Most Cited NEURIPS "object synthesis" Papers
5,858 papers found • Page 8 of 30
Conference
EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling
Jia-Hua Lee, Bor-Jiun Lin, Wei-Fang Sun et al.
Unified Scaling Laws for Compressed Representations
Andrei Panferov, Alexandra Volkova, Ionut-Vlad Modoranu et al.
The Implicit Bias of Structured State Space Models Can Be Poisoned With Clean Labels
Yonatan Slutzky, Yotam Alexander, Noam Razin et al.
CosmoBench: A Multiscale, Multiview, Multitask Cosmology Benchmark for Geometric Deep Learning
Teresa Huang, Richard Stiskalek, Jun-Young Lee et al.
Model-Based Policy Adaptation for Closed-Loop End-to-end Autonomous Driving
Haohong Lin, Yunzhi Zhang, Wenhao Ding et al.
JanusDNA: A Powerful Bi-directional Hybrid DNA Foundation Model
Qihao Duan, Bingding Huang, Zhenqiao Song et al.
DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos
Chieh Lin, Zhaoyang Lv, Songyin Wu 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
Measuring and Guiding Monosemanticity
Ruben Härle, Felix Friedrich, Manuel Brack 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.
Traversal Verification for Speculative Tree Decoding
Yepeng Weng, Qiao Hu, Xujie Chen et al.
Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training
Minhak Song, Beomhan Baek, Kwangjun Ahn 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.
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
Pratik Rathore, Zachary Frangella, Sachin Garg et al.
Spark Transformer: Reactivating Sparsity in Transformer FFN and Attention
Chong You, Kan Wu, Zhipeng Jia et al.
Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark
Hanlei Zhang, zhuohang li, Hua Xu 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.
scMRDR: A scalable and flexible framework for unpaired single-cell multi-omics data integration
Jianle Sun, Chaoqi Liang, Ran Wei et al.
Over-squashing in Spatiotemporal Graph Neural Networks
Ivan Marisca, Jacob Bamberger, Cesare Alippi et al.
CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis
Florian Barthel, Wieland Morgenstern, Paul Hinzer et al.
FlareX: A Physics-Informed Dataset for Lens Flare Removal via 2D Synthesis and 3D Rendering
Lishen Qu, Zhihao Liu, Jinshan Pan et al.
Language Modeling by Language Models
Junyan Cheng, Peter Clark, Kyle Richardson
Second-Order Convergence in Private Stochastic Non-Convex Optimization
Youming Tao, Zuyuan Zhang, Dongxiao Yu et al.
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
Omri Lev, Vishwak Srinivasan, Moshe Shenfeld 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.
Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion
Vinh Tong, Trung-Dung Hoang, Anji Liu et al.
Probabilistic Token Alignment for Large Language Model Fusion
Runjia Zeng, James Liang, Cheng Han et al.
Robustness in Both Domains: CLIP Needs a Robust Text Encoder
Elias Abad Rocamora, Christian Schlarmann, Naman Deep Singh et al.
Imagined Autocurricula
Ahmet Hamdi Güzel, Matthew T Jackson, Jarek Liesen et al.
Mixture-of-Experts Meets In-Context Reinforcement Learning
Wenhao Wu, Fuhong Liu, Haoru Li et al.
From Black-box to Causal-box: Towards Building More Interpretable Models
Inwoo Hwang, Yushu Pan, Elias Bareinboim
Fair Deepfake Detectors Can Generalize
Harry Cheng, Ming-Hui Liu, Yangyang Guo et al.
StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training
Ziming Liu, Shaoyu Wang, Shenggan Cheng et al.
Reward Reasoning Models
Jiaxin Guo, Zewen Chi, Li Dong et al.
GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining
Simin Fan, Maria Ios Glarou, Martin Jaggi
Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
Longwei Wang, Ifrat Ikhtear Uddin, Prof. KC Santosh (PhD) et al.
AlphaFold Database Debiasing for Robust Inverse Folding
Cheng Tan, Zhenxiao Cao, Zhangyang Gao et al.
msf-CNN: Patch-based Multi-Stage Fusion with Convolutional Neural Networks for TinyML
Zhaolan Huang, Emmanuel Baccelli
Unified Reinforcement and Imitation Learning for Vision-Language Models
Byung-Kwan Lee, Ryo Hachiuma, Yong Man Ro et al.
VT-FSL: Bridging Vision and Text with LLMs for Few-Shot Learning
Wenhao Li, Qiangchang Wang, Xianjing Meng et al.
Differentially Private Gomory-Hu Trees
Anders Aamand, Justin Chen, Mina Dalirrooyfard et al.
Escaping saddle points without Lipschitz smoothness: the power of nonlinear preconditioning
Alexander Bodard, Panagiotis Patrinos
Bayes optimal learning of attention-indexed models
Fabrizio Boncoraglio, Emanuele Troiani, Vittorio Erba et al.
Demystifying Network Foundation Models
Roman Beltiukov, Satyandra Guthula, Wenbo Guo et al.
AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark
Aruna Gauba, Irene Pi, Yunze Man et al.
Rethinking Nighttime Image Deraining via Learnable Color Space Transformation
Qiyuan Guan, Xiang Chen, Guiyue Jin et al.
Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality
Alex Fang, Hadi Pouransari, Matt Jordan et al.
When Kernels Multiply, Clusters Unify: Fusing Embeddings with the Kronecker Product
Youqi WU, Jingwei Zhang, Farzan Farnia
Monitoring Risks in Test-Time Adaptation
Mona Schirmer, Metod Jazbec, Christian Andersson Naesseth et al.
ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training
Adel Nabli, Louis Fournier, Pierre ERBACHER et al.
Learning Counterfactual Outcomes Under Rank Preservation
Peng Wu, Haoxuan Li, Chunyuan Zheng et al.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!
Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi et al.
AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
Yuezhou Hu, Jiaxin Guo, Xinyu Feng et al.
Learning to cluster neuronal function
Nina Nellen, Polina Turishcheva, Michaela Vystrčilová 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.
Visual Instruction Bottleneck Tuning
Changdae Oh, Jiatong Li, Shawn Im et al.
A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation
Yiwen Tu, Pingbang Hu, Jiaqi Ma
Logical Expressiveness of Graph Neural Networks with Hierarchical Node Individualization
Arie Soeteman, Balder ten Cate
HoloScene: Simulation‑Ready Interactive 3D Worlds from a Single Video
Hongchi Xia, Chih-Hao Lin, Hao-Yu Hsu et al.
BeliefMapNav: 3D Voxel-Based Belief Map for Zero-Shot Object Navigation
Zibo Zhou, Yue Hu, Lingkai Zhang et al.
Cognitive Mirrors: Exploring the Diverse Functional Roles of Attention Heads in LLM Reasoning
Xueqi Ma, Jun Wang, Yanbei Jiang et al.
Generalized Contrastive Learning for Universal Multimodal Retrieval
Jungsoo Lee, Janghoon Cho, Hyojin Park et al.
Reconstruct, Inpaint, Test-Time Finetune: Dynamic Novel-view Synthesis from Monocular Videos
Kaihua Chen, Tarasha Khurana, Deva Ramanan
PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation
Yanlong Chen, Mattia Orlandi, Pierangelo Rapa et al.
The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games
Ioannis Anagnostides, Ioannis Panageas, Tuomas Sandholm et al.
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.
The Underappreciated Power of Vision Models for Graph Structural Understanding
Xinjian Zhao, Wei Pang, Zhongkai Xue et al.
ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints
Rui Xu, Dakuan Lu, Zicheng Zhao et al.
Gradient Variance Reveals Failure Modes in Flow-Based Generative Models
Teodora Reu, Sixtine Dromigny, Michael Bronstein et al.
Learning to Insert for Constructive Neural Vehicle Routing Solver
Fu Luo, Xi Lin, Mengyuan Zhong et al.
Differentially Private Quantiles with Smaller Error
Jacob Imola, Fabrizio Boninsegna, Hannah Keller et al.
From Linear to Nonlinear: Provable Weak-to-Strong Generalization through Feature Learning
Junsoo Oh, Jerry Song, Chulhee Yun
Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli et al.
Solver-Free Decision-Focused Learning for Linear Optimization Problems
Senne Berden, Ali Mahmutoğulları, Dimos Tsouros et al.
An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models
Binxu Wang, Cengiz Pehlevan
Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds
Fan Wang, Pengtao Shao, Yiming Zhang et al.
Learning Dense Hand Contact Estimation from Imbalanced Data
Daniel Jung, Kyoung Mu Lee
COOPERA: Continual Open-Ended Human-Robot Assistance
Chenyang Ma, Kai Lu, Ruta Desai et al.
Many LLMs Are More Utilitarian Than One
Anita Keshmirian, Razan Baltaji, Babak Hemmatian et al.
SAS: Simulated Attention Score
Chuanyang Zheng, Jiankai Sun, Yihang Gao et al.
Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search
Yousef Al-Jazzazi, Haya Diwan, Jinrui Gou et al.
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference
Wenxuan Zeng, Ye Dong, Jinjin Zhou et al.
OmniGaze: Reward-inspired Generalizable Gaze Estimation in the Wild
Hongyu Qu, Jianan Wei, Xiangbo Shu et al.
Multivariate Dynamic Mediation Analysis under a Reinforcement Learning Framework
Lan Luo, Chengchun Shi, Jitao Wang 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.
Zero-shot protein stability prediction by inverse folding models: a free energy interpretation
Jes Frellsen, Maher Kassem, Tone Bengtsen et al.
Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approach
Swetha Ganesh, Vaneet Aggarwal
Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab
Haonan Duan, Stephen Lu, Caitlin F Harrigan et al.
Risk-aware Direct Preference Optimization under Nested Risk Measure
Lijun Zhang, Lin Li, Yajie Qi et al.
Teaching Language Models to Reason with Tools
Chengpeng Li, Zhengyang Tang, Ziniu Li et al.
SplitFlow: Flow Decomposition for Inversion-Free Text-to-Image Editing
Sung-Hoon Yoon, Minghan Li, Gaspard Beaudouin et al.
Optimism Without Regularization: Constant Regret in Zero-Sum Games
John Lazarsfeld, Georgios Piliouras, Ryann Sim et al.
Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum
Snir Hordan, Maya Bechler-Speicher, Gur Lifshitz et al.
The Generative Leap: Tight Sample Complexity for Efficiently Learning Gaussian Multi-Index Models
Alex Damian, Jason Lee, Joan Bruna
AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing
Sam Bright-Thonney, Christina Reissel, Gaia Grosso et al.
Set Smoothness Unlocks Clarke Hyper-stationarity in Bilevel Optimization
He Chen, Jiajin Li, Anthony Man-Cho So
Diffusion Generative Modeling on Lie Group Representations
Marco Bertolini, Tuan Le, Djork-Arné Clevert
Feedback-Aware MCTS for Goal-Oriented Information Seeking
Harshita Chopra, Chirag Shah
Distributional Autoencoders Know the Score
Andrej Leban
Attack via Overfitting: 10-shot Benign Fine-tuning to Jailbreak LLMs
Zhixin Xie, Xurui Song, Jun Luo
Multivariate Latent Recalibration for Conditional Normalizing Flows
Victor Dheur, Souhaib Ben Taieb
FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models
Zihao Fu, Ryan Brown, Shun Shao et al.
Influence Guided Context Selection for Effective Retrieval-Augmented Generation
Jiale Deng, Yanyan Shen, Ziyuan Pei et al.
Beyond Scores: Proximal Diffusion Models
Zhenghan Fang, Mateo Diaz, Sam Buchanan et al.
Neural Collapse in Cumulative Link Models for Ordinal Regression: An Analysis with Unconstrained Feature Model
Chuang Ma, Tomoyuki Obuchi, Toshiyuki Tanaka
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.
ArchCAD-400K: A Large-Scale CAD drawings Dataset and New Baseline for Panoptic Symbol Spotting
Ruifeng Luo, Zhengjie Liu, Tianxiao Cheng et al.
Conformal Risk Training: End-to-End Optimization of Conformal Risk Control
Christopher Yeh, Nicolas Christianson, Adam Wierman et al.
Noise Matters: Optimizing Matching Noise for Diffusion Classifiers
Yanghao Wang, Long Chen
Convolution Goes Higher-Order: A Biologically Inspired Mechanism Empowers Image Classification
Simone Azeglio, Olivier Marre, Peter Neri et al.
Robo2VLM: Improving Visual Question Answering using Large-Scale Robot Manipulation Data
Kaiyuan Eric Chen, Shuangyu Xie, Zehan Ma et al.
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion
Yuanyi Wang, Zhaoyi Yan, Yiming Zhang et al.
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune, David Vigouroux, Yilun Du et al.
PartNeXt: A Next-Generation Dataset for Fine-Grained and Hierarchical 3D Part Understanding
Penghao Wang, Yiyang He, Xin Lv et al.
Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models
Jiaqi Cao, Jiarui Wang, Rubin Wei et al.
Representation Consistency for Accurate and Coherent LLM Answer Aggregation
Junqi Jiang, Tom Bewley, Salim I. Amoukou et al.
Brain Harmony: A Multimodal Foundation Model Unifying Morphology and Function into 1D Tokens
Zijian Dong, Ruilin Li, Joanna Chong et al.
Limitations of Normalization in Attention
Timur Mudarisov, Mikhail Burtsev, Tatiana Petrova et al.
DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs
Ruokai Yin, Yuhang Li, Donghyun Lee et al.
A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning
Yuzheng Hu, Fan Wu, Haotian Ye et al.
Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models
William Overman, Mohsen Bayati
Emergent Risk Awareness in Rational Agents under Resource Constraints
Daniel Jarne Ornia, Nicholas Bishop, Joel Dyer 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.
A Clean Slate for Offline Reinforcement Learning
Matthew T Jackson, Uljad Berdica, Jarek Liesen et al.
Connecting Neural Models Latent Geometries with Relative Geodesic Representations
Hanlin Yu, Berfin Inal, Georgios Arvanitidis et al.
Preconditioned Langevin Dynamics with Score-based Generative Models for Infinite-Dimensional Linear Bayesian Inverse Problems
Lorenzo Baldassari, Josselin Garnier, Knut Solna et al.
V2V: Scaling Event-Based Vision through Efficient Video-to-Voxel Simulation
Hanyue Lou, Jinxiu Liang, Minggui Teng et al.
From Forecasting to Planning: Policy World Model for Collaborative State-Action Prediction
Zhida Zhao, Talas Fu, Yifan Wang et al.
Credal Prediction based on Relative Likelihood
Timo Löhr, Paul Hofman, Felix Mohr et al.
Rethinking Residual Distribution in Locate-then-Edit Model Editing
Xiaopeng Li, Shangwen Wang, Shasha Li et al.
Image Editing As Programs with Diffusion Models
Yujia Hu, Songhua Liu, Zhenxiong Tan et al.
EVODiff: Entropy-aware Variance Optimized Diffusion Inference
Shigui Li, Wei Chen, Delu Zeng
Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning
Tianyi Bai, Yuxuan Fan, Qiu Jiantao et al.
ReCAP: Recursive Context-Aware Reasoning and Planning for Large Language Model Agents
Zhenyu Zhang, Tianyi Chen, Weiran Xu et al.
Provably Efficient Online RLHF with One-Pass Reward Modeling
Long-Fei Li, Yu-Yang Qian, Peng Zhao et al.
On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning
Till Freihaut, Giorgia Ramponi
Text-Aware Real-World Image Super-Resolution via Diffusion Model with Joint Segmentation Decoders
Qiming Hu, Linlong Fan, Yiyan Luo et al.
ViSpec: Accelerating Vision-Language Models with Vision-Aware Speculative Decoding
Jialiang Kang, Han Shu, Wenshuo Li et al.
A Partition Cover Approach to Tokenization
Jia Peng Lim, Shawn Tan, XianJun, Davin Choo et al.
A Theory for Worst-Case vs. Average-Case Guarantees for LLMs
Noga Amit, Shafi Goldwasser, Orr Paradise et al.
What are you sinking? A geometric approach on attention sink
Valeria Ruscio, Umberto Nanni, Fabrizio Silvestri
Efficient Preference-Based Reinforcement Learning: Randomized Exploration meets Experimental Design
Andreas Schlaginhaufen, Reda Ouhamma, Maryam Kamgarpour
Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models
zhentao he, Can Zhang, Ziheng Wu et al.
Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback
Shinji Ito, Kevin Jamieson, Haipeng Luo et al.
Meta-Learning Objectives for Preference Optimization
Carlo Alfano, Silvia Sapora, Jakob Foerster et al.
Transformers for Mixed-type Event Sequences
Felix Draxler, Yang Meng, Kai Nelson et al.
Scale-invariant attention
Ben Anson, Xi Wang, Laurence Aitchison
GnnXemplar: Exemplars to Explanations - Natural Language Rules for Global GNN Interpretability
Burouj Armgaan, Eshan Jain, Harsh Pandey et al.
Generalized Linear Bandits: Almost Optimal Regret with One-Pass Update
Yu-Jie Zhang, Sheng-An Xu, Peng Zhao et al.
Data Fusion for Partial Identification of Causal Effects
Quinn Lanners, Cynthia Rudin, Alexander Volfovsky et al.
Streaming Attention Approximation via Discrepancy Theory
Ekaterina Kochetkova, Kshiteej Jitesh Sheth, Insu Han et al.
A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
Qingyue Zhang, Haohao Fu, Guanbo Huang et al.
Factorio Learning Environment
Jack Hopkins, Mart Bakler, Akbir Khan
Rethinking Losses for Diffusion Bridge Samplers
Sebastian Sanokowski, Lukas Gruber, Christoph Bartmann et al.
Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents
Zhizhen Zhang, Lei Zhu, Zhen Fang et al.
RSCC: A Large-Scale Remote Sensing Change Caption Dataset for Disaster Events
Zhenyuan Chen, Chenxi Wang, Ningyu Zhang et al.
Elucidated Rolling Diffusion Models for Probabilistic Forecasting of Complex Dynamics
Salva Rühling Cachay, Miika Aittala, Karsten Kreis et al.
BLINK-Twice: You see, but do you observe? A Reasoning Benchmark on Visual Perception
junyan ye, Dongzhi JIANG, Jun He et al.
Plasticity as the Mirror of Empowerment
David Abel, Michael Bowling, Andre Barreto et al.
PDEfuncta: Spectrally-Aware Neural Representation for PDE Solution Modeling
Minju Jo, Woojin Cho, Uvini Balasuriya Mudiyanselage et al.
Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models
Chantal Shaib, Vinith Suriyakumar, Byron Wallace et al.
Hamiltonian Descent Algorithms for Optimization: Accelerated Rates via Randomized Integration Time
Qiang Fu, Andre Wibisono
Exploring the Translation Mechanism of Large Language Models
Hongbin Zhang, Kehai Chen, Xuefeng Bai et al.
PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs
Xinzhe Zheng, Hao Du, Fanding Xu et al.
SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
Reda Marzouk, Shahaf Bassan, Guy Katz
Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
Mustafa Hajij, Lennart Bastian, Sarah Osentoski et al.
On the creation of narrow AI: hierarchy and nonlocality of neural network skills
Eric Michaud, Asher Parker-Sartori, Max Tegmark
HYPRL: Reinforcement Learning of Control Policies for Hyperproperties
Tzu-Han Hsu, Arshia Rafieioskouei, Borzoo Bonakdarpour
Normalization in Attention Dynamics
Nikita Karagodin, Shu Ge, Yury Polyanskiy et al.
The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
Moritz Stargalla, Christoph Hertrich, Daniel Reichman
Open-World Drone Active Tracking with Goal-Centered Rewards
Haowei Sun, Jinwu Hu, Zhirui Zhang et al.
GRIP: A Graph-Based Reasoning Instruction Producer
Jiankang Wang, Jianjun Xu, Xiaorui Wang et al.
Learn2Mix: Training Neural Networks Using Adaptive Data Integration
Shyam Venkatasubramanian, Vahid Tarokh
Conformal Information Pursuit for Interactively Guiding Large Language Models
Kwan Ho Ryan Chan, Yuyan Ge, Edgar Dobriban et al.
CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting
Kornel Howil, Joanna Waczynska, Piotr Borycki et al.
S'MoRE: Structural Mixture of Residual Experts for Parameter-Efficient LLM Fine-tuning
Hanqing Zeng, Yinglong Xia, Zhuokai Zhao et al.
Selective Learning for Deep Time Series Forecasting
Yisong Fu, Zezhi Shao, Chengqing Yu et al.
Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems
Jongyeong Lee, Junya Honda, Shinji Ito et al.
Delta Attention: Fast and Accurate Sparse Attention Inference by Delta Correction
Jeffrey Willette, Heejun Lee, Sung Ju Hwang
The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model
Kaito Takanami, Takashi Takahashi, Ayaka Sakata
Reinforced Context Order Recovery for Adaptive Reasoning and Planning
Long Ma, Fangwei Zhong, Yizhou Wang
Adaptive Inference-Time Scaling via Cyclic Diffusion Search
Gyubin Lee, Bao Truong, Jaesik Yoon et al.
LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
Yanan Li, Fanxu Meng, Muhan Zhang et al.
SparseDiT: Token Sparsification for Efficient Diffusion Transformer
Shuning Chang, Pichao WANG, Jiasheng Tang et al.
Practical Bayes-Optimal Membership Inference Attacks
Marcus Lassila, Johan Oestman, Khac-Hoang Ngo et al.
Intervene-All-Paths: Unified Mitigation of LVLM Hallucinations across Alignment Formats
Jiaye Qian, Ge Zheng, Yuchen Zhu et al.
UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
Shijun Liang, Ismail Alkhouri, Siddhant Gautam et al.
Filter Like You Test: Data-Driven Data Filtering for CLIP Pretraining
Mikey Shechter, Yair Carmon
Hadamax Encoding: Elevating Performance in Model-Free Atari
Jacob Eeuwe Kooi, Zhao Yang, Vincent Francois-Lavet
A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications
Zhenyu Tao, Wei Xu, Xiaohu You
Modeling the Economic Impacts of AI Openness Regulation
Tori Qiu, Benjamin Laufer, Jon Kleinberg et al.
FLOWING: Implicit Neural Flows for Structure-Preserving Morphing
Arthur Bizzi, Matias Grynberg Portnoy, Vitor Pereira Matias et al.
High-order Equivariant Flow Matching for Density Functional Theory Hamiltonian Prediction
Seongsu Kim, Nayoung Kim, Dongwoo Kim et al.
Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models
Sima Noorani, Shayan Kiyani, George J. Pappas et al.