Most Cited NEURIPS "joint probability distribution" Papers
5,858 papers found • Page 11 of 30
Conference
Bigram Subnetworks: Mapping to Next Tokens in Transformer Language Models
Tyler Chang, Benjamin Bergen
SING: SDE Inference via Natural Gradients
Amber Hu, Henry Smith, Scott Linderman
Visual Anagrams Reveal Hidden Differences in Holistic Shape Processing Across Vision Models
Fenil Doshi, Thomas Fel, Talia Konkle et al.
Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning
Lei Wang, Jieming Bian, Letian Zhang et al.
Vision‑Language‑Vision Auto‑Encoder: Scalable Knowledge Distillation from Diffusion Models
Tiezheng Zhang, Yitong Li, Yu-Cheng Chou et al.
MUSTAFAR: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference
Donghyeon Joo, Helya Hosseini, Ramyad Hadidi et al.
LoTA-QAF: Lossless Ternary Adaptation for Quantization-Aware Fine-Tuning
Junyu Chen, Junzhuo Li, Zhen Peng et al.
ClusterFusion: Expanding Operator Fusion Scope for LLM Inference via Cluster-Level Collective Primitive
Xinhao Luo, Zihan Liu, Yangjie Zhou et al.
Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
Itamar Harel, Yonathan Wolanowsky, Gal Vardi et al.
AstroVisBench: A Code Benchmark for Scientific Computing and Visualization in Astronomy
Sebastian Joseph, Syed M. Husain, Stella Offner et al.
Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training
Minhak Song, Beomhan Baek, Kwangjun Ahn et al.
A Provable Approach for End-to-End Safe Reinforcement Learning
Akifumi Wachi, Kohei Miyaguchi, Takumi Tanabe et al.
UniFoil: A Universal Dataset of Airfoils in Transitional and Turbulent Regimes for Subsonic and Transonic Flows
Rohit Kanchi, Benjamin Melanson, Nithin Somasekharan et al.
Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark
Hanlei Zhang, zhuohang li, Hua Xu et al.
metaTextGrad: Automatically optimizing language model optimizers
Guowei Xu, Mert Yuksekgonul, Carlos Guestrin et al.
GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
Yeonjoon Jung, Daehyun Ahn, Hyungjun Kim et al.
Neural Mutual Information Estimation with Vector Copulas
Yanzhi Chen, Zijing Ou, Adrian Weller et al.
One Filters All: A Generalist Filter For State Estimation
Shiqi Liu, Wenhan Cao, Chang Liu et al.
A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging
Sajad Khodadadian, Martin Zubeldia
FlareX: A Physics-Informed Dataset for Lens Flare Removal via 2D Synthesis and 3D Rendering
Lishen Qu, Zhihao Liu, Jinshan Pan et al.
LLM Meets Diffusion: A Hybrid Framework for Crystal Material Generation
Subhojyoti Khastagir, KISHALAY DAS, Pawan Goyal et al.
Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings
Aditya Sengar, Ali Hariri, Daniel Probst et al.
On the Mechanisms of Weak-to-Strong Generalization: A Theoretical Perspective
Behrad Moniri, Hamed Hassani
Sparse Polyak: an adaptive step size rule for high-dimensional M-estimation
Tianqi Qiao, Marie Maros
Resource-Constrained Federated Continual Learning: What Does Matter?
Yichen Li, Yuying Wang, Jiahua Dong et al.
Learning Interactive World Model for Object-Centric Reinforcement Learning
Fan Feng, Phillip Lippe, Sara Magliacane
Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards
Artin Tajdini, Jonathan Scarlett, Kevin Jamieson
REASONING COMPILER: LLM-Guided Optimizations for Efficient Model Serving
Annabelle Sujun Tang, Christopher Priebe, Rohan Mahapatra et al.
Affine-Invariant Global Non-Asymptotic Convergence Analysis of BFGS under Self-Concordance
Qiujiang Jin, Aryan Mokhtari
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
Omri Lev, Vishwak Srinivasan, Moshe Shenfeld et al.
MESS+: Dynamically Learned Inference-Time LLM Routing in Model Zoos with Service Level Guarantees
Herbert Woisetschläger, Ryan Zhang, Shiqiang Wang et al.
Robustness in Both Domains: CLIP Needs a Robust Text Encoder
Elias Abad Rocamora, Christian Schlarmann, Naman Deep Singh et al.
StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training
Ziming Liu, Shaoyu Wang, Shenggan Cheng et al.
Nabla-R2D3: Effective and Efficient 3D Diffusion Alignment with 2D Rewards
Qingming LIU, Zhen Liu, Dinghuai Zhang et al.
Bayes optimal learning of attention-indexed models
Fabrizio Boncoraglio, Emanuele Troiani, Vittorio Erba et al.
Breaking the Performance Ceiling in Reinforcement Learning requires Inference Strategies
Felix Chalumeau, Daniel Rajaonarivonivelomanantsoa, Ruan John de Kock et al.
Can Large Language Models Master Complex Card Games?
Wei Wang, Fuqing Bie, Junzhe Chen et al.
Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework
Thomson Yen, Andrew Siah, Haozhe Chen et al.
Alignment of Large Language Models with Constrained Learning
Botong Zhang, Shuo Li, Ignacio Hounie et al.
A Diffusion Model for Regular Time Series Generation from Irregular Data with Completion and Masking
Gal Fadlon, Idan Arbiv, Nimrod Berman et al.
CellCLIP - Learning Perturbation Effects in Cell Painting via Text-Guided Contrastive Learning
MingYu Lu, Ethan Weinberger, Chanwoo Kim et al.
High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model
Valentin Schmutz, Ali Haydaroğlu, Shuqi Wang et al.
Alchemist: Turning Public Text-to-Image Data into Generative Gold
Valerii Startsev, Alexander Ustyuzhanin, Alexey Kirillov et al.
VisDiff: SDF-Guided Polygon Generation for Visibility Reconstruction, Characterization and Recognition
Rahul Moorthy Mahesh, Jun-Jee Chao, Volkan Isler
msf-CNN: Patch-based Multi-Stage Fusion with Convolutional Neural Networks for TinyML
Zhaolan Huang, Emmanuel Baccelli
Physics-informed Reduced Order Modeling of Time-dependent PDEs via Differentiable Solvers
Nima Hosseini Dashtbayaz, Hesam Salehipour, Adrian Butscher et al.
Diffusion Adaptive Text Embedding for Text-to-Image Diffusion Models
Byeonghu Na, Minsang Park, Gyuwon Sim et al.
Semi-off-Policy Reinforcement Learning for Vision-Language Slow-Thinking Reasoning
Junhao Shen, Haiteng Zhao, Yuzhe Gu et al.
Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality
Alex Fang, Hadi Pouransari, Matt Jordan et al.
Restricted Spectral Gap Decomposition for Simulated Tempering Targeting Mixture Distributions
Jhanvi Garg, Krishnakumar Balasubramanian, Quan Zhou
Path Gradients after Flow Matching
Lorenz Vaitl, Leon Klein
Rethinking Nighttime Image Deraining via Learnable Color Space Transformation
Qiyuan Guan, Xiang Chen, Guiyue Jin et al.
LaX: Boosting Low-Rank Training of Foundation Models via Latent Crossing
Ruijie (Ray) Zhang, Ziyue (Alvin) Liu, Zhengyang Wang et al.
Measuring Fingerprints of Web-filtered Text Datasets and Fingerprint Propagation Through Training
Youssef Mansour, Reinhard Heckel
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
Daolang Huang, Xinyi Wen, Ayush Bharti et al.
MATCH: Multi-faceted Adaptive Topo-Consistency for Semi-Supervised Histopathology Segmentation
Meilong Xu, Xiaoling Hu, Shahira Abousamra et al.
Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning
Amit Peleg, Naman Deep Singh, Matthias Hein
Towards Predicting Any Human Trajectory In Context
Ryo Fujii, Hideo Saito, Ryo Hachiuma
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
Frank Shih, Zhenghao Jiang, Faming Liang
A geometric framework for momentum-based optimizers for low-rank training
Steffen Schotthöfer, Timon Klein, Jonas Kusch
ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals
Jonas Elsborg, Luca Thiede, Alan Aspuru-Guzik et al.
CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
Zhining Liu, Zihao Li, Ze Yang et al.
Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
Li Bai, Qingqing Ye, Xinwei Zhang et al.
Towards Self-Refinement of Vision-Language Models with Triangular Consistency
Yunlong Deng, Guangyi Chen, Tianpei Gu et al.
TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence
Feng Jiang, Mangal Prakash, Hehuan Ma et al.
CURE: Concept Unlearning via Orthogonal Representation Editing in Diffusion Models
Shristi Das Biswas, Arani Roy, Kaushik Roy
Panoptic Captioning: An Equivalence Bridge for Image and Text
Kun-Yu Lin, Hongjun Wang, Weining Ren et al.
BackdoorDM: A Comprehensive Benchmark for Backdoor Learning on Diffusion Model
Weilin Lin, Nanjun Zhou, Yanyun Wang et al.
URB - Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles
Ahmet Onur Akman, Anastasia Psarou, Michał Hoffmann et al.
BikeBench: A Bicycle Design Benchmark for Generative Models with Objectives and Constraints
Lyle Regenwetter, Yazan Abu Obaideh, Fabien Chiotti et al.
Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
Jiani Liu, Zhiyuan Wang, Zeliang Zhang et al.
ExAct: A Video-Language Benchmark for Expert Action Analysis
Han Yi, Yulu Pan, Feihong He et al.
STAR: A Benchmark for Astronomical Star Fields Super-Resolution
WU KUO-CHENG, Guohang Zhuang, Jinyang Huang et al.
Activation-Guided Consensus Merging for Large Language Models
Yuxuan Yao, Shuqi LIU, Zehua Liu et al.
LIFEBENCH: Evaluating Length Instruction Following in Large Language Models
Wei Zhang, Zhenhong Zhou, Kun Wang et al.
Reinforcement Learning Meets Masked Generative Models: Mask-GRPO for Text-to-Image Generation
Yifu Luo, Xinhao Hu, Keyu Fan et al.
DualOptim: Enhancing Efficacy and Stability in Machine Unlearning with Dual Optimizers
Xuyang Zhong, Haochen Luo, Chen Liu
SutureBot: A Precision Framework & Benchmark For Autonomous End-to-End Suturing
Jesse Haworth, Juo-Tung Chen, Nigel Nelson et al.
Hierarchical Frequency Tagging Probe (HFTP): A Unified Approach to Investigate Syntactic Structure Representations in Large Language Models and the Human Brain
Jingmin An, Yilong Song, Ruolin Yang et al.
On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
Anas Barakat, Souradip Chakraborty, Peihong Yu et al.
Predicting partially observable dynamical systems via diffusion models with a multiscale inference scheme
Rudy Morel, Francesco Ramunno, Jeff Shen et al.
SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding
Trung Le, Hao Fang, Jingyuan Li et al.
Beyond Components: Singular Vector-Based Interpretability of Transformer Circuits
Areeb Ahmad, Abhinav Joshi, Ashutosh Modi
Reconstruct, Inpaint, Test-Time Finetune: Dynamic Novel-view Synthesis from Monocular Videos
Kaihua Chen, Tarasha Khurana, Deva Ramanan
BenchmarkCards: Standardized Documentation for Large Language Model Benchmarks
Anna Sokol, Elizabeth Daly, Michael Hind et al.
From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications
Yang Cai, Haipeng Luo, Chen-Yu Wei et al.
MAESTRO : Adaptive Sparse Attention and Robust Learning for Multimodal Dynamic Time Series
Payal Mohapatra, Yueyuan Sui, Akash Pandey et al.
MTBBench: A Multimodal Sequential Clinical Decision-Making Benchmark in Oncology
Kiril Vasilev, Alexandre Misrahi, Eeshaan Jain et al.
Homogeneous Algorithms Can Reduce Competition in Personalized Pricing
Nathanael Jo, Ashia Wilson, Kathleen Creel et al.
PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation
Yanlong Chen, Mattia Orlandi, Pierangelo Rapa et al.
LookWhere? Efficient Visual Recognition by Learning Where to Look and What to See from Self-Supervision
Anthony Fuller, Yousef Yassin, Junfeng Wen et al.
HyPlaneHead: Rethinking Tri-plane-like Representations in Full-Head Image Synthesis
Heyuan Li, Kenkun Liu, Lingteng Qiu et al.
NAUTILUS: A Large Multimodal Model for Underwater Scene Understanding
Wei Xu, Cheng Wang, Dingkang Liang et al.
Evaluating LLM-contaminated Crowdsourcing Data Without Ground Truth
Yichi Zhang, Jinlong Pang, Zhaowei Zhu et al.
Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization
Noémie Bergues, Arthur Carré, Paul Join-Lambert et al.
DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
Antonio Guillen-Perez, Avisek Naug, Vineet Gundecha et al.
Large Language Bayes
Justin Domke
SEAL: Semantic-Aware Hierarchical Learning for Generalized Category Discovery
Zhenqi He, Yuanpei Liu, Kai Han
LooGLE v2: Are LLMs Ready for Real World Long Dependency Challenges?
Ziyuan He, Yuxuan Wang, Jiaqi Li et al.
EngiBench: A Framework for Data-Driven Engineering Design Research
Florian Felten, Gabriel Apaza, Gerhard Bräunlich et al.
Model-Based Policy Adaptation for Closed-Loop End-to-end Autonomous Driving
Haohong Lin, Yunzhi Zhang, Wenhao Ding et al.
Statistical Inference under Performativity
Xiang Li, Yunai Li, Huiying Zhong et al.
System-Embedded Diffusion Bridge Models
Bartlomiej Sobieski, Matthew Tivnan, Yuang Wang et al.
PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning
Xiaogang Jia, Qian Wang, Anrui Wang et al.
GLSim: Detecting Object Hallucinations in LVLMs via Global-Local Similarity
Seongheon Park, Sharon Li
Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts
Andrea Pugnana, Riccardo Massidda, Francesco Giannini et al.
NFL-BA: Near-Field Light Bundle Adjustment for SLAM in Dynamic Lighting
Andrea Dunn Beltran, Daniel Rho, Marc Niethammer et al.
VA-GS: Enhancing the Geometric Representation of Gaussian Splatting via View Alignment
Qing Li, Huifang Feng, Xun Gong et al.
Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
Bryan Wong, Jongwoo Kim, Huazhu Fu et al.
SRHand: Super-Resolving Hand Images and 3D Shapes via View/Pose-aware Neural Image Representations and Explicit Meshes
Minje Kim, Tae-Kyun Kim
Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples
Suqin Yuan, Lei Feng, Bo Han et al.
Reward-Aware Proto-Representations in Reinforcement Learning
Hon Tik Tse, Siddarth Chandrasekar, Marlos C. Machado
Learning Temporal 3D Semantic Scene Completion via Optical Flow Guidance
meng wang, Fan Wu, Ruihui Li et al.
VITRIX-CLIPIN: Enhancing Fine-Grained Visual Understanding in CLIP via Instruction-Editing Data and Long Captions
Ziteng Wang, Siqi Yang, Limeng Qiao et al.
Measuring and Guiding Monosemanticity
Ruben Härle, Felix Friedrich, Manuel Brack et al.
Unifying Proportional Fairness in Centroid and Non-Centroid Clustering
Benjamin Cookson, Nisarg Shah, Ziqi Yu
Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds
Fan Wang, Pengtao Shao, Yiming Zhang et al.
Chirality in Action: Time-Aware Video Representation Learning by Latent Straightening
Piyush Nitin Bagad, Andrew Zisserman
GeoDynamics: A Geometric State‑Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds
Tingting Dan, Jiaqi Ding, Guorong Wu
Posterior Sampling by Combining Diffusion Models with Annealed Langevin Dynamics
Zhiyang Xun, Shivam Gupta, Eric Price
Layer as Puzzle Pieces: Compressing Large Language Models through Layer Concatenation
Fei Wang, Li Shen, Liang Ding et al.
A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation
Etienne Boursier, Scott Pesme, Radu-Alexandru Dragomir
HoPE: Hybrid of Position Embedding for Long Context Vision-Language Models
Haoran Li, Yingjie Qin, Baoyuan Ou et al.
Information Theoretic Learning for Diffusion Models with Warm Start
Yirong Shen, Lu GAN, Cong Ling
Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
Anna van Elst, Igor Colin, Stephan Clémençon
SPARKE: Scalable Prompt-Aware Diversity and Novelty Guidance in Diffusion Models via RKE Score
Mohammad Jalali, Haoyu Lei, Amin Gohari et al.
A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
Fitsum Gaim, Hoyun Song, Huije Lee et al.
Spark Transformer: Reactivating Sparsity in Transformer FFN and Attention
Chong You, Kan Wu, Zhipeng Jia et al.
What's Producible May Not Be Reachable: Measuring the Steerability of Generative Models
Keyon Vafa, Sarah Bentley, Jon Kleinberg et al.
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Richard Suwandi, Feng Yin, Juntao Wang et al.
scMRDR: A scalable and flexible framework for unpaired single-cell multi-omics data integration
Jianle Sun, Chaoqi Liang, Ran Wei et al.
Teaching Language Models to Reason with Tools
Chengpeng Li, Zhengyang Tang, Ziniu Li et al.
MVU-Eval: Towards Multi-Video Understanding Evaluation for Multimodal LLMs
Tianhao Peng, Haochen Wang, Yuanxing Zhang et al.
On the Hardness of Conditional Independence Testing In Practice
Zheng He, Roman Pogodin, Yazhe Li et al.
Edit Less, Achieve More: Dynamic Sparse Neuron Masking for Lifelong Knowledge Editing in LLMs
Jinzhe Liu, Junshu Sun, Shufan Shen et al.
POCO: Scalable Neural Forecasting through Population Conditioning
Yu Duan, Hamza Chaudhry, Misha B Ahrens et al.
Multivariate Latent Recalibration for Conditional Normalizing Flows
Victor Dheur, Souhaib Ben Taieb
Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization
Sebastian Kassing, Simon Weissmann, Leif Döring
AffordBot: 3D Fine-grained Embodied Reasoning via Multimodal Large Language Models
Xinyi Wang, Xun Yang, Yanlong Xu et al.
When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration
Quan Shi, Carlos Jimenez, Shunyu Yao et al.
HMARL-CBF – Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems
H M Sabbir Ahmad, Ehsan Sabouni, Alexander Wasilkoff et al.
FFN Fusion: Rethinking Sequential Computation in Large Language Models
Akhiad Bercovich, Mohammed Dabbah, Omri Puny et al.
A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications
Zhenyu Tao, Wei Xu, Xiaohu You
CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis
Florian Barthel, Wieland Morgenstern, Paul Hinzer et al.
ArchCAD-400K: A Large-Scale CAD drawings Dataset and New Baseline for Panoptic Symbol Spotting
Ruifeng Luo, Zhengjie Liu, Tianxiao Cheng et al.
Compute-Optimal Scaling for Value-Based Deep RL
Preston Fu, Oleh Rybkin, Zhiyuan (Paul) Zhou et al.
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research
A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen et al.
Disentangling Latent Shifts of In-Context Learning with Weak Supervision
Josip Jukić, Jan Šnajder
Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion
Vinh Tong, Trung-Dung Hoang, Anji Liu et al.
Constructing an Optimal Behavior Basis for the Option Keyboard
Lucas N. Alegre, Ana Bazzan, Andre Barreto et al.
Automatic Synthetic Data and Fine-grained Adaptive Feature Alignment for Composed Person Retrieval
Delong Liu, Haiwen Li, Zhaohui Hou et al.
CosmoBench: A Multiscale, Multiview, Multitask Cosmology Benchmark for Geometric Deep Learning
Teresa Huang, Richard Stiskalek, Jun-Young Lee et al.
Increasing the Utility of Synthetic Images through Chamfer Guidance
Nicola Dall'Asen, Xiaofeng Zhang, Reyhane Askari Hemmat et al.
DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos
Chieh Lin, Zhaoyang Lv, Songyin Wu et al.
Exploiting Vocabulary Frequency Imbalance in Language Model Pre-training
Woojin Chung, Jeonghoon Kim
Neural Collapse in Cumulative Link Models for Ordinal Regression: An Analysis with Unconstrained Feature Model
Chuang Ma, Tomoyuki Obuchi, Toshiyuki Tanaka
DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization
Hongshu Guo, Zeyuan Ma, Yining Ma et al.
From Black-box to Causal-box: Towards Building More Interpretable Models
Inwoo Hwang, Yushu Pan, Elias Bareinboim
Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models
William Overman, Mohsen Bayati
Imagined Autocurricula
Ahmet Hamdi Güzel, Matthew T Jackson, Jarek Liesen et al.
Hankel Singular Value Regularization for Highly Compressible State Space Models
Paul Schwerdtner, Jules Berman, Benjamin Peherstorfer
Disentanglement Beyond Static vs. Dynamic: A Benchmark and Evaluation Framework for Multi-Factor Sequential Representations
Tal Barami, Nimrod Berman, Ilan Naiman et al.
Composition and Alignment of Diffusion Models using Constrained Learning
Shervin Khalafi, Ignacio Hounie, Dongsheng Ding et al.
MAP Estimation with Denoisers: Convergence Rates and Guarantees
Scott Pesme, Giacomo Meanti, Michael Arbel et al.
Hawaii: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models
Yimu Wang, Mozhgan Nasr Azadani, Sean Sedwards et al.
Clean First, Align Later: Benchmarking Preference Data Cleaning for Reliable LLM Alignment
Samuel (Min-Hsuan) Yeh, Sharon Li
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning
Zeyuan Liu, Zhihe Yang, Jiawei Xu et al.
A Circular Argument: Does RoPE need to be Equivariant for Vision?
Chase van de Geijn, Timo Lüddecke, Polina Turishcheva et al.
MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models
Hang Hua, Ziyun Zeng, Yizhi Song et al.
Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning
Jiayu Wang, Yifei Ming, Zixuan Ke et al.
CREA: A Collaborative Multi-Agent Framework for Creative Image Editing and Generation
Kavana Venkatesh, Connor Dunlop, Pinar Yanardag
Fair Deepfake Detectors Can Generalize
Harry Cheng, Ming-Hui Liu, Yangyang Guo et al.
Pairwise Calibrated Rewards for Pluralistic Alignment
Daniel Halpern, Evi Micha, Ariel Procaccia et al.
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune, David Vigouroux, Yilun Du et al.
Greedy Algorithms for Structured Bandits: A Sharp Characterization of Asymptotic Success / Failure
Aleksandrs Slivkins, Yunzong Xu, Shiliang Zuo
Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
Longwei Wang, Ifrat Ikhtear Uddin, Prof. KC Santosh (PhD) et al.
ReliabilityRAG: Effective and Provably Robust Defense for RAG-based Web-Search
Zeyu Shen, Basileal Imana, Tong Wu et al.
Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling
Hao Chen, Guanxi Lu, Yasuyuki Okoshi et al.
Scaling Diffusion Transformers Efficiently via $\mu$P
Chenyu Zheng, Xinyu Zhang, Rongzhen Wang et al.
Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool
Jiangtong Li, Dongyi Liu, Kun Zhu et al.
PhySense: Sensor Placement Optimization for Accurate Physics Sensing
Yuezhou Ma, Haixu Wu, Hang Zhou et al.
Probabilistic Token Alignment for Large Language Model Fusion
Runjia Zeng, James Liang, Cheng Han et al.
GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining
Simin Fan, Maria Ios Glarou, Martin Jaggi
Improved Approximation Algorithms for Chromatic and Pseudometric-Weighted Correlation Clustering
Chenglin Fan, Dahoon Lee, Euiwoong Lee
InstaInpaint: Instant 3D-Scene Inpainting with Masked Large Reconstruction Model
Junqi You, Chieh Lin, Weijie Lyu et al.
Blackbox Model Provenance via Palimpsestic Membership Inference
Rohith Kuditipudi, Jing Huang, Sally Zhu et al.
Slow Transition to Low-Dimensional Chaos in Heavy-Tailed Recurrent Neural Networks
Eva Xie, Stefan Mihalas, Łukasz Kuśmierz
EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
Rikuto Kotoge, Zheng Chen, Tasuku Kimura et al.
Demystifying Network Foundation Models
Roman Beltiukov, Satyandra Guthula, Wenbo Guo et al.
MaNGO — Adaptable Graph Network Simulators via Meta-Learning
Philipp Dahlinger, Tai Hoang, Denis Blessing et al.
Taming Hyperparameter Sensitivity in Data Attribution: Practical Selection Without Costly Retraining
Weiyi Wang, Junwei Deng, Yuzheng Hu et al.
Reward Reasoning Models
Jiaxin Guo, Zewen Chi, Li Dong et al.
RAST: Reasoning Activation in LLMs via Small-model Transfer
Siru Ouyang, Xinyu Zhu, Zilin Xiao et al.
AlphaFold Database Debiasing for Robust Inverse Folding
Cheng Tan, Zhenxiao Cao, Zhangyang Gao et al.
Risk-aware Direct Preference Optimization under Nested Risk Measure
Lijun Zhang, Lin Li, Yajie Qi et al.
Unified Reinforcement and Imitation Learning for Vision-Language Models
Byung-Kwan Lee, Ryo Hachiuma, Yong Man Ro et al.
ViSpec: Accelerating Vision-Language Models with Vision-Aware Speculative Decoding
Jialiang Kang, Han Shu, Wenshuo Li et al.
ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training
Adel Nabli, Louis Fournier, Pierre ERBACHER et al.
Differentially Private Gomory-Hu Trees
Anders Aamand, Justin Chen, Mina Dalirrooyfard et al.