Most Cited 2025 "style-content separation" Papers

Linear Recurrences Accessible to Everyone

Felix Sarnthein

The Ramanujan Library - Automated Discovery on the Hypergraph of Integer Relations

Itay Beit Halachmi, Ido Kaminer

Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations

Julius Aka, Johannes Brunnemann, Jörg Eiden et al.

More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing

Sagi Shaier, Francisco Pereira, Katharina Kann et al.

Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models

Tianqi Chen, Shujian Zhang, Mingyuan Zhou

Has the Deep Neural Network learned the Stochastic Process? An Evaluation Viewpoint

Harshit Kumar, Beomseok Kang, Biswadeep Chakraborty et al.

Beyond Mere Token Analysis: A Hypergraph Metric Space Framework for Defending Against Socially Engineered LLM Attacks

Manohar Kaul, Aditya Saibewar, Sadbhavana Babar

OLMoE: Open Mixture-of-Experts Language Models

Niklas Muennighoff, Luca Soldaini, Dirk Groeneveld et al.

O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions

Gen Li, Yuling Yan

SINGAPO: Single Image Controlled Generation of Articulated Parts in Objects

Jiayi Liu, Denys Iliash, Angel Chang et al.

One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs

Linbao Li, Yannan Liu, Daojing He et al.

Scalable Extraction of Training Data from Aligned, Production Language Models

Milad Nasr, Javier Rando, Nicholas Carlini et al.

Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model

Chunming He, Chengyu Fang, Yulun Zhang et al.

Gap Preserving Distillation by Building Bidirectional Mappings with A Dynamic Teacher

Yong Guo, Shulian Zhang, Haolin Pan et al.

Causal Graphical Models for Vision-Language Compositional Understanding

Fiorenzo Parascandolo, Nicholas Moratelli, Enver Sangineto et al.

A Unified Theory of Quantum Neural Network Loss Landscapes

Eric Anschuetz

Bias Mitigation in Graph Diffusion Models

Meng Yu, Kun Zhan

VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models

Lisa Dunlap, Krishna Mandal, trevor darrell et al.

Improved Sampling Algorithms for Lévy-Itô Diffusion Models

Vadim Popov, Assel Yermekova, Tasnima Sadekova et al.

Counterfactual Realizability

Arvind Raghavan, Elias Bareinboim

MMD-Regularized Unbalanced Optimal Transport

SakethaNath Jagarlapudi, Pratik Jawanpuria, Piyushi Manupriya

Variance-Reducing Couplings for Random Features

Isaac Reid, Stratis Markou, Krzysztof Choromanski et al.

Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces

Saket Tiwari, Omer Gottesman, George D Konidaris

Differentiable and Learnable Wireless Simulation with Geometric Transformers

Thomas Hehn, Markus Peschl, Tribhuvanesh Orekondy et al.

Do vision models perceive objects like toddlers ?

Arthur Aubret, Jochen Triesch

Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval

Pengcheng Jiang, Cao (Danica) Xiao, Minhao Jiang et al.

Bayesian Optimization via Continual Variational Last Layer Training

Paul Brunzema, Mikkel Jordahn, John Willes et al.

Relation-Aware Diffusion for Heterogeneous Graphs with Partially Observed Features

Daeho Um, Yoonji Lee, Jiwoong Park et al.

TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Ivan Rubachev, Nikolay Kartashev, Yury Gorishniy et al.

NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals

Jaden Fiotto-Kaufman, Alexander Loftus, Eric Todd et al.

GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks

Dingyi Zhuang, Chonghe Jiang, Yunhan Zheng et al.

Learning to Discover Regulatory Elements for Gene Expression Prediction

Xingyu Su, Haiyang Yu, Degui Zhi et al.

Improved Training Technique for Latent Consistency Models

Minh Quan Dao, Khanh Doan, Di Liu et al.

Does Training with Synthetic Data Truly Protect Privacy?

Yunpeng Zhao, Jie Zhang

Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles

Buu Phan, Brandon Amos, Itai Gat et al.

MA$^2$E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder

Sehyeok Kang, Yongsik Lee, Gahee Kim et al.

Rapid Selection and Ordering of In-Context Demonstrations via Prompt Embedding Clustering

Kha Pham, Hung Le, Man Ngo et al.

Plug, Play, and Generalize: Length Extrapolation with Pointer-Augmented Neural Memory

Svetha Venkatesh, Kien Do, Hung Le et al.

FlickerFusion: Intra-trajectory Domain Generalizing Multi-agent Reinforcement Learning

Woosung Koh, Wonbeen Oh, Siyeol Kim et al.

Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold

Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams et al.

A deep inverse-mapping model for a flapping robotic wing

Hadar Sharvit, Raz Karl, Tsevi Beatus

Robust Transfer of Safety-Constrained Reinforcement Learning Agents

Markel Zubia, Thiago Simão, Nils Jansen

On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning

Bokun Wang, Yunwen Lei, Yiming Ying et al.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics

Keyi Shen, Jiangwei Yu, Jose Barreiros et al.

Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning

Bahare Fatemi, Seyed Mehran Kazemi, Anton Tsitsulin et al.

Mind the GAP: Glimpse-based Active Perception improves generalization and sample efficiency of visual reasoning

Oleh Kolner, Thomas Ortner, Stanisław Woźniak et al.

Brain Bandit: A Biologically Grounded Neural Network for Efficient Control of Exploration

Chen Jiang, Jiahui An, Yating Liu et al.

Regularization by Texts for Latent Diffusion Inverse Solvers

Jeongsol Kim, Geon Yeong Park, Hyungjin Chung et al.

Partial Gromov-Wasserstein Metric

Yikun Bai, Rocio Diaz Martin, Abihith Kothapalli et al.

Differential Transformer

Tianzhu Ye, Li Dong, Yuqing Xia et al.

Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation

Yikun Zhang, Geyan Ye, Chaohao Yuan et al.

Demystifying the Token Dynamics of Deep Selective State Space Models

Thieu Vo, Duy-Tung Pham, Xin Tong et al.

Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization

Yury Demidovich, Petr Ostroukhov, Grigory Malinovsky et al.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision

Yaowen Ye, Cassidy Laidlaw, Jacob Steinhardt

Towards Unbiased Calibration using Meta-Regularization

Jacek Golebiowski, Cheng Wang

Improving Pretraining Data Using Perplexity Correlations

Tristan Thrush, Christopher Potts, Tatsunori Hashimoto

Retri3D: 3D Neural Graphics Representation Retrieval

Yushi Guan, Daniel Kwan, Jean Dandurand et al.

On the Price of Differential Privacy for Hierarchical Clustering

Chengyuan Deng, Jie Gao, Jalaj Upadhyay et al.

MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures

Anvith Thudi, Chris Maddison

Improving Unsupervised Constituency Parsing via Maximizing Semantic Information

Junjie Chen, Xiangheng He, Yusuke Miyao et al.

Cross-Domain Off-Policy Evaluation and Learning for Contextual Bandits

Yuta Natsubori, Masataka Ushiku, Yuta Saito

Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them

Anh Bui, Thuy-Trang Vu, Long Vuong et al.

Efficient Top-m Data Values Identification for Data Selection

Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng et al.

Learning to Search from Demonstration Sequences

Dixant Mittal, Liwei Kang, Wee Sun Lee

An Information Criterion for Controlled Disentanglement of Multimodal Data

Chenyu Wang, Sharut Gupta, Xinyi Zhang et al.

Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models

Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa et al.

Generalized Consistency Trajectory Models for Image Manipulation

Beomsu Kim, Jaemin Kim, Jeongsol Kim et al.

NeurFlow: Interpreting Neural Networks through Neuron Groups and Functional Interactions

Tue Cao, Nhat Hoang-Xuan, Hieu Pham et al.

HyperPLR: Hypergraph Generation through Projection, Learning, and Reconstruction

Weihuang Wen, Tianshu Yu

Semi-Parametric Retrieval via Binary Bag-of-Tokens Index

Jiawei Zhou, Li Dong, Furu Wei et al.

M^3PC: Test-time Model Predictive Control using Pretrained Masked Trajectory Model

Kehan Wen, Yutong Hu, Yao Mu et al.

RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks

Nazia Tasnim, Bryan Plummer

Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space

Zhiliang Chen, Xinyuan Niu, Chuan Sheng Foo et al.

Scaling LLM Test-Time Compute Optimally Can be More Effective than Scaling Parameters for Reasoning

Charlie Snell, Jaehoon Lee, Kelvin Xu et al.

Progressive Token Length Scaling in Transformer Encoders for Efficient Universal Segmentation

Abhishek Aich, Yumin Suh, Samuel Schulter et al.

Toward Guidance-Free AR Visual Generation via Condition Contrastive Alignment

Huayu Chen, Hang Su, Peize Sun et al.

Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation

Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai et al.

Intermediate Layer Classifiers for OOD generalization

Arnas Uselis, Seong Joon Oh

Jamba: Hybrid Transformer-Mamba Language Models

Barak Lenz, Opher Lieber, Alan Arazi et al.

A Curious Case of the Missing Measure: Better Scores and Worse Generation

Joseph Turian, Jordie Shier

HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting

Nian Ran, Peng Xiao, Yue Wang et al.

ViSAGe: Video-to-Spatial Audio Generation

Jaeyeon Kim, Heeseung Yun, Gunhee Kim

Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models

Sumeet Singh, Vikas Sindhwani, Stephen Tu

Shallow diffusion networks provably learn hidden low-dimensional structure

Nicholas Boffi, Arthur Jacot, Stephen Tu et al.

Deep Kernel Posterior Learning under Infinite Variance Prior Weights

Jorge Loría, Anindya Bhadra

Credit-based self organizing maps: training deep topographic networks with minimal performance degradation

Amir Ozhan Dehghani, Xinyu Qian, Asa Farahani et al.

Privacy Auditing of Large Language Models

Ashwinee Panda, Xinyu Tang, Christopher Choquette-Choo et al.

Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching

Enshu Liu, Xuefei Ning, Yu Wang et al.

TexTailor: Customized Text-aligned Texturing via Effective Resampling

Suin Lee, DAE SHIK KIM

ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation

Tianchen Zhao, Tongcheng Fang, Haofeng Huang et al.

PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos

Alex N. Wang, Christopher Hoang, Yuwen Xiong et al.

OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models

Junda Wu, Xintong Li, Ruoyu Wang et al.

Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs

Xuandong Zhao, Lei Li, Yu-Xiang Wang

Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator

xin zhang, Jiawei Du, Ping Liu et al.

Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Fangyu Lei, Jixuan Chen, Yuxiao Ye et al.

How do we interpret the outputs of a neural network trained on classification?

Yudi Xie

ONLINE EPSILON NET & PIERCING SET FOR GEOMETRIC CONCEPTS

Sujoy Bhore, Devdan Dey, Satyam Singh

Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization

Jiajun Fan, Shuaike Shen, Chaoran Cheng et al.

Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF

Tengyang Xie, Dylan Foster, Akshay Krishnamurthy et al.

PPT: Patch Order Do Matters In Time Series Pretext Task

Jaeho Kim, Kwangryeol Park, Sukmin Yun et al.

Immunogenicity Prediction with Dual Attention Enables Vaccine Target Selection

Song Li, Yang Tan, Song Ke et al.

Counterfactual Concept Bottleneck Models

Gabriele Dominici, Pietro Barbiero, Francesco Giannini et al.

“I Am the One and Only, Your Cyber BFF”: Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AI

Myra Cheng, Alicia DeVrio, Lisa Egede et al.

Predicate Hierarchies Improve Few-Shot State Classification

Emily Jin, Joy Hsu, Jiajun Wu

On the Modeling Capabilities of Large Language Models for Sequential Decision Making

Martin Klissarov, R Devon Hjelm, Alexander Toshev et al.

Learning Causal Alignment for Reliable Disease Diagnosis

Mingzhou Liu, Ching-Wen Lee, Xinwei Sun et al.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency

Qixin ZHANG, Zongqi Wan, Yu Yang et al.

YouTube-SL-25: A Large-Scale, Open-Domain Multilingual Sign Language Parallel Corpus

Garrett Tanzer, Biao Zhang

Towards Unbiased Learning in Semi-Supervised Semantic Segmentation

Rui Sun, Huayu Mai, Wangkai Li et al.

Chain-of-Focus Prompting: Leveraging Sequential Visual Cues to Prompt Large Autoregressive Vision Models

Jiyang Zheng, Jialiang Shen, Yu Yao et al.

On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models

Xu-Hui Liu, Yali Du, Jun Wang et al.

Multi-modal Learning: A Look Back and the Road Ahead

Divyam Madaan, Sumit Chopra, Kyunghyun Cho

Correlation and Navigation in the Vocabulary Key Representation Space of Language Models

Letian Peng, Chenyang An, Jingbo Shang

LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch

caigao jiang, Xiang Shu, Hong Qian et al.

OPTAMI: Global Superlinear Convergence of High-order Methods

Dmitry Kamzolov, Artem Agafonov, Dmitry Pasechnyuk et al.

SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization

Hong Qian, Yiyi Zhu, Xiang Shu et al.

Emergent Orientation Maps —— Mechanisms, Coding Efficiency and Robustness

Haixin Zhong, Haoyu Wang, Wei Dai et al.

Do not write that jailbreak paper

Javier Rando

It Helps to Take a Second Opinion: Teaching Smaller LLMs To Deliberate Mutually via Selective Rationale Optimisation

Sohan Patnaik, Milan Aggarwal, Sumit Bhatia et al.

Learning Partial Graph Matching via Optimal Partial Transport

Gathika Ratnayaka, James Nichols, Qing Wang

MTSAM: Multi-Task Fine-Tuning for Segment Anything Model

Xuehao Wang, Zhan ZHUANG, Feiyang YE et al.

HeadMap: Locating and Enhancing Knowledge Circuits in LLMs

Xuehao Wang, Liyuan Wang, Binghuai Lin et al.

Learning to Explore and Exploit with GNNs for Unsupervised Combinatorial Optimization

Utku Umur Acikalin, Aaron Ferber, Carla Gomes

Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning

Xinyue Wang, Biwei Huang

HiRA: Parameter-Efficient Hadamard High-Rank Adaptation for Large Language Models

Qiushi Huang, Tom Ko, Zhan ZHUANG et al.

Sharpness-Aware Black-Box Optimization

Feiyang YE, YUEMING LYU, Xuehao Wang et al.

Better Instruction-Following Through Minimum Bayes Risk

Ian Wu, Patrick Fernandes, Amanda Bertsch et al.

Long-Short Decision Transformer: Bridging Global and Local Dependencies for Generalized Decision-Making

Jincheng Wang, Penny Karanasou, Pengyuan Wei et al.

Collab: Controlled Decoding using Mixture of Agents for LLM Alignment

Souradip Chakraborty, Sujay Bhatt, Udari Sehwag et al.

VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration

Dezhan Tu, Danylo Vashchilenko, Yuzhe Lu et al.

Joint Gradient Balancing for Data Ordering in Finite-Sum Multi-Objective Optimization

Hansi Yang, James Kwok

Hierarchically Encapsulated Representation for Protocol Design in Self-Driving Labs

Yu-Zhe Shi, Mingchen Liu, Fanxu Meng et al.

Manifold Constraint Reduces Exposure Bias in Accelerated Diffusion Sampling

Divergence of Neural Tangent Kernel in Classification Problems

Zixiong Yu, Songtao Tian, Guhan Chen

Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics

Alireza Mousavi-Hosseini, Denny Wu, Murat A Erdogdu

DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback

GUOJUN XIONG, Ujwal Dinesha, Debajoy Mukherjee et al.

Sensitivity-Aware Amortized Bayesian Inference

Lasse Elsemüller, Hans Olischläger, Marvin Schmitt et al.

LLM Unlearning via Loss Adjustment with Only Forget Data

Yaxuan Wang, Jiaheng Wei, Yuhao Liu et al.

Denoising Levy Probabilistic Models

Dario Shariatian, Umut Simsekli, Alain Oliviero Durmus

Why In-Context Learning Models are Good Few-Shot Learners?

Shiguang Wu, Yaqing Wang, Quanming Yao

Co$^{\mathbf{3}}$Gesture: Towards Coherent Concurrent Co-speech 3D Gesture Generation with Interactive Diffusion

Xingqun Qi, Yatian Wang, Hengyuan Zhang et al.

Latent Action Pretraining from Videos

Seonghyeon Ye, Joel Jang, Byeongguk Jeon et al.

Do WGANs succeed because they minimize the Wasserstein Distance? Lessons from Discrete Generators

Ariel Elnekave, Yair Weiss

The Illustrated AlphaFold

Elana Simon, Jake Silberg

Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation

Anish Abhijit Diwan, Julen Urain, Jens Kober et al.

Improved Convergence Rate for Diffusion Probabilistic Models

Gen Li, Yuchen Jiao

SymDiff: Equivariant Diffusion via Stochastic Symmetrisation

Leo Zhang, Kianoosh Ashouritaklimi, Yee Whye Teh et al.

Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors

Sungyoon Lee, Sokbae Lee

Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents

Dongjun Lee, Juyong Lee, Kyuyoung Kim et al.

Efficient Neuron Segmentation in Electron Microscopy by Affinity-Guided Queries

Hang Chen, Chufeng Tang, Xiao Li et al.

Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series

Byoungwoo Park, Hyungi Lee, Juho Lee

Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models

Chuan Liu, Chunshu Wu, shihui cao et al.

Effective post-training embedding compression via temperature control in contrastive training

georgiana dinu, Corey Barrett, Yi Xiang et al.

In vivo cell-type and brain region classification via multimodal contrastive learning

Han Yu, Hanrui Lyu, YiXun Xu et al.

LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision

Mateusz Pach, Koryna Lewandowska, Jacek Tabor et al.

DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL

Mathias Jackermeier, Alessandro Abate

FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware

Korbinian Pöppel, Maximilian Beck, Sepp Hochreiter

MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark

Sakshi, Utkarsh Tyagi, Sonal Kumar et al.

MatExpert: Decomposing Materials Discovery By Mimicking Human Experts

Qianggang Ding, Santiago Miret, Bang Liu

Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL

Cevahir Koprulu, Franck Djeumou, ufuk topcu

Robust Root Cause Diagnosis using In-Distribution Interventions

Lokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi et al.

Efficient and Robust Neural Combinatorial Optimization via Wasserstein-Based Coresets

Xu Wang, Fuyou Miao, Wenjie Liu et al.

Safety-Prioritizing Curricula for Constrained Reinforcement Learning

Cevahir Koprulu, Thiago Simão, Nils Jansen et al.

Transformers Provably Learn Two-Mixture of Linear Classification via Gradient Flow

Hongru Yang, Zhangyang Wang, Jason Lee et al.

Forewarned is Forearmed: Harnessing LLMs for Data Synthesis via Failure-induced Exploration

Qintong Li, Jiahui Gao, Sheng Wang et al.

CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction

Hyukjun Lim, Sun Kim, Sangseon Lee

Provable Uncertainty Decomposition via Higher-Order Calibration

Gustaf Ahdritz, Aravind Gollakota, Parikshit Gopalan et al.

SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction

Lu Dai, Yijie Xu, Jinhui Ye et al.

Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment

Dongyoung Kim, Kimin Lee, Jinwoo Shin et al.

Synthesizing Realistic fMRI: A Physiological Dynamics-Driven Hierarchical Diffusion Model for Efficient fMRI Acquisition

Yufan Hu, Jiang, Wuyang Li et al.

HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics

Fan, Sarah Martinson, Erik Wang et al.

Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention

Weitai Kang, Mengxue Qu, Jyoti Kini et al.

How to visualize training dynamics in neural networks

Michael Hu, Shreyans Jain, Sangam Chaulagain et al.

AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data

Tuan Truong, Rithwik Sudharsan, Yibo Yang et al.

Private Mechanism Design via Quantile Estimation

Yuanyuan Yang, Tao Xiao, Bhuvesh Kumar et al.

SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation

Jaehong Yoon, Shoubin Yu, Vaidehi Ramesh Patil et al.

Following the Human Thread in Social Navigation

Luca Scofano, Alessio Sampieri, Tommaso Campari et al.

Population Transformer: Learning Population-level Representations of Neural Activity

Geeling Chau, Christopher Wang, Sabera Talukder et al.

Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search

Jonathan Light, Min Cai, Weiqin Chen et al.

ReAttention: Training-Free Infinite Context with Finite Attention Scope

Xiaoran Liu, Ruixiao Li, Zhigeng Liu et al.

PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans

Giang Nguyen, Valerie Chen, Mohammad Reza Taesiri et al.

PIORF: Physics-Informed Ollivier-Ricci Flow for Long–Range Interactions in Mesh Graph Neural Networks

Youn-Yeol Yu, Jeongwhan Choi, Jaehyeon Park et al.

Multi-Field Adaptive Retrieval

Millicent Li, Tongfei Chen, Ben Van Durme et al.

Learning General-purpose Biomedical Volume Representations using Randomized Synthesis

Neel Dey, Benjamin Billot, Hallee Wong et al.

ST-GCond: Self-supervised and Transferable Graph Dataset Condensation

Beining Yang, Qingyun Sun, Cheng Ji et al.

A new framework for evaluating model out-of-distribution generalisation for the biochemical domain

Raul Fernandez-Diaz, Hoang Thanh Lam, Vanessa Lopez et al.

Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment

Naoya Hasegawa, Issei Sato

Duoduo CLIP: Efficient 3D Understanding with Multi-View Images

Han-Hung Lee, Yiming Zhang, Angel Chang

Conformal Structured Prediction

Botong Zhang, Shuo Li, Osbert Bastani

Straightness of Rectified Flow: A Theoretical Insight into Wasserstein Convergence

Saptarshi Roy, Vansh Bansal, Purnamrita Sarkar et al.

Rare event modeling with self-regularized normalizing flows: what can we learn from a single failure?

Charles Dawson, Van Tran, Max Li et al.

SOREL: A Stochastic Algorithm for Spectral Risks Minimization

Yuze Ge, Rujun Jiang

FairDen: Fair Density-Based Clustering

Lena Krieger, Anna Beer, Pernille Matthews et al.

Discrete Copula Diffusion

Anji Liu, Oliver Broadrick, Mathias Niepert et al.

Learn hybrid prototypes for multivariate time series anomaly detection

Ke-Yuan Shen

Transformer Block Coupling and its Correlation with Generalization in LLMs

Murdock Aubry, Haoming Meng, Anton Sugolov et al.

ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidance

Jiannan Huang, Jun Hao Liew, Hanshu Yan et al.

Provence: efficient and robust context pruning for retrieval-augmented generation

Nadezhda Chirkova, Thibault Formal, Vassilina Nikoulina et al.

Aligned LLMs Are Not Aligned Browser Agents

Priyanshu Kumar, Elaine Lau, Saranya Vijayakumar et al.

Three-in-One: Fast and Accurate Transducer for Hybrid-Autoregressive ASR

Hainan Xu, Travis Bartley, Vladimir Bataev et al.