Most Cited 2025 "auroc adaptation" Papers
22,274 papers found • Page 111 of 112
Conference
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann, Dongxia Wu, Germano Heinzelmann et al.
Sanity Checking Causal Representation Learning on a Simple Real-World System
Juan L. Gamella, Simon Bing, Jakob Runge
CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning
Hongtu Zhou, Ruiling Yang, Yakun Zhu et al.
To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
Roman Plaud, Alexandre Perez-Lebel, Matthieu Labeau et al.
InfoCons: Identifying Interpretable Critical Concepts in Point Clouds via Information Theory
Feifei Li, Mi Zhang, Zhaoxiang Wang et al.
Chip Placement with Diffusion Models
Vint Lee, Minh Nguyen, Leena Elzeiny et al.
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
Walter Mayor, Johan Obando-Ceron, Aaron Courville et al.
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Zhao, Xinai Lu et al.
Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching
Nabeel Seedat, Mihaela van der Schaar
EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration
Allen Nie, Yi Su, Bo Chang et al.
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games
Tong Yang, Bo Dai, Lin Xiao et al.
Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning
Wenjing Yan, Xiangyu Zhong, Xiaolu Wang et al.
Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
Kuheli Pratihar, Debdeep Mukhopadhyay
Improving Soft Unification with Knowledge Graph Embedding Methods
Xuanming Cui, Chionh Peng, Adriel Kuek et al.
Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida et al.
Nonparametric Identification of Latent Concepts
Yujia Zheng, Shaoan Xie, Kun Zhang
The Limits of Tractable Marginalization
Oliver Broadrick, Sanyam Agarwal, Guy Van den Broeck et al.
Compressed Image Generation with Denoising Diffusion Codebook Models
Guy Ohayon, Hila Manor, Tomer Michaeli et al.
Large Language Models to Diffusion Finetuning
Edoardo Cetin, Tianyu Zhao, Yujin Tang
Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
Anas Jnini, Lorenzo Breschi, Flavio Vella
Learning Fused State Representations for Control from Multi-View Observations
Zeyu Wang, Yao-Hui Li, Xin Li et al.
Efficient and Separate Authentication Image Steganography Network
Junchao Zhou, Yao Lu, Jie Wen et al.
EvFocus: Learning to Reconstruct Sharp Images from Out-of-Focus Event Streams
Lin Zhu, Xiantao Ma, Xiao Wang et al.
Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time
Mohamad Chehade, Soumya Suvra Ghosal, Souradip Chakraborty et al.
The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination
Yifan Sun, Han Wang, Dongbai Li et al.
Controlling Large Language Model with Latent Action
Chengxing Jia, Ziniu Li, Pengyuan Wang et al.
Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations
Yucheng Hu, Yanjiang Guo, Pengchao Wang et al.
What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning?
Katie Kang, Amrith Setlur, Dibya Ghosh et al.
Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara et al.
Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning
Wenke Huang, Jian Liang, Guancheng Wan et al.
Runtime Analysis of Evolutionary NAS for Multiclass Classification
Zeqiong Lv, Chao Qian, Yun Liu et al.
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
Le Tuyet Nhi PHAM, Dario Shariatian, Antonio Ocello et al.
The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models Via Visual Information Steering
Zhuowei Li, Haizhou Shi, Yunhe Gao et al.
Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation
Yiming Yang, Xiaoyuan Cheng, Daniel Giles et al.
TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
Ron Shapira Weber, shahar benishay, Andrey Lavrinenko et al.
Language Models as Implicit Tree Search
Ziliang Chen, Zhao-Rong Lai, Yufeng Yang et al.
SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
Yong Liu, Di Fu, Shenggan Cheng et al.
Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedule
Keyue Qiu, Yuxuan Song, Zhehuan Fan et al.
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
Hanting Wang, Tao Jin, Wang Lin et al.
Splitting & Integrating: Out-of-Distribution Detection via Adversarial Gradient Attribution
Jiayu Zhang, Xinyi Wang, Zhibo Jin et al.
SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation
Haoquan Fang, Markus Grotz, Wilbert Pumacay et al.
Offline Learning for Combinatorial Multi-armed Bandits
Xutong Liu, Xiangxiang Dai, Jinhang Zuo et al.
Lightweight-Mark: Rethinking Deep Learning-Based Watermarking
Yupeng Qiu, Han Fang, Ee-Chien Chang
MoE-SVD: Structured Mixture-of-Experts LLMs Compression via Singular Value Decomposition
Wei Li, Lujun Li, Hao Gu et al.
Compositional Condition Question Answering in Tabular Understanding
Jun-Peng Jiang, Tao Zhou, De-Chuan Zhan et al.
Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance
Guoqing Chao, Zhenghao Zhang, Lei Meng et al.
On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning
Thomas T. Zhang, Behrad Moniri, Ansh Nagwekar et al.
Multi-Turn Code Generation Through Single-Step Rewards
Arnav Kumar Jain, Gonzalo Gonzalez-Pumariega, Wayne Chen et al.
AnyEdit: Edit Any Knowledge Encoded in Language Models
Houcheng Jiang, Junfeng Fang, Ningyu Zhang et al.
Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model
SHEN FEI, Cong Wang, Junyao Gao et al.
Risk-Sensitive Theory of Mind: Coordinating with Agents of Unknown Bias using Cumulative Prospect Theory
Mason O. Smith, Wenlong Zhang
The Limits of Predicting Agents from Behaviour
Alexis Bellot, Jonathan Richens, Tom Everitt
Reinforcement Learning Control of a Physical Robot Device for Assisted Human Walking without a Simulator
junmin zhong, Emiliano Quinones Yumbla, Seyed Yousef Soltanian et al.
In-Context Learning as Conditioned Associative Memory Retrieval
Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu et al.
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition
Sungnyun Kim, Kangwook Jang, Sangmin Bae et al.
Disentangled Graph Spectral Domain Adaptation
Liang Yang, Xin Chen, Jiaming Zhuo et al.
Fourier Position Embedding: Enhancing Attention’s Periodic Extension for Length Generalization
Ermo Hua, Che Jiang, Xingtai Lv et al.
Controlling Neural Collapse Enhances Out-of-Distribution Detection and Transfer Learning
Md Yousuf Harun, Jhair Gallardo, Christopher Kanan
You Get What You Give: Reciprocally Fair Federated Learning
Aniket Murhekar, Jiaxin Song, Parnian Shahkar et al.
CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
Zongzhen Yang, Binhang Qi, Hailong Sun et al.
Decoupled SGDA for Games with Intermittent Strategy Communication
Ali Zindari, Parham Yazdkhasti, Anton Rodomanov et al.
BILBO: BILevel Bayesian Optimization
Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low
Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes
Zhuocheng Gong, Jian Guan, Wei Wu et al.
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
Yunhao Tang, Kunhao Zheng, Gabriel Synnaeve et al.
Low-Dimension-to-High-Dimension Generalization and Its Implications for Length Generalization
Yang Chen, Long Yang, Yitao Liang et al.
Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
Yulun Wu, Doron Bergman
Don't Restart, Just Reuse: Reoptimizing MILPs with Dynamic Parameters
Sijia Zhang, Shuli Zeng, Shaoang Li et al.
Physics Aware Neural Networks for Unsupervised Binding Energy Prediction
Ke Liu, Hao Chen, Chunhua Shen
MARGE: Improving Math Reasoning with Guided Exploration
Jingyue Gao, Runji Lin, Keming Lu et al.
ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization
Hee Suk Yoon, Eunseop Yoon, Mark Hasegawa-Johnson et al.
ERICT: Enhancing Robustness by Identifying Concept Tokens in Zero-Shot Vision Language Models
Xinpeng Dong, Min Zhang, Didi Zhu et al.
Equivalence is All: A Unified View for Self-supervised Graph Learning
Yejiang Wang, Yuhai Zhao, Zhengkui Wang et al.
NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations
Myunsoo Kim, Hayeong Lee, Seong-Woong Shim et al.
LightGTS: A Lightweight General Time Series Forecasting Model
Yihang Wang, Yuying Qiu, Peng Chen et al.
EcoMapper: Generative Modeling for Climate-Aware Satellite Imagery
Muhammed Göktepe, Amir Hossein Shamseddin, Erencan Uysal et al.
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
Hanxun Huang, Sarah Erfani, Yige Li et al.
Adaptive Flow Matching for Resolving Small-Scale Physics
Stathi Fotiadis, Noah Brenowitz, Tomas Geffner et al.
Improving Compositional Generation with Diffusion Models Using Lift Scores
Chenning Yu, Sicun Gao
Learning Mean Field Control on Sparse Graphs
Christian Fabian, Kai Cui, Heinz Koeppl
Safe-EF: Error Feedback for Non-smooth Constrained Optimization
Rustem Islamov, Yarden As, Ilyas Fatkhullin
Quadruple Attention in Many-body Systems for Accurate Molecular Property Predictions
Jiahua Rao, Dahao Xu, Wentao Wei et al.
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills
Aidan Curtis, Eric Li, Michael S Noseworthy et al.
No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets
Corinna Coupette, Jeremy Wayland, Emily Simons et al.
Fast Tensor Completion via Approximate Richardson Iteration
Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook et al.
Habitizing Diffusion Planning for Efficient and Effective Decision Making
Haofei Lu, Yifei Shen, Dongsheng Li et al.
Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
Jijia Liu, Feng Gao, Qingmin Liao et al.
Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
Alessandro Montenegro, Marco Mussi, Matteo Papini et al.
FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models
Xinting Liao, Weiming Liu, Jiaming Qian et al.
Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding
Ziyao Wang, Muneeza Azmat, Ang Li et al.
DeepLayout: Learning Neural Representations of Circuit Placement Layout
Yuxiang Zhao, zhuomin chai, Xun Jiang et al.
BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training
Chenyi yang, Wenjie Nie, Yuxin Zhang et al.
Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails
Jindong Tong, Hongcheng Liu, Johannes Royset
Pareto-frontier Entropy Search with Variational Lower Bound Maximization
Masanori Ishikura, Masayuki Karasuyama
When to retrain a machine learning model
Florence Regol, Leo Schwinn, Kyle Sprague et al.
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts
Yike Yuan, Ziyu Wang, Zihao Huang et al.
Feature Shift Localization Network
Míriam Barrabés, Daniel Mas Montserrat, Kapal Dev et al.
GIVE: Structured Reasoning of Large Language Models with Knowledge Graph Inspired Veracity Extrapolation
Jiashu HE, Mingyu Ma, Jinxuan Fan et al.
Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation
Zhihua Liu, Amrutha Saseendran, Lei Tong et al.
Diving into Self-Evolving Training for Multimodal Reasoning
Wei Liu, Junlong Li, Xiwen Zhang et al.
Generalization and Robustness of the Tilted Empirical Risk
Gholamali Aminian, Amir R. Asadi, Tian Li et al.
Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision
Anqi Lu, Junchi Yan
ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
Tianci Bu, Le Zhou, Wenchuan Yang et al.
Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification
Teng Huang, Bin-Bin Jia, Min-Ling Zhang
Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
Yibo Xu, Dawei Zhou, Decheng Liu et al.
Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing
Xiang Zhang, Jiaqi Wei, Zijie Qiu et al.
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk
Approximating Latent Manifolds in Neural Networks via Vanishing Ideals
Nico Pelleriti, Max Zimmer, Elias Wirth et al.
D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
Zijing Hu, Fengda Zhang, Kun Kuang
MVA: Linear Attention with High-order Query-Keys Integration and Multi-level Vocabulary Decomposition
ning wang, Zekun Li, Tongxin Bai et al.
Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path Simplices
Junhao Dong, Piotr Koniusz, Yifei Zhang et al.
Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral et al.
Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily
Online Learning in the Random-Order Model
Martino Bernasconi, Andrea Celli, Riccardo Colini Baldeschi et al.
Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations
Zhengming Chen, Yewei Xia, Feng Xie et al.
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
Mohamad Chehade, Wenting Li, Brian Bell et al.
Latent Variable Causal Discovery under Selection Bias
Haoyue Dai, Yiwen Qiu, Ignavier Ng et al.
Communicating Activations Between Language Model Agents
Vignav Ramesh, Kenneth Li
Batch List-Decodable Linear Regression via Higher Moments
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
Gravity-Bench-v1: A Benchmark on Gravitational Physics Discovery for Agents
Nolan Koblischke, Hyunseok Jang, Kristen Menou et al.
LLM-Assisted Semantically Diverse Teammate Generation for Efficient Multi-agent Coordination
Lihe Li, lei yuan, Pengsen Liu et al.
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
Wenzhe Niu, Zongxia Xie, Yanru Sun et al.
DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
Junjie Wen, Yichen Zhu, Minjie Zhu et al.
Learning Monotonic Probabilities with a Generative Cost Model
Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu et al.
Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion
Dohoon Lee, Jaehyun Park, Hyunwoo Kim et al.
UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent
Jianke Zhang, Yanjiang Guo, Yucheng Hu et al.
Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
Hanyang Zhao, Haoxian Chen, Ji Zhang et al.
TabSDS: a Lightweight, Fully Non-Parametric, and Model Free Approach for Generating Synthetic Tabular Data
Elias Chaibub Neto
Point Cloud Dataset Distillation
Deyu Bo, Xinchao Wang
Towards Black-Box Membership Inference Attack for Diffusion Models
Jingwei Li, Jing Dong, Tianxing He et al.
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents
Shayan Kiyani, George Pappas, Aaron Roth et al.
Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models
peijie liu, Fengli Xu, Yong Li
Efficient Core-set Selection for Deep Learning Through Squared Loss Minimization
Jianting Chen
Training a Generally Curious Agent
Fahim Tajwar, Yiding Jiang, Abitha Thankaraj et al.
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
Rethinking Benign Overfitting in Two-Layer Neural Networks
Ruichen Xu, Kexin Chen
Multimodal Medical Code Tokenizer
Xiaorui Su, Shvat Messica, Yepeng Huang et al.
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions
Onat Dalmaz, Arjun Desai, Reinhard Heckel et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.
Can DBNNs Robust to Environmental Noise for Resource-constrained Scenarios?
Wendong Zheng, Junyang Chen, Husheng Guo et al.
Probably Approximately Global Robustness Certification
Peter Blohm, Patrick Indri, Thomas Gärtner et al.
Graph Adaptive Autoregressive Moving Average Models
Moshe Eliasof, Alessio Gravina, Andrea Ceni et al.
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
MYUNG-SIK CHO, Jong Eui Park, Jeonghye Kim et al.
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
Rickard Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj et al.
Understanding the difficulties of posterior predictive estimation
Abhinav Agrawal, Justin Domke
Fast Exact Unlearning for In-Context Learning Data for LLMs
Andrei Muresanu, Anvith Thudi, Michael Zhang et al.
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
Filip Szatkowski, Yaoyue Zheng, Fei Yang et al.
Griffin: Towards a Graph-Centric Relational Database Foundation Model
Yanbo Wang, Xiyuan Wang, Quan Gan et al.
Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks
Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
Optimizing Test-Time Compute via Meta Reinforcement Finetuning
Yuxiao Qu, Matthew Yang, Amrith Setlur et al.
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting
Chen Huang, Skyler Seto, Hadi Pouransari et al.
Stochastic Forward–Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets
Haoye Lu, Qifan Wu, Yaoliang Yu
Progressive Tempering Sampler with Diffusion
Severi Rissanen, RuiKang OuYang, Jiajun He et al.
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama
Mind the Gap: A Practical Attack on GGUF Quantization
Kazuki Egashira, Robin Staab, Mark Vero et al.
Unlocking the Power of SAM 2 for Few-Shot Segmentation
Qianxiong Xu, Lanyun Zhu, Xuanyi Liu et al.
ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
Yeqing Qiu, Ye XUE, Akang Wang et al.
Optimal Fair Learning Robust to Adversarial Distribution Shift
Sushant Agarwal, Amit Jayant Deshpande, Rajmohan Rajaraman et al.
Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token Prediction
Shu-wen Yang, Byeonggeun Kim, Kuan Po Huang et al.
What Has a Foundation Model Found? Inductive Bias Reveals World Models
Keyon Vafa, Peter Chang, Ashesh Rambachan et al.
Dialogue Without Limits: Constant-Sized KV Caches for Extended Response in LLMs
Ravi Ghadia, Avinash Kumar, Gaurav Jain et al.
Tree-Sliced Wasserstein Distance: A Geometric Perspective
Viet Hoang Tran, Trang Pham, Tho Tran Huu et al.
When Bad Data Leads to Good Models
Kenneth Li, Yida Chen, Fernanda Viégas et al.
Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback
Simone Drago, Marco Mussi, Alberto Maria Metelli
Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
JINHAO LIANG, Jacob Christopher, Sven Koenig et al.
Off-Policy Evaluation under Nonignorable Missing Data
Han Wang, Yang Xu, Wenbin Lu et al.
PokéChamp: an Expert-level Minimax Language Agent
Seth Karten, Andy Nguyen, Chi Jin
Self-supervised Adversarial Purification for Graph Neural Networks
Woohyun Lee, Hogun Park
The Case for Learned Provenance-based System Behavior Baseline
Yao Zhu, Zhenyuan LI, yangyang wei et al.
KIND: Knowledge Integration and Diversion for Training Decomposable Models
Yucheng Xie, Fu Feng, Ruixiao Shi et al.
Fast Large Language Model Collaborative Decoding via Speculation
Jiale Fu, Yuchu Jiang, Junkai Chen et al.
STD-FD: Spatio-Temporal Distribution Fitting Deviation for AIGC Forgery Identification
Hengrui Lou, Zunlei Feng, Jinsong Geng et al.
Simple Policy Optimization
Zhengpeng Xie, Qiang Zhang, Fan Yang et al.
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Blake Bordelon, Cengiz Pehlevan
LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
Dachuan Shi, Yonggan Fu, Xiangchi Yuan et al.
Provable Efficiency of Guidance in Diffusion Models for General Data Distribution
Gen Li, Yuchen Jiao
Directly Forecasting Belief for Reinforcement Learning with Delays
Qingyuan Wu, Yuhui Wang, Simon Zhan et al.
Quantum Speedup for Hypergraph Sparsification
Chenghua Liu, Minbo Gao, Zhengfeng Ji et al.
The Role of Sparsity for Length Generalization in LLMs
Noah Golowich, Samy Jelassi, David Brandfonbrener et al.
Selective Preference Aggregation
Shreyas Kadekodi, Hayden McTavish, Berk Ustun
ZipAR: Parallel Autoregressive Image Generation through Spatial Locality
Yefei He, Feng Chen, Yuanyu He et al.
Chaos Meets Attention: Transformers for Large-Scale Dynamical Prediction
Yi He, Yiming Yang, Xiaoyuan Cheng et al.
DSBRouter: End-to-end Global Routing via Diffusion Schr\"{o}dinger Bridge
Liangliang Shi, Shenhui Zhang, Xingbo Du et al.
Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion
David Geissbühler, Hatef Otroshi Shahreza, Sébastien Marcel
Improving Diversity in Language Models: When Temperature Fails, Change the Loss
Alexandre Verine, Florian Le Bronnec, Kunhao Zheng et al.
Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
Sayan Bhattacharya, Martín Costa, Ermiya Farokhnejad et al.
Efficient Network Automatic Relevance Determination
Hongwei Zhang, Ziqi Ye, Xinyuan Wang et al.
Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification
Jie Wen, Yadong Liu, Zhanyan Tang et al.
Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation
Junyu Luo, Yuhao Tang, Yiwei Fu et al.
H-Tuning: Toward Low-Cost and Efficient ECG-based Cardiovascular Disease Detection with Pre-Trained Models
Rushuang Zhou, Yuanting Zhang, Yining Dong
Schwarz–Schur Involution: Lightspeed Differentiable Sparse Linear Solvers
Yu Wang, Mazdak Abulnaga, Yaël Balbastre et al.
Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage
Saehyung Lee, Seunghyun Yoon, Trung Bui et al.
Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models
Quan Nguyen, Minh Vu, Truc Nguyen et al.
Tensor Decomposition Based Memory-Efficient Incremental Learning
Yuhang Li, Guoxu Zhou, Zhenhao Huang et al.
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations
Andrei Panferov, Jiale Chen, Rush Tabesh et al.
Editable Concept Bottleneck Models
Lijie Hu, Chenyang Ren, Zhengyu Hu et al.
GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation
Yi Cai, Thibaud Ardoin, Gerhard Wunder
Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation
Yaowenhu, Wenxuan Tu, Yue Liu et al.
Beyond Entropy: Region Confidence Proxy for Wild Test-Time Adaptation
Zixuan Hu, Yichun Hu, Xiaotong Li et al.
Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional
Sanjeev Raja, Martin Šípka, Michael Psenka et al.
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
Ning LU, Shengcai Liu, Jiahao Wu et al.