kleist, Joshua Wendland, Ilya Shpitser et al.
Why do Variational Autoencoders Really Promote Disentanglement?
Pratik Bhowal, Achint Soni, Sirisha Rambhatla
Improving Transformer World Models for Data-Efficient RL
Antoine Dedieu, Joseph Ortiz, Xinghua Lou et al.
WildChat-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Benjamin Feuer, Chinmay Hegde
DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts
Tobias Braun, Mark Rothermel, Marcus Rohrbach et al.
Dynamic Survival Analysis with Controlled Latent States
Linus Bleistein, Van NGUYEN, Adeline Fermanian et al.
UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
Fangchen Yu, Yanzhen Chen, Jiaxing Wei et al.
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features
Simone Bombari, Marco Mondelli
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
Alessio Russo, Aldo Pacchiano
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans et al.
Positive-unlabeled AUC Maximization under Covariate Shift
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi et al.
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee et al.
Differentially Private Bias-Term Fine-tuning of Foundation Models
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha et al.
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
Gon Buzaglo, Itamar Harel, Mor Shpigel Nacson et al.
Rethinking Score Distilling Sampling for 3D Editing and Generation
Xingyu Miao, Haoran Duan, Yang Long et al.
Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation
Lincan Cai, Shuang Li, Wenxuan Ma et al.
Upcycling Text-to-Image Diffusion Models for Multi-Task Capabilities
Ruchika Chavhan, Abhinav Mehrotra, Malcolm Chadwick et al.
Sample-specific Masks for Visual Reprogramming-based Prompting
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Implicit degree bias in the link prediction task
Rachith Aiyappa, Xin Wang, Munjung Kim et al.
AI Alignment with Changing and Influenceable Reward Functions
Micah Carroll, Davis Foote, Anand Siththaranjan et al.
Ergodic Generative Flows
Leo Brunswic, Mateo Clémente, Rui Heng Yang et al.
Simple Ingredients for Offline Reinforcement Learning
Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta et al.
Reinforcement Learning with Segment Feedback
Yihan Du, Anna Winnicki, Gal Dalal et al.
Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation
Guiyang Chan, Pengcheng Zhang, Hai Dong et al.
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
Serina Chang, Frederic Koehler, Zhaonan Qu et al.
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen, Yatao Bian, Bo Han et al.
Auditing Prompt Caching in Language Model APIs
Chenchen Gu, Xiang Li, Rohith Kuditipudi et al.
$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng et al.