Most Cited NEURIPS "human-in-the-loop interactions" Papers
5,858 papers found • Page 7 of 30
Conference
Constrained Diffusers for Safe Planning and Control
Jichen Zhang, Liqun Zhao, Antonis Papachristodoulou et al.
Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness–Generalization Perspective
Ming Gu, Zhuonan Zheng, Sheng Zhou et al.
Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?
Yiwei Yang, Chung Peng Lee, Shangbin Feng et al.
Differentiation Through Black-Box Quadratic Programming Solvers
Connor Magoon, Fengyu Yang, Noam Aigerman et al.
TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration
Yuwei Du, Jie Feng, Jie Zhao et al.
ODG: Occupancy Prediction Using Dual Gaussians
Yunxiao Shi, Yinhao Zhu, Herbert Cai et al.
GeneMAN: Generalizable Single-Image 3D Human Reconstruction from Multi-Source Human Data
Wentao Wang, Hang Ye, Fangzhou Hong et al.
CoT-lized Diffusion: Let's Reinforce T2I Generation Step-by-step
Zheyuan Liu, Munan Ning, Qihui Zhang et al.
Self-Refining Language Model Anonymizers via Adversarial Distillation
Kyuyoung Kim, Hyunjun Jeon, Jinwoo Shin
STEER-ME: Assessing the Microeconomic Reasoning of Large Language Models
Narun Raman, Taylor Lundy, Thiago Amin et al.
Efficient Policy Optimization in Robust Constrained MDPs with Iteration Complexity Guarantees
Sourav Ganguly, Kishan Panaganti, Arnob Ghosh et al.
On the Coexistence and Ensembling of Watermarks
Aleksandar Petrov, Shruti Agarwal, Philip Torr et al.
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset
Zirui Wang, Wenjing Bian, Xinghui Li et al.
Polar Sparsity: High Throughput Batched LLM Inferencing with Scalable Contextual Sparsity
Susav Shrestha, Bradley Settlemyer, Nikoli Dryden et al.
LLM-Driven Treatment Effect Estimation Under Inference Time Text Confounding
Yuchen Ma, Dennis Frauen, Jonas Schweisthal et al.
Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao et al.
Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models
Charvi Rastogi, Tian Huey Teh, Pushkar Mishra et al.
LiteReality: Graphic-Ready 3D Scene Reconstruction from RGB-D Scans
Zhening Huang, Xiaoyang Wu, Fangcheng Zhong et al.
RLZero: Direct Policy Inference from Language Without In-Domain Supervision
Harshit Sushil Sikchi, Siddhant Agarwal, Pranaya Jajoo et al.
AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees
Hongyi Zhou, Jin Zhu, Pingfan Su et al.
Anti-Aliased 2D Gaussian Splatting
Mae Younes, Adnane Boukhayma
Evaluating multiple models using labeled and unlabeled data
Divya Shanmugam, Shuvom Sadhuka, Manish Raghavan et al.
Reinforcement Learning for Out-of-Distribution Reasoning in LLMs: An Empirical Study on Diagnosis-Related Group Coding
Hanyin Wang, Zhenbang Wu, Gururaj Kolar et al.
Who You Are Matters: Bridging Interests and Social Roles via LLM-Enhanced Logic Recommendation
Qing Yu, Xiaobei Wang, Shuchang Liu et al.
CAPability: A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughness
Zhihang Liu, Chen-Wei Xie, Bin Wen et al.
EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving
Shihan Dou, Ming Zhang, Chenhao Huang et al.
Stable Part Diffusion 4D: Multi-View RGB and Kinematic Parts Video Generation
Hao Zhang, Chun-Han Yao, Simon Donné et al.
SViMo: Synchronized Diffusion for Video and Motion Generation in Hand-object Interaction Scenarios
Lingwei Dang, Ruizhi Shao, Hongwen Zhang et al.
Entropic Time Schedulers for Generative Diffusion Models
Dejan Stancevic, Florian Handke, Luca Ambrogioni
InvFusion: Bridging Supervised and Zero-shot Diffusion for Inverse Problems
Noam Elata, Hyungjin Chung, Jong Chul Ye et al.
SMMILE: An expert-driven benchmark for multimodal medical in-context learning
Melanie Rieff, Maya Varma, Ossian Rabow et al.
Memory-Enhanced Neural Solvers for Routing Problems
Felix Chalumeau, Refiloe Shabe, Noah De Nicola et al.
MMMG: A Massive, Multidisciplinary, Multi-Tier Generation Benchmark for Text-to-Image Reasoning
Yuxuan Luo, Ryan Yuan, Junwen Chen et al.
Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality
Alex Fang, Hadi Pouransari, Matt Jordan et al.
Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models
Jiaqi Cao, Jiarui Wang, Rubin Wei et al.
A Theory for Worst-Case vs. Average-Case Guarantees for LLMs
Noga Amit, Shafi Goldwasser, Orr Paradise et al.
PartNeXt: A Next-Generation Dataset for Fine-Grained and Hierarchical 3D Part Understanding
Penghao Wang, Yiyang He, Xin Lv et al.
LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agents
Rui Li, Zixuan Hu, Wenxi Qu et al.
A Partition Cover Approach to Tokenization
Jia Peng Lim, Shawn Tan, XianJun, Davin Choo et al.
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune, David Vigouroux, Yilun Du et al.
Orientation-anchored Hyper-Gaussian for 4D Reconstruction from Casual Videos
Junyi Wu, Jiachen Tao, Haoxuan Wang et al.
DAMamba: Vision State Space Model with Dynamic Adaptive Scan
Tanzhe Li, Caoshuo Li, Jiayi Lyu et al.
Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models
zhentao he, Can Zhang, Ziheng Wu et al.
AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners
Reiss Koh, Wonbeen Oh, Jaein Jang et al.
Seg2Any: Open-set Segmentation-Mask-to-Image Generation with Precise Shape and Semantic Control
Danfeng Li, Hui Zhang, Sheng Wang et al.
NOBLE - Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models
Luca Ghafourpour, Valentin Duruisseaux, Bahareh Tolooshams et al.
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Richard Suwandi, Feng Yin, Juntao Wang et al.
Option-aware Temporally Abstracted Value for Offline Goal-Conditioned Reinforcement Learning
Hongjoon Ahn, Heewoong Choi, Jisu Han et al.
Inference-Time Reward Hacking in Large Language Models
Hadi Khalaf, Claudio Mayrink Verdun, Alex Oesterling et al.
SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
Reda Marzouk, Shahaf Bassan, Guy Katz
Fast Monte Carlo Tree Diffusion: 100× Speedup via Parallel and Sparse Planning
Jaesik Yoon, Hyeonseo Cho, Yoshua Bengio et al.
FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees
Hoang Nguyen, Priya Donti
Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approach
Swetha Ganesh, Vaneet Aggarwal
Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems
Jongyeong Lee, Junya Honda, Shinji Ito et al.
FACE: Faithful Automatic Concept Extraction
Dipkamal Bhusal, Michael Clifford, Sara Rampazzi 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.
Scaling Image Geo-Localization to Continent Level
Philipp Lindenberger, Paul-Edouard Sarlin, Jan Hosang et al.
Plasticity as the Mirror of Empowerment
David Abel, Michael Bowling, Andre Barreto et al.
A2Seek: Towards Reasoning-Centric Benchmark for Aerial Anomaly Understanding
Mengjingcheng Mo, Xinyang Tong, Mingpi Tan et al.
Anytime-valid, Bayes-assisted, Prediction-Powered Inference
Valentin Kilian, Stefano Cortinovis, Francois Caron
Neural-Driven Image Editing
Pengfei Zhou, Jie Xia, Xiaopeng Peng et al.
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation
Enshu Liu, Qian Chen, Xuefei Ning et al.
Block Coordinate Descent for Neural Networks Provably Finds Global Minima
Shunta Akiyama
See through the Dark: Learning Illumination-affined Representations for Nighttime Occupancy Prediction
Yuan Wu, Zhiqiang Yan, Yigong Zhang et al.
Exploring the Noise Robustness of Online Conformal Prediction
HuaJun Xi, Kangdao Liu, Hao Zeng et al.
Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards
Artin Tajdini, Jonathan Scarlett, Kevin Jamieson
PT-MoE: An Efficient Finetuning Framework for Integrating Mixture-of-Experts into Prompt Tuning
Zongqian Li, Yixuan Su, Nigel Collier
Generalized Linear Bandits: Almost Optimal Regret with One-Pass Update
Yu-Jie Zhang, Sheng-An Xu, Peng Zhao et al.
Guard Me If You Know Me: Protecting Specific Face-Identity from Deepfakes
Kaiqing Lin, Zhiyuan Yan, Ke-Yue Zhang et al.
Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning
Amit Peleg, Naman Deep Singh, Matthias Hein
Robust Transfer Learning with Unreliable Source Data
Jianqing Fan, Cheng Gao, Jason Klusowski
Towards Predicting Any Human Trajectory In Context
Ryo Fujii, Hideo Saito, Ryo Hachiuma
CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting
Kornel Howil, Joanna Waczynska, Piotr Borycki et al.
TCM-Ladder: A Benchmark for Multimodal Question Answering on Traditional Chinese Medicine
Jiacheng Xie, Yang Yu, Ziyang Zhang et al.
GradMetaNet: An Equivariant Architecture for Learning on Gradients
Yoav Gelberg, Yam Eitan, Aviv Navon et al.
Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving
Xuan Chen, Shiwei Feng, Zikang Xiong et al.
RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skills
Chunru Lin, Haotian Yuan, Yian Wang et al.
Stable Matching with Ties: Approximation Ratios and Learning
Shiyun Lin, Simon Mauras, Nadav Merlis et al.
Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry
Antoine Collas, Ce Ju, Nicolas Salvy et al.
Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable
Bicheng Ying, Zhe Li, Haibo Yang
SparseDiT: Token Sparsification for Efficient Diffusion Transformer
Shuning Chang, Pichao WANG, Jiasheng Tang et al.
Tail-Optimized Caching for LLM Inference
Wenxin Zhang, Yueying Li, Ciamac C Moallemi et al.
AttentionPredictor: Temporal Patterns Matter for KV Cache Compression
Qingyue Yang, Jie Wang, Xing Li et al.
The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements
Bingchen Zhao, Despoina Magka, Minqi Jiang et al.
Conformal Information Pursuit for Interactively Guiding Large Language Models
Kwan Ho Ryan Chan, Yuyan Ge, Edgar Dobriban et al.
MoPFormer: Motion-Primitive Transformer for Wearable-Sensor Activity Recognition
Hao Zhang, Zhan Zhuang, Xuehao Wang et al.
Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion
Vinh Tong, Trung-Dung Hoang, Anji Liu et al.
RADAR: Benchmarking Language Models on Imperfect Tabular Data
Ken Gu, Zhihan Zhang, Kate Lin et al.
ROGR: Relightable 3D Objects using Generative Relighting
Jiapeng Tang, Matthew Levine, Dor Verbin et al.
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
Shaocong Ma, Heng Huang
Generalizing while preserving monotonicity in comparison-based preference learning models
Julien Fageot, Peva Blanchard, Gilles Bareilles et al.
Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli et al.
Towards Unsupervised Domain Bridging via Image Degradation in Semantic Segmentation
Wangkai Li, Rui Sun, Huayu Mai et al.
Learning to cluster neuronal function
Nina Nellen, Polina Turishcheva, Michaela Vystrčilová et al.
Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation
Xinghao Wu, Xuefeng Liu, Jianwei Niu et al.
FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
Seanie Lee, Sangwoo Park, Dong Bok Lee et al.
Lost in Transmission: When and Why LLMs Fail to Reason Globally
Tobias Schnabel, Kiran Tomlinson, Adith Swaminathan et al.
Uni-LoRA: One Vector is All You Need
Kaiyang Li, Shaobo Han, Qing Su et al.
Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
Runyu Lu, Peng Zhang, Ruochuan Shi et al.
Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing
Yisong Xiao, Aishan Liu, Siyuan Liang et al.
CALM-PDE: Continuous and Adaptive Convolutions for Latent Space Modeling of Time-dependent PDEs
Jan Hagnberger, Daniel Musekamp, Mathias Niepert
Purifying Approximate Differential Privacy with Randomized Post-processing
Yingyu Lin, Erchi Wang, Yian Ma et al.
MoE-Gyro: Self-Supervised Over-Range Reconstruction and Denoising for MEMS Gyroscopes
Feiyang Pan, Shenghe Zheng, Chunyan Yin et al.
Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
Longwei Wang, Ifrat Ikhtear Uddin, Prof. KC Santosh (PhD) et al.
Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning
Haolin Yang, Hakaze Cho, Yiqiao Zhong et al.
Generative Graph Pattern Machine
Zehong Wang, Zheyuan Zhang, Tianyi Ma et al.
KL Penalty Control via Perturbation for Direct Preference Optimization
Sangkyu Lee, Janghoon Han, Hosung Song et al.
Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
Kehan Long, Jorge Cortes, Nikolay Atanasov
Set-LLM: A Permutation-Invariant LLM
Beni Egressy, Jan Stühmer
High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model
Valentin Schmutz, Ali Haydaroğlu, Shuqi Wang et al.
Measuring Fingerprints of Web-filtered Text Datasets and Fingerprint Propagation Through Training
Youssef Mansour, Reinhard Heckel
A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging
Sajad Khodadadian, Martin Zubeldia
AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing
Sam Bright-Thonney, Christina Reissel, Gaia Grosso et al.
Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
Hongyi Henry Jin, Zijun Ding, Dung Daniel Ngo et al.
Head Pursuit: Probing Attention Specialization in Multimodal Transformers
Lorenzo Basile, Valentino Maiorca, Diego Doimo et al.
Rethinking Tokenized Graph Transformers for Node Classification
Jinsong Chen, Chenyang Li, Gaichao Li et al.
Availability-aware Sensor Fusion via Unified Canonical Space
Dong-Hee Paek, SEUNG-HYUN KONG
A geometric framework for momentum-based optimizers for low-rank training
Steffen Schotthöfer, Timon Klein, Jonas Kusch
Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
Itamar Harel, Yonathan Wolanowsky, Gal Vardi et al.
Brain Harmony: A Multimodal Foundation Model Unifying Morphology and Function into 1D Tokens
Zijian Dong, Ruilin Li, Joanna Chong et al.
STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds
Yinfang Chen, Jiaqi Pan, Jackson Clark et al.
An Analysis of Concept Bottleneck Models: Measuring, Understanding, and Mitigating the Impact of Noisy Annotations
Seonghwan Park, Jueun Mun, Donghyun Oh et al.
Concerto: Joint 2D-3D Self-Supervised Learning Emerges Spatial Representations
Yujia Zhang, Xiaoyang Wu, Yixing Lao et al.
Emergent Risk Awareness in Rational Agents under Resource Constraints
Daniel Jarne Ornia, Nicholas Bishop, Joel Dyer et al.
BackdoorDM: A Comprehensive Benchmark for Backdoor Learning on Diffusion Model
Weilin Lin, Nanjun Zhou, Yanyun Wang et al.
Reparameterized LLM Training via Orthogonal Equivalence Transformation
Zeju Qiu, Simon Buchholz, Tim Xiao 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.
Contrastive Self-Supervised Learning As Neural Manifold Packing
Guanming Zhang, David Heeger, Stefano Martiniani
Auto-Compressing Networks
Evangelos Dorovatas, Georgios Paraskevopoulos, Alexandros Potamianos
Low Rank Gradients and Where to Find Them
Rishi Sonthalia, Michael Murray, Guido Montufar
Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization
Sunay Joshi, Shayan Kiyani, George J. Pappas et al.
Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts
Andrea Pugnana, Riccardo Massidda, Francesco Giannini et al.
Latent Mixture of Symmetries for Sample-Efficient Dynamic Learning
Haoran Li, CHENHAN XIAO, Muhao Guo et al.
SimSort: A Data-Driven Framework for Spike Sorting by Large-Scale Electrophysiology Simulation
Yimu Zhang, Dongqi Han, Yansen Wang et al.
Streaming Attention Approximation via Discrepancy Theory
Ekaterina Kochetkova, Kshiteej Jitesh Sheth, Insu Han et al.
Hamiltonian Descent Algorithms for Optimization: Accelerated Rates via Randomized Integration Time
Qiang Fu, Andre Wibisono
Adaptive Prediction-Powered AutoEval with Reliability and Efficiency Guarantees
Sangwoo Park, Matteo Zecchin, Osvaldo Simeone
Data Fusion for Partial Identification of Causal Effects
Quinn Lanners, Cynthia Rudin, Alexander Volfovsky et al.
Can Large Language Models Master Complex Card Games?
Wei Wang, Fuqing Bie, Junzhe Chen et al.
Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Linear Extrapolation
Jiawei Zhang, Ziyuan Liu, Leon Yan et al.
scMRDR: A scalable and flexible framework for unpaired single-cell multi-omics data integration
Jianle Sun, Chaoqi Liang, Ran Wei et al.
MultiHuman-Testbench: Benchmarking Image Generation for Multiple Humans
Shubhankar Borse, Seokeon Choi, Sunghyun Park et al.
On the creation of narrow AI: hierarchy and nonlocality of neural network skills
Eric Michaud, Asher Parker-Sartori, Max Tegmark
Restricted Spectral Gap Decomposition for Simulated Tempering Targeting Mixture Distributions
Jhanvi Garg, Krishnakumar Balasubramanian, Quan Zhou
Efficient Multimodal Dataset Distillation via Generative Models
Zhenghao Zhao, Haoxuan Wang, Junyi Wu et al.
Quantifying Cross-Modality Memorization in Vision-Language Models
Yuxin Wen, Yangsibo Huang, Tom Goldstein et al.
MUSTAFAR: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference
Donghyeon Joo, Helya Hosseini, Ramyad Hadidi et al.
Fair Deepfake Detectors Can Generalize
Harry Cheng, Ming-Hui Liu, Yangyang Guo et al.
Imagined Autocurricula
Ahmet Hamdi Güzel, Matthew T Jackson, Jarek Liesen et al.
Reinforced Context Order Recovery for Adaptive Reasoning and Planning
Long Ma, Fangwei Zhong, Yizhou Wang
DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly Detection
Yingli Shen, Wen Lai, Shuo Wang et al.
Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization
Yu Huang, Zixin Wen, Aarti Singh et al.
Large Language Bayes
Justin Domke
FLOWING: Implicit Neural Flows for Structure-Preserving Morphing
Arthur Bizzi, Matias Grynberg Portnoy, Vitor Pereira Matias et al.
Demystifying Network Foundation Models
Roman Beltiukov, Satyandra Guthula, Wenbo Guo et al.
Failure Prediction at Runtime for Generative Robot Policies
Ralf Römer, Adrian Kobras, Luca Worbis et al.
Shallow Diffuse: Robust and Invisible Watermarking through Low-Dim Subspaces in Diffusion Models
Wenda Li, Huijie Zhang, Qing Qu
TRAP: Targeted Redirecting of Agentic Preferences
Hangoo Kang, Jehyeok Yeon, Gagandeep Singh
OpenWorldSAM: Extending SAM2 for Universal Image Segmentation with Language Prompts
Shiting (Ginny) Xiao, Rishabh Kabra, Yuhang Li et al.
SynBrain: Enhancing Visual-to-fMRI Synthesis via Probabilistic Representation Learning
Weijian Mai, Jiamin Wu, Yu Zhu et al.
Continuous Simplicial Neural Networks
Aref Einizade, Dorina Thanou, Fragkiskos Malliaros et al.
Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
Bryan Wong, Jongwoo Kim, Huazhu Fu et al.
Universal Causal Inference in a Topos
Sridhar Mahadevan
Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data
Dennis Frauen, Maresa Schröder, Konstantin Hess et al.
Logical Expressiveness of Graph Neural Networks with Hierarchical Node Individualization
Arie Soeteman, Balder ten Cate
VisDiff: SDF-Guided Polygon Generation for Visibility Reconstruction, Characterization and Recognition
Rahul Moorthy Mahesh, Jun-Jee Chao, Volkan Isler
What's Producible May Not Be Reachable: Measuring the Steerability of Generative Models
Keyon Vafa, Sarah Bentley, Jon Kleinberg et al.
ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints
Rui Xu, Dakuan Lu, Zicheng Zhao et al.
Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
Subhojyoti Mukherjee, Viet Lai, Raghavendra Addanki et al.
A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
Fitsum Gaim, Hoyun Song, Huije Lee et al.
ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training
Adel Nabli, Louis Fournier, Pierre ERBACHER et al.
SAS: Simulated Attention Score
Chuanyang Zheng, Jiankai Sun, Yihang Gao et al.
Many LLMs Are More Utilitarian Than One
Anita Keshmirian, Razan Baltaji, Babak Hemmatian et al.
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference
Wenxuan Zeng, Ye Dong, Jinjin Zhou et al.
AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark
Aruna Gauba, Irene Pi, Yunze Man et al.
Solver-Free Decision-Focused Learning for Linear Optimization Problems
Senne Berden, Ali Mahmutoğulları, Dimos Tsouros et al.
GeoDynamics: A Geometric State‑Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds
Tingting Dan, Jiaqi Ding, Guorong Wu
Common Task Framework For a Critical Evaluation of Scientific Machine Learning Algorithms
Philippe Wyder, Judah Goldfeder, Alexey Yermakov et al.
SkyLadder: Better and Faster Pretraining via Context Window Scheduling
Tongyao Zhu, Qian Liu, Haonan Wang et al.
A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications
Zhenyu Tao, Wei Xu, Xiaohu You
Optimism Without Regularization: Constant Regret in Zero-Sum Games
John Lazarsfeld, Georgios Piliouras, Ryann Sim et al.
Evaluating LLM-contaminated Crowdsourcing Data Without Ground Truth
Yichi Zhang, Jinlong Pang, Zhaowei Zhu et al.
From Linear to Nonlinear: Provable Weak-to-Strong Generalization through Feature Learning
Junsoo Oh, Jerry Song, Chulhee Yun
FFN Fusion: Rethinking Sequential Computation in Large Language Models
Akhiad Bercovich, Mohammed Dabbah, Omri Puny et al.
Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum
Snir Hordan, Maya Bechler-Speicher, Gur Lifshitz 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.
Contrastive Representations for Temporal Reasoning
Alicja Ziarko, Michał Bortkiewicz, Michał Zawalski et al.
Model-Based Policy Adaptation for Closed-Loop End-to-end Autonomous Driving
Haohong Lin, Yunzhi Zhang, Wenhao Ding et al.
Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning
Tianyi Bai, Yuxuan Fan, Qiu Jiantao et al.
Convolution Goes Higher-Order: A Biologically Inspired Mechanism Empowers Image Classification
Simone Azeglio, Olivier Marre, Peter Neri et al.
Representation Consistency for Accurate and Coherent LLM Answer Aggregation
Junqi Jiang, Tom Bewley, Salim I. Amoukou 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
Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search
Yousef Al-Jazzazi, Haya Diwan, Jinrui Gou et al.
Measuring and Guiding Monosemanticity
Ruben Härle, Felix Friedrich, Manuel Brack et al.
A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation
Yiwen Tu, Pingbang Hu, Jiaqi Ma
Compute-Optimal Scaling for Value-Based Deep RL
Preston Fu, Oleh Rybkin, Zhiyuan (Paul) Zhou et al.
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
Pratik Rathore, Zachary Frangella, Sachin Garg et al.
Hankel Singular Value Regularization for Highly Compressible State Space Models
Paul Schwerdtner, Jules Berman, Benjamin Peherstorfer
Spark Transformer: Reactivating Sparsity in Transformer FFN and Attention
Chong You, Kan Wu, Zhipeng Jia et al.