Most Cited 2025 "k-space data" Papers
22,274 papers found • Page 92 of 112
Conference
Is uniform expressivity too restrictive? Towards efficient expressivity of GNNs
Sammy Khalife, Josué Tonelli-Cueto
Tuning Frequency Bias of State Space Models
Annan Yu, Dongwei Lyu, Soon Hoe Lim et al.
Denoising Task Difficulty-based Curriculum for Training Diffusion Models
Jin-Young Kim, Hyojun Go, Soonwoo Kwon 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.
Knowledge Entropy Decay during Language Model Pretraining Hinders New Knowledge Acquisition
Jiyeon Kim, Hyunji Lee, Hyowon Cho et al.
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
Dennis Frauen, Konstantin Hess, Stefan Feuerriegel
Interpretable Causal Representation Learning for Biological Data in the Pathway Space
Jesus de la Fuente Cedeño, Robert Lehmann, Carlos Ruiz-Arenas et al.
MCNC: Manifold-Constrained Reparameterization for Neural Compression
Chayne Thrash, Reed Andreas, Ali Abbasi et al.
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
Amrith Setlur, Chirag Nagpal, Adam Fisch et al.
Adaptive Rank Allocation: Speeding Up Modern Transformers with RaNA Adapters
Roberto Garcia, Jerry Liu, Daniel Sorvisto et al.
UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation
Huimin LU, Masaru Isonuma, Junichiro Mori et al.
A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization
Aron Brenner, Rahman Khorramfar, Jennifer Sun et al.
TSC-Net: Prediction of Pedestrian Trajectories by Trajectory-Scene-Cell Classification
BO HU, Tat-Jen Cham
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
Hyunsu Kim, Giung Nam, Chulhee Yun et al.
The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning
Youssef Allouah, Joshua Kazdan, Rachid Guerraoui et al.
Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
Haoran He, Can Chang, Huazhe Xu et al.
Adaptive Gradient Clipping for Robust Federated Learning
Youssef Allouah, Rachid Guerraoui, Nirupam Gupta 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
An Effective Manifold-based Optimization Method for Distributionally Robust Classification
Jiawei Huang, Hu Ding
MambaExtend: A Training-Free Approach to Improve Long Context Extension of Mamba
Seyedarmin Azizi, Souvik Kundu, Mohammad Sadeghi et al.
Detecting Backdoor Samples in Contrastive Language Image Pretraining
Hanxun Huang, Sarah Erfani, Yige Li et al.
Mitigating Spurious Correlations in Zero-Shot Multimodal Models
Shenyu Lu, Junyi Chai, Xiaoqian Wang
Test-Time Adaptation for Combating Missing Modalities in Egocentric Videos
Merey Ramazanova, Alejandro Pardo, Bernard Ghanem et al.
The Value of Sensory Information to a Robot
Arjun Krishna, Edward Hu, Dinesh Jayaraman
QPM: Discrete Optimization for Globally Interpretable Image Classification
Thomas Norrenbrock, Timo Kaiser, Sovan Biswas et al.
metabench - A Sparse Benchmark of Reasoning and Knowledge in Large Language Models
Alex Kipnis, Konstantinos Voudouris, Luca Schulze Buschoff et al.
Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels
Daning Huang, Hanyang He, John Harlim et al.
Steering LLMs' Behavior with Concept Activation Vectors
Ruixuan HUANG, Shuai Wang
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.
GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation
Tao Feng, Yihang Sun, Jiaxuan You
DiffPuter: Empowering Diffusion Models for Missing Data Imputation
Hengrui Zhang, Liancheng Fang, Qitian Wu et al.
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
Juntong Shi, Minkai Xu, Harper Hua et al.
Holistically Evaluating the Environmental Impact of Creating Language Models
Jacob Morrison, Clara Na, Jared Fernandez et al.
Generating Likely Counterfactuals Using Sum-Product Networks
Jiří Němeček, Tomáš Pevný, Jakub Marecek
A Sanity Check for AI-generated Image Detection
Shilin Yan, Ouxiang Li, Jiayin Cai et al.
Conformalized Survival Analysis for General Right-Censored Data
Hen Davidov, Shai Feldman, Gil Shamai et al.
The Foundations of Tokenization: Statistical and Computational Concerns
Juan Luis Gastaldi, John Terilla, Luca Malagutti et al.
MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs
Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf et al.
POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition
Yuta Saito, Jihan Yao, Thorsten Joachims
A General Framework for Off-Policy Learning with Partially-Observed Reward
Rikiya Takehi, Masahiro Asami, Kosuke Kawakami et al.
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
André Hottung, Mridul Mahajan, Kevin Tierney
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
How many samples are needed to train a deep neural network?
Pegah Golestaneh, Mahsa Taheri, Johannes Lederer
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 Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models
Mazda Moayeri, Sriram Balasubramanian, Samyadeep Basu et al.
On Calibration of LLM-based Guard Models for Reliable Content Moderation
Hongfu Liu, Hengguan Huang, Xiangming Gu et al.
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices
Frida Viset, Frederiek Wesel, Arno Solin et al.
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.
Searching for Optimal Solutions with LLMs via Bayesian Optimization
Dhruv Agarwal, Manoj Ghuhan Arivazhagan, Rajarshi Das 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
A Theory of Initialisation's Impact on Specialisation
Devon Jarvis, Sebastian Lee, Clementine Domine et al.
Non-Equilibrium Dynamics of Hybrid Continuous-Discrete Ground-State Sampling
Timothee Leleu, Sam Reifenstein
Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models
Francisco Eiras, Aleksandar Petrov, Philip Torr et al.
Disentangling 3D Animal Pose Dynamics with Scrubbed Conditional Latent Variables
Joshua Wu, Hari Koneru, James Ravenel et al.
Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling
David Grangier, Simin Fan, Skyler Seto et al.
Feedback Favors the Generalization of Neural ODEs
Jindou Jia, Zihan Yang, Meng Wang et al.
MaestroMotif: Skill Design from Artificial Intelligence Feedback
Martin Klissarov, Mikael Henaff, Roberta Raileanu et al.
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
Iman Mirzadeh, Keivan Alizadeh-Vahid, Hooman Shahrokhi 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.
ChartMoE: Mixture of Diversely Aligned Expert Connector for Chart Understanding
Zhengzhuo Xu, Bowen Qu, Yiyan Qi et al.
CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning
Fanxu Meng, Muhan Zhang
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
Mentored Learning: Improving Generalization and Convergence of Student Learner
Xiaofeng Cao, Yaming Guo, Heng Tao Shen et al.
Scaling Laws for Adversarial Attacks on Language Model Activations and Tokens
Stanislav Fort
TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation
Chenghan Li, Mingchen LI, Ruisheng Diao
Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning
Calarina Muslimani, Matthew E Taylor
Root Cause Analysis of Anomalies in Multivariate Time Series through Granger Causal Discovery
Xiao Han, Saima Absar, Lu Zhang et al.
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
LLaVA-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models
Feng Li, Renrui Zhang, Hao Zhang et al.
Towards Automated Knowledge Integration From Human-Interpretable Representations
Katarzyna Kobalczyk, Mihaela van der Schaar
Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples
Yangming Li, Max Ruiz Luyten, Mihaela van der Schaar
What's New in My Data? Novelty Exploration via Contrastive Generation
Masaru Isonuma, Ivan Titov
Pacmann: Efficient Private Approximate Nearest Neighbor Search
Mingxun Zhou, Elaine Shi, Giulia Fanti
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
SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation
Jongmin Lee, Meiqi Sun, Pieter Abbeel
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
Should VLMs be Pre-trained with Image Data?
Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre et al.
Competitive Fair Scheduling with Predictions
Tianming Zhao, Chunqiu xia, Xiaomin Chang et al.
Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement
Stathis Megas, Daniel Chen, Krzysztof Polanski et al.
Online-to-Offline RL for Agent Alignment
Xu Liu, Haobo Fu, Stefano V. Albrecht et al.
URLOST: Unsupervised Representation Learning without Stationarity or Topology
Zeyu Yun, Juexiao Zhang, Yann LeCun et al.
Examining Alignment of Large Language Models through Representative Heuristics: the case of political stereotypes
Sullam Jeoung, Yubin Ge, Haohan Wang et al.
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
Anming Gu, Edward Chien, Kristjan Greenewald
Laplace Sample Information: Data Informativeness Through a Bayesian Lens
Johannes Kaiser, Kristian Schwethelm, Daniel Rueckert 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.
Multilevel Generative Samplers for Investigating Critical Phenomena
Ankur Singha, Elia Cellini, Kim A. Nicoli 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
ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization
The Viet Bui, Thanh Nguyen, Tien Mai
Global Identifiability of Overcomplete Dictionary Learning via L1 and Volume Minimization
Yuchen Sun, Kejun Huang
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
Connectome Mapping: Shape-Memory Network via Interpretation of Contextual Semantic Information
Kyungsu Lee, Haeyun Lee, Jae Youn Hwang
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
OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination
Tobias Gessler, Tin Dizdarevic, Ani Calinescu et al.
Select before Act: Spatially Decoupled Action Repetition for Continuous Control
Buqing Nie, Yangqing Fu, Yue Gao
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
Operator Deep Smoothing for Implied Volatility
Ruben Wiedemann, Antoine (Jack) Jacquier, Lukas Gonon
Vertical Federated Learning with Missing Features During Training and Inference
Pedro Valdeira, Shiqiang Wang, Yuejie Chi
Exploiting Hidden Symmetry to Improve Objective Perturbation for DP Linear Learners with a Nonsmooth L1-Norm
Du Chen, Geoffrey A. Chua
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.
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
Shicong Cen, Jincheng Mei, Katayoon Goshvadi et al.
Continual Slow-and-Fast Adaptation of Latent Neural Dynamics (CoSFan): Meta-Learning What-How & When to Adapt
Ryan Missel, Linwei Wang
GeoLoRA: Geometric integration for parameter efficient fine-tuning
Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti et al.
Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs
Levi Rauchwerger, Stefanie Jegelka, Ron Levie
Open-Set Graph Anomaly Detection via Normal Structure Regularisation
Qizhou Wang, Guansong Pang, Mahsa Salehi et al.
Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages
Xiang Yue, Yueqi Song, Akari Asai et al.
Towards more rigorous evaluations of language models
Desi R Ivanova, Ilija Ilievski, Momchil Konstantinov
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.
The Belief State Transformer
Edward Hu, Kwangjun Ahn, Qinghua Liu 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.
Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
Deep Networks Learn Features From Local Discontinuities in the Label Function
Prithaj Banerjee, Harish G Ramaswamy, Mahesh Yadav et al.
Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models
Junyu Chen, Han Cai, Junsong Chen et al.
SIMPL: Scalable and hassle-free optimisation of neural representations from behaviour
Tom George, Pierre Glaser, Kimberly Stachenfeld 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.
Vision and Language Synergy for Rehearsal Free Continual Learning
Muhammad Anwar Masum, Mahardhika Pratama, Savitha Ramasamy et al.
RESuM: A Rare Event Surrogate Model for Physics Detector Design
Ann-Kathrin Schuetz, Alan Poon, Aobo Li
SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding
Jian Chen, Ruiyi Zhang, Yufan Zhou et al.
Causal Identification for Complex Functional Longitudinal Studies
Andrew Ying
Taming Overconfidence in LLMs: Reward Calibration in RLHF
Jixuan Leng, Chengsong Huang, Banghua Zhu et al.
Fourier Head: Helping Large Language Models Learn Complex Probability Distributions
Nate Gillman, Daksh Aggarwal, Michael Freeman et al.
Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning
Sheng Li, Qitao Tan, Yue Dai et al.
TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies
Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang et al.
Minimalistic Predictions for Online Class Constraint Scheduling
Dorian Guyot, Alexandra Lassota
XAIguiFormer: explainable artificial intelligence guided transformer for brain disorder identification
Hanning Guo, Farah Abdellatif, Yu Fu et al.
Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning
Berken Utku Demirel, Christian Holz
Underdamped Diffusion Bridges with Applications to Sampling
Denis Blessing, Julius Berner, Lorenz Richter et al.
Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks
Hanling Tian, Yuhang Liu, Mingzhen He et al.
GraphArena: Evaluating and Exploring Large Language Models on Graph Computation
Jianheng Tang, Qifan Zhang, Yuhan Li et al.
GDrag:Towards General-Purpose Interactive Editing with Anti-ambiguity Point Diffusion
Xiaojian Lin, Hanhui Li, Yuhao Cheng 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
Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs
Yuheng Zhang, Nan Jiang
Mechanistic Interpretability Meets Vision Language Models: Insights and Limitations
Yiming Liu, Yuhui Zhang, Serena Yeung
A Little Goes a Long Way: Efficient Long Context Training and Inference with Partial Contexts
Suyu Ge, Xihui Lin, Yunan Zhang et al.
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.
Autoregressive Pretraining with Mamba in Vision
Sucheng Ren, Xianhang Li, Haoqin Tu 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.
YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary
Hao-Tang Tsui, Chien-Yao Wang, Hong-Yuan Liao
TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking
Danqing Wang, Jianxin Ma, Fei Fang et al.
Causal Representation Learning from Multimodal Biomedical Observations
Yuewen Sun, Lingjing Kong, Guangyi Chen et al.
How much of my dataset did you use? Quantitative Data Usage Inference in Machine Learning
Yao Tong, Jiayuan Ye, Sajjad Zarifzadeh 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.
PFGuard: A Generative Framework with Privacy and Fairness Safeguards
Soyeon Kim, Yuji Roh, Geon Heo et al.
Factual Context Validation and Simplification: A Scalable Method to Enhance GPT Trustworthiness and Efficiency
Tianyi Huang
Neuron based Personality Trait Induction in Large Language Models
Jia Deng, Tianyi Tang, Yanbin Yin et al.
Support is All You Need for Certified VAE Training
Changming Xu, Debangshu Banerjee, Deepak Vasisht et al.
SmartPretrain: Model-Agnostic and Dataset-Agnostic Representation Learning for Motion Prediction
Yang Zhou, Hao Shao, Letian Wang et al.
Scaling In-the-Wild Training for Diffusion-based Illumination Harmonization and Editing by Imposing Consistent Light Transport
Lvmin Zhang, Anyi Rao, Maneesh Agrawala
Sparse components distinguish visual pathways & their alignment to neural networks
Ammar I Marvi, Nancy Kanwisher, Meenakshi Khosla
GaussianAnything: Interactive Point Cloud Flow Matching for 3D Generation
Yushi LAN, Shangchen Zhou, Zhaoyang Lyu et al.
LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Yukang Chen, Fuzhao Xue, Dacheng Li et al.
Identifying latent state transitions in non-linear dynamical systems
Çağlar Hızlı, Çağatay Yıldız, Matthias Bethge et al.
Selective Task Group Updates for Multi-Task Optimization
Wooseong Jeong, Kuk-Jin Yoon
From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation
Xingchen Wan, Han Zhou, Ruoxi Sun et al.
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
Satoki Ishikawa, Makoto Yamada, Han Bao et al.
Self-Supervised Diffusion Models for Electron-Aware Molecular Representation Learning
Gyoung S. Na, Chanyoung Park
REFINE: Inversion-Free Backdoor Defense via Model Reprogramming
Yukun Chen, Shuo Shao, Enhao Huang et al.
Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training
Maximillian Chen, Ruoxi Sun, Tomas Pfister et al.
Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior
Yuliang Xu, Jian Kang
Explore Theory of Mind: program-guided adversarial data generation for theory of mind reasoning
Melanie Sclar, Jane Dwivedi-Yu, Maryam Fazel-Zarandi et al.