Most Cited 2025 "microscopic imaging" Papers
22,274 papers found • Page 106 of 112
Conference
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
Peng Xu, Wei Ping, Xianchao Wu et al.
Boltzmann priors for Implicit Transfer Operators
Juan Viguera Diez, Mathias Schreiner, Ola Engkvist et al.
Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics
Tianfang Zhu, Dongli Hu, Jiandong Zhou et al.
Towards Understanding the Universality of Transformers for Next-Token Prediction
Michael Sander, Gabriel Peyré
Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning
Menglong Zhang, Fuyuan Qian, Quanying Liu
Online Clustering with Nearly Optimal Consistency
T-H. Hubert Chan, Shaofeng Jiang, Tianyi Wu et al.
The Geometry of Categorical and Hierarchical Concepts in Large Language Models
Kiho Park, Yo Joong Choe, Yibo Jiang et al.
Watch Less, Do More: Implicit Skill Discovery for Video-Conditioned Policy
Wang, Zongqing Lu
From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities
Wanpeng Zhang, Zilong Xie, Yicheng Feng et al.
Lost in Prediction: Why Social Media Narratives Don't Help Macroeconomic Forecasting?
Almog Gueta, Roi Reichart, Amir Feder et al.
Procedural Synthesis of Synthesizable Molecules
Michael Sun, Alston Lo, Minghao Guo et al.
Conditional Testing based on Localized Conformal $p$-values
Xiaoyang Wu, Lin Lu, Zhaojun Wang et al.
3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting
Qihang Zhang, Yinghao Xu, Chaoyang Wang et al.
Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence
Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker et al.
Time-to-Event Pretraining for 3D Medical Imaging
Zepeng Frazier Huo, Jason Fries, Alejandro Lozano et al.
Denoising Autoregressive Transformers for Scalable Text-to-Image Generation
Jiatao Gu, Yuyang Wang, Yizhe Zhang et al.
Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement
Bryan Bo Cao, Lawrence OGorman, Michael Coss et al.
Bad-PFL: Exploiting Backdoor Attacks against Personalized Federated Learning
Mingyuan Fan, Zhanyi Hu, Fuyi Wang et al.
Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
Ryan Lucas, Rahul Mazumder
Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks
Hung Quang Nguyen, Hieu Nguyen, Anh Ta et al.
CR-CTC: Consistency regularization on CTC for improved speech recognition
Zengwei Yao, Wei Kang, Xiaoyu Yang et al.
An Illustrated Guide to Automatic Sparse Differentiation
Adrian Hill, Guillaume Dalle, Alexis Montoison
LLM-DR: A Novel LLM-Aided Diffusion Model for Rule Generation on Temporal Knowledge Graphs
Kai Chen, Xin Song, Ye Wang et al.
Augmenting Sequential Recommendation with Balanced Relevance and Diversity
Yizhou Dang, Jiahui Zhang, Yuting Liu et al.
Robust System Identification: Finite-sample Guarantees and Connection to Regularization
Hank Park, Grani A. Hanasusanto, Yingying Li
Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon et al.
A Statistical Framework for Ranking LLM-based Chatbots
Siavash Ameli, Siyuan Zhuang, Ion Stoica et al.
NExUME: Adaptive Training and Inference for DNNs under Intermittent Power Environments
Cyan Subhra Mishra, Deeksha Chaudhary, Jack Sampson et al.
PEARL: Parallel Speculative Decoding with Adaptive Draft Length
Tianyu Liu, Yun Li, Qitan Lv et al.
Capturing the Temporal Dependence of Training Data Influence
Jiachen (Tianhao) Wang, Dawn Song, James Y Zou et al.
Reconciling Model Multiplicity for Downstream Decision Making
Ally Du, Dung Daniel Ngo, Steven Wu
Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning
Shengyuan Hu, Yiwei Fu, Steven Wu et al.
Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness
Eli Chien, Pan Li
ARB-LLM: Alternating Refined Binarizations for Large Language Models
Zhiteng Li, Xianglong Yan, Tianao Zhang et al.
OSTQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Xing Hu, Yuan Cheng, Dawei Yang et al.
GOttack: Universal Adversarial Attacks on Graph Neural Networks via Graph Orbits Learning
Zulfikar Alom, Tran Gia Bao Ngo, Murat Kantarcioglu et al.
Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds
Michael Chen, A. Pavan, N. V. Vinodchandran et al.
Efficient Imitation under Misspecification
Nicolas Espinosa Dice, Sanjiban Choudhury, Wen Sun et al.
Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
Qi Le, Enmao Diao, Ziyan Wang et al.
Discrete Distribution Networks
Lei Yang
Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model
Rundong He, Yicong Dong, Lan-Zhe Guo et al.
ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano et al.
Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building
Jaedong Hwang, Zhang-Wei Hong, Eric Chen et al.
DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes
Hengwei Bian, Lingdong Kong, Haozhe Xie et al.
MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
Masakazu Yoshimura, Teruaki Hayashi, Yota Maeda
CBQ: Cross-Block Quantization for Large Language Models
Xin Ding, Xiaoyu Liu, Zhijun Tu et al.
Learning-Augmented Frequent Directions
Anders Aamand, Justin Chen, Siddharth Gollapudi et al.
MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions
Yekun Chai, Haoran Sun, Huang Fang et al.
Structuring Benchmark into Knowledge Graphs to Assist Large Language Models in Retrieving and Designing Models
Hanmo Liu, Shimin Di, Jialiang Wang et al.
Adaptive Retention & Correction: Test-Time Training for Continual Learning
Haoran Chen, Micah Goldblum, Zuxuan Wu et al.
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Vindula Jayawardana, Baptiste Freydt, Ao Qu et al.
Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do
Yoav Wald, Mark Goldstein, Yonathan Efroni et al.
LR0.FM: LOW-RESOLUTION ZERO-SHOT CLASSIFICATION BENCHMARK FOR FOUNDATION MODELS
Priyank Pathak, Shyam Marjit, Shruti Vyas et al.
LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement
Zhifan Ye, Kejing Xia, Yonggan Fu et al.
Both Supply and Precision: Sample Debias and Ranking Consistency Joint Learning for Large Scale Pre-Ranking System
Feng Gao, Xin Zhou, Yinning Shao et al.
Responsive Dynamic Graph Disentanglement for Metro Flow Forecasting
Qiang Gao, Zizheng Wang, Li Huang et al.
Radar: Fast Long-Context Decoding for Any Transformer
Yongchang Hao, Mengyao Zhai, Hossein Hajimirsadeghi et al.
Learning the Optimal Stopping for Early Classification within Finite Horizons via Sequential Probability Ratio Test
Akinori F. Ebihara, Taiki Miyagawa, Kazuyuki Sakurai et al.
Visually Guided Decoding: Gradient-Free Hard Prompt Inversion with Language Models
Donghoon Kim, Minji Bae, Kyuhong Shim et al.
Tight Time Complexities in Parallel Stochastic Optimization with Arbitrary Computation Dynamics
Alexander Tyurin
Looking Backward: Streaming Video-to-Video Translation with Feature Banks
Feng Liang, Akio Kodaira, Chenfeng Xu et al.
Why Does the Effective Context Length of LLMs Fall Short?
Chenxin An, Jun Zhang, Ming Zhong et al.
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
Caleb Chuck, Fan Feng, Carl Qi et al.
$\text{I}^2\text{AM}$: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Maps
Junseo Park, Hyeryung Jang
Aligned Datasets Improve Detection of Latent Diffusion-Generated Images
Anirudh Sundara Rajan, Utkarsh Ojha, Jedidiah Schloesser et al.
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
YiFan Zhang, Huanyu Zhang, Haochen Tian et al.
MuPT: A Generative Symbolic Music Pretrained Transformer
Xingwei Qu, yuelin bai, Yinghao MA et al.
Order-aware Interactive Segmentation
Bin Wang, Anwesa Choudhuri, Meng Zheng et al.
Discovering Temporally Compositional Neural Manifolds with Switching Infinite GPFA
Changmin Yu, Maneesh Sahani, Máté Lengyel
ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
Seonghwan Park, Jaehyeon Jeong, Yongjun Kim et al.
Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late In Training
Zhanpeng Zhou, Mingze Wang, Yuchen Mao et al.
ImDy: Human Inverse Dynamics from Imitated Observations
Xinpeng Liu, Junxuan Liang, Zili Lin et al.
Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
Binghui Li, Zhixuan Pan, Kaifeng Lyu et al.
Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods
Akira Ito, Masanori Yamada, Atsutoshi Kumagai
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
Satoki Ishikawa, Rio Yokota, Ryo Karakida
Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling
Yuxuan YAO, Han Wu, Mingyang LIU et al.
State Space Model Meets Transformer: A New Paradigm for 3D Object Detection
Chuxin Wang, Wenfei Yang, Xiang Liu et al.
A primer on analytical learning dynamics of nonlinear neural networks
Rodrigo Carrasco-Davis, Erin Grant
Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
Yong Liu, Guo Qin, Xiangdong Huang et al.
Neural Fluid Simulation on Geometric Surfaces
Haoxiang Wang, Tao Yu, Hui Qiao et al.
PWM: Policy Learning with Multi-Task World Models
Ignat Georgiev, Varun Giridhar, Nick Hansen et al.
Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning
Théo Vincent, Fabian Wahren, Jan Peters et al.
Do Contemporary Causal Inference Models Capture Real-World Heterogeneity? Findings from a Large-Scale Benchmark
Haining Yu, Yizhou Sun
Point-based Instance Completion with Scene Constraints
Wesley Khademi, Li Fuxin
Spectral Compressive Imaging via Unmixing-driven Subspace Diffusion Refinement
Haijin Zeng, Benteng Sun, Yongyong Chen et al.
Unifying Causal Representation Learning with the Invariance Principle
Dingling Yao, Dario Rancati, Riccardo Cadei et al.
Deep Signature: Characterization of Large-Scale Molecular Dynamics
Tiexin Qin, Mengxu ZHU, Chunyang Li et al.
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly
James Enouen, Yan Liu
LLMs' Potential Influences on Our Democracy: Challenges and Opportunities
Yujin Potter, David Rand, Yejin Choi et al.
Solving hidden monotone variational inequalities with surrogate losses
Ryan D'Orazio, Danilo Vucetic, Zichu Liu et al.
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Dayal Singh Kalra, Tianyu He, Maissam Barkeshli
Dynamic Low-Rank Sparse Adaptation for Large Language Models
Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.
Identifiability for Gaussian Processes with Holomorphic Kernels
Ameer Qaqish, Didong Li
Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation
Chendi Ge, Xin Wang, Ziwei Zhang et al.
DABL: Detecting Semantic Anomalies in Business Processes Using Large Language Models
Wei Guan, Jian Cao, Jianqi Gao et al.
Is Your Video Language Model a Reliable Judge?
Ming Liu, Wensheng Zhang
Param$\Delta$ for Direct Mixing: Post-Train Large Language Model At Zero Cost
Sheng Cao, Mingrui Wu, Karthik Prasad et al.
Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces
Andy (DiJia) Su, Sainbayar Sukhbaatar, Michael Rabbat et al.
CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair
Mingjie Liu, Yun-Da Tsai, Wenfei Zhou et al.
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Seunghun Lee, Jinyoung Park, Jaewon Chu et al.
Tuning Frequency Bias of State Space Models
Annan Yu, Dongwei Lyu, Soon Hoe Lim et al.
Interpreting the Second-Order Effects of Neurons in CLIP
Yossi Gandelsman, Alexei Efros, Jacob Steinhardt
Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations
Nick Jiang, Anish Kachinthaya, Suzanne Petryk et al.
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
Dennis Frauen, Konstantin Hess, Stefan Feuerriegel
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
Amrith Setlur, Chirag Nagpal, Adam Fisch et al.
Zero-shot Model-based Reinforcement Learning using Large Language Models
Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat et al.
Sufficient Context: A New Lens on Retrieval Augmented Generation Systems
Hailey Joren, Jianyi Zhang, Chun-Sung Ferng et al.
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization
Kim Youwang, Lee Hyun, Kim Sung-Bin et al.
Semantic Aware Representation Learning for Lifelong Learning
Fahad Sarfraz, Elahe Arani, Bahram Zonooz
Detecting Backdoor Samples in Contrastive Language Image Pretraining
Hanxun Huang, Sarah Erfani, Yige Li et al.
The Value of Sensory Information to a Robot
Arjun Krishna, Edward Hu, Dinesh Jayaraman
metabench - A Sparse Benchmark of Reasoning and Knowledge in Large Language Models
Alex Kipnis, Konstantinos Voudouris, Luca Schulze Buschoff et al.
Revolutionizing EMCCD Denoising through a Novel Physics-Based Learning Framework for Noise Modeling
Haiyang Jiang, Tetsuichi Wazawa, Imari Sato et al.
Memory Efficient Transformer Adapter for Dense Predictions
Dong Zhang, Rui Yan, Pingcheng Dong et al.
DiffPuter: Empowering Diffusion Models for Missing Data Imputation
Hengrui Zhang, Liancheng Fang, Qitian Wu et al.
Generating Likely Counterfactuals Using Sum-Product Networks
Jiří Němeček, Tomáš Pevný, Jakub Marecek
The Foundations of Tokenization: Statistical and Computational Concerns
Juan Luis Gastaldi, John Terilla, Luca Malagutti et al.
A General Framework for Off-Policy Learning with Partially-Observed Reward
Rikiya Takehi, Masahiro Asami, Kosuke Kawakami et al.
Rethinking Graph Prompts: Unraveling the Power of Data Manipulation in Graph Neural Networks
Chenyi Zi, Bowen LIU, Xiangguo SUN et al.
Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity
Mutian He, Philip N. Garner
Neural Wave Equation for Irregularly Sampled Sequence Data
Arkaprava Majumdar, M Anand Krishna, P. K. Srijith
Understanding Long Videos with Multimodal Language Models
Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya et al.
Protecting against simultaneous data poisoning attacks
Neel Alex, Muhammad Shoaib Ahmed Siddiqui, Amartya Sanyal et al.
Rethinking Reward Modeling in Preference-based Large Language Model Alignment
Hao Sun, Yunyi Shen, Jean-Francois Ton
X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale
Haoran Xu, Kenton Murray, Philipp Koehn et al.
Semantix: An Energy-guided Sampler for Semantic Style Transfer
Huiang He, Minghui HU, Chuanxia Zheng et al.
Efficient Off-Policy Learning for High-Dimensional Action Spaces
Fabian Otto, Philipp Becker, Vien A Ngo et al.
RandLoRA: Full rank parameter-efficient fine-tuning of large models
Paul Albert, Frederic Zhang, Hemanth Saratchandran et al.
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Yuhan Chen, Yihong Luo, Yifan Song et al.
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory
Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco
Unveiling the Knowledge of CLIP for Training-Free Open-Vocabulary Semantic Segmentation
Yajie Liu, Guodong Wang, Jinjin Zhang et al.
CONGO: Compressive Online Gradient Optimization
Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena et al.
ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts
Yuanchen Wu, Junlong Du, Ke Yan et al.
Edge-aware Image Smoothing with Relative Wavelet Domain Representation
Huiqing Qi, Xiaoliu Luo, Tingting Li et al.
When does compositional structure yield compositional generalization? A kernel theory.
Samuel Lippl, Kimberly Stachenfeld
TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation
Chenghan Li, Mingchen LI, Ruisheng Diao
Provable unlearning in topic modeling and downstream tasks
Stanley Wei, Sadhika Malladi, Sanjeev Arora et al.
Object-Centric Pretraining via Target Encoder Bootstrapping
Nikola Đukić, Tim Lebailly, Tinne Tuytelaars
LASeR: Towards Diversified and Generalizable Robot Design with Large Language Models
JUNRU SONG, Yang Yang, Huan Xiao et al.
Bridging Traffic State and Trajectory for Dynamic Road Network and Trajectory Representation Learning
Chengkai Han, Jingyuan Wang, Yongyao Wang et al.
Unaligned Message-Passing and Contextualized-Pretraining for Robust Geo-Entity Resolution
Yuwen Ji, Wenbo Xie, Jiaqi Zhang et al.
PiCO: Peer Review in LLMs based on Consistency Optimization
Kun-Peng Ning, Shuo Yang, Yuyang Liu et al.
Can We Ignore Labels in Out of Distribution Detection?
Hong Yang, Qi Yu, Travis Desell
SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels
Xiangyu Dong, Xingyi Zhang, Lei Chen et al.
ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
Pengwei Tang, Xiaolin Hu, Yong Liu
Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation
Kim Yong Tan, YUEMING LYU, Ivor Tsang et al.
Competitive Fair Scheduling with Predictions
Tianming Zhao, Chunqiu xia, Xiaomin Chang et al.
Online-to-Offline RL for Agent Alignment
Xu Liu, Haobo Fu, Stefano V. Albrecht et al.
On the Benefits of Memory for Modeling Time-Dependent PDEs
Ricardo Buitrago Ruiz, Tanya Marwah, Albert Gu et al.
The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG
Francesco Carzaniga, Gary Hoppeler, Michael Hersche et al.
Do LLMs have Consistent Values?
Naama Rozen, Liat Bezalel, Gal Elidan et al.
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems
Dan MacKinlay, Russell Tsuchida, Daniel Pagendam et al.
Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers
Quoc-Vinh Lai-Dang, Taemin Kang, Seungah Son
A Causal Lens for Learning Long-term Fair Policies
Jacob Lear, Lu Zhang
ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization
The Viet Bui, Thanh Nguyen, Tien Mai
ControlAR: Controllable Image Generation with Autoregressive Models
Zongming Li, Tianheng Cheng, Shoufa Chen et al.
Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies
Lingwei Zhu, Han Wang, Yukie Nagai
Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models
Yuda Song, Hanlin Zhang, Carson Eisenach et al.
RetroInText: A Multimodal Large Language Model Enhanced Framework for Retrosynthetic Planning via In-Context Representation Learning
Chenglong Kang, Xiaoyi Liu, Fei Guo
PhyloLM: Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks
Nicolas Yax, Pierre-Yves Oudeyer, Stefano Palminteri
Improving Text-to-Image Consistency via Automatic Prompt Optimization
Melissa Hall, Michal Drozdzal, Oscar Mañas et al.
OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination
Tobias Gessler, Tin Dizdarevic, Ani Calinescu et al.
Score-based free-form architectures for high-dimensional Fokker-Planck equations
Feng Liu, Faguo Wu, Xiao Zhang
ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample $V$-Ensemble
Tianyuan Chen, Ronglong Cai, Faguo Wu et al.
Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence
Dharmesh Tailor, Alvaro Correia, Eric Nalisnick et al.
Reveal Object in Lensless Photography via Region Gaze and Amplification
Xiangjun Yin, Huihui Yue
Vertical Federated Learning with Missing Features During Training and Inference
Pedro Valdeira, Shiqiang Wang, Yuejie Chi
Going Beyond Feature Similarity: Effective Dataset distillation based on Class-aware Conditional Mutual Information
Xinhao Zhong, Bin Chen, Hao Fang et al.
Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning
Shangding Gu, Laixi Shi, Muning Wen et al.
See Through Their Minds: Learning Transferable Brain Decoding Models from Cross-Subject fMRI
Yulong Liu, Yongqiang Ma, Guibo Zhu et al.
Open-Set Graph Anomaly Detection via Normal Structure Regularisation
Qizhou Wang, Guansong Pang, Mahsa Salehi et al.
Balancing Bias in Two-sided Markets for Fair Stable Matchings
Siyuan Wu, Leong Hou U, Panagiotis Karras
KBLaM: Knowledge Base augmented Language Model
Xi Wang, Taketomo Isazawa, Liana Mikaelyan et al.
PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding
Wei Chow, Jiageng Mao, Boyi Li et al.
From Complexity to Clarity: Analytical Expressions of Deep Neural Network Weights via Clifford Algebra and Convexity
Mert Pilanci
PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
Ségolène Martin, Anne Gagneux, Paul Hagemann et al.
Building Blocks of Differentially Private Training
Mahmoud Hegazy, Aymeric Dieuleveut
Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.
Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
Amin Soleimani Abyaneh, Mahrokh Boroujeni, Hsiu-Chin Lin et al.
Vision and Language Synergy for Rehearsal Free Continual Learning
Muhammad Anwar Masum, Mahardhika Pratama, Savitha Ramasamy et al.
SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding
Jian Chen, Ruiyi Zhang, Yufan Zhou et al.
Fourier Head: Helping Large Language Models Learn Complex Probability Distributions
Nate Gillman, Daksh Aggarwal, Michael Freeman et al.
Minimalistic Predictions for Online Class Constraint Scheduling
Dorian Guyot, Alexandra Lassota
Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning
Berken Utku Demirel, Christian Holz
Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks
Hanling Tian, Yuhang Liu, Mingzhen He et al.
Find A Winning Sign: Sign Is All We Need to Win the Lottery
Junghun Oh, Sungyong Baik, Kyoung Mu Lee
SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement
Antonis Antoniades, Albert Örwall, Kexun Zhang et al.
Handling Delay in Real-Time Reinforcement Learning
Ivan Anokhin, Rishav Rishav, Matt Riemer et al.
Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
Andrew Jesson, Nicolas Beltran-Velez, David Blei
Video Action Differencing
James Burgess, Xiaohan Wang, Yuhui Zhang et al.
Recovery of Causal Graph Involving Latent Variables via Homologous Surrogates
Xiuchuan Li, Jun Wang, Tongliang Liu
GenEx: Generating an Explorable World
TaiMing Lu, Tianmin Shu, Alan Yuille et al.
Training LLMs over Neurally Compressed Text
Brian Lester, Jaehoon Lee, Jeffrey Pennington et al.
Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement
Kotaro Yoshida, Yuji Naraki, Takafumi Horie et al.
Instance-dependent Early Stopping
Suqin Yuan, Runqi Lin, Lei Feng et al.
SFS: Smarter Code Space Search improves LLM Inference Scaling
Jonathan Light, Yue Wu, Yiyou Sun et al.
TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking
Danqing Wang, Jianxin Ma, Fei Fang et al.
OCCAM: Towards Cost-Efficient and Accuracy-Aware Classification Inference
Dujian Ding, Bicheng Xu, Laks Lakshmanan
StringLLM: Understanding the String Processing Capability of Large Language Models
Xilong Wang, Hao Fu, Jindong Wang et al.
Personalized Visual Instruction Tuning
Renjie Pi, Jianshu Zhang, Tianyang Han et al.