Most Cited 2025 "autoregressive image modeling" Papers
22,274 papers found • Page 107 of 112
Conference
Shifting Time: Time-series Forecasting with Khatri-Rao Neural Operators
Srinath Dama, Kevin L Course, Prasanth B Nair
iN2V: Bringing Transductive Node Embeddings to Inductive Graphs
Nicolas Lell, Ansgar Scherp
Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More
Geonhui Yoo, Minhak Song, Chulhee Yun
Provable Benefit of Random Permutations over Uniform Sampling in Stochastic Coordinate Descent
Donghwa Kim, Jaewook Lee, Chulhee Yun
Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
Yeseul Cho, Baekrok Shin, Changmin Kang et al.
AutoCATE: End-to-End, Automated Treatment Effect Estimation
Toon Vanderschueren, Tim Verdonck, Mihaela van der Schaar et al.
Where is the Truth? The Risk of Getting Confounded in a Continual World
Florian Peter Busch, Roshni Ramanna Kamath, Rupert Mitchell et al.
Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity
Qiuhao Wang, Yuqi Zha, Chin Pang Ho et al.
Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
Tyler Kastner, Mark Rowland, Yunhao Tang et al.
What can large language models do for sustainable food?
Anna Thomas, Adam Yee, Andrew Mayne et al.
Sample-Optimal Agnostic Boosting with Unlabeled Data
Udaya Ghai, Karan Singh
Discrete Neural Algorithmic Reasoning
Gleb Rodionov, Liudmila Prokhorenkova
Multi-View Graph Clustering via Node-Guided Contrastive Encoding
Yazhou Ren, Junlong Ke, Zichen Wen et al.
TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree
Yu-Yang Qian, Yuan-Ze Xu, Zhen-Yu Zhang et al.
Hybrid Quantum-Classical Multi-Agent Pathfinding
Thore Gerlach, Loong Kuan Lee, Frederic BARBARESCO et al.
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye, Yujia Jin, Alekh Agarwal et al.
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane et al.
Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks
Yixin Cheng, Hongcheng Guo, Yangming Li et al.
An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints
Jiahui Zhu, Kihyun Yu, Dabeen Lee et al.
Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations
Jason Qin, Hans-Hermann Wessels, Carlos Fernandez-Granda et al.
KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors
Benson Chen, Tomasz Danel, Gabriel Dreiman et al.
Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models
Shuoyuan Wang, Sharon Li, Hongxin Wei
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca et al.
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
Changdae Oh, zhen fang, Shawn Im et al.
Steer LLM Latents for Hallucination Detection
Seongheon Park, Xuefeng Du, Min-Hsuan Yeh et al.
CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries
Ni Mu, Hao Hu, Xiao Hu et al.
Towards a Formal Theory of Representational Compositionality
Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio et al.
Reinforcement Learning with Adaptive Reward Modeling for Expensive-to-Evaluate Systems
Hongyuan Su, Yu Zheng, Yuan Yuan et al.
Cover learning for large-scale topology representation
Luis Scoccola, Uzu Lim, Heather Harrington
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei, Ke Ma, Yingfei Sun et al.
Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality Metrics
Aleksandr Gushchin, Khaled Abud, Georgii Bychkov et al.
BDC-CLIP: Brownian Distance Covariance for Adapting CLIP to Action Recognition
Fei Long, Xiaoou Li, jiaming Lv et al.
Quadratic Upper Bound for Boosting Robustness
Euijin You, Hyang-Won Lee
Compute or Load KV Cache? Why Not Both?
Shuowei Jin, Xueshen Liu, Qingzhao Zhang et al.
Prediction-Powered Adaptive Shrinkage Estimation
Sida Li, Nikolaos Ignatiadis
Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curves
Mykhailo Uss, Ruslan Yermolenko, Oleksii Shashko et al.
CVE-Bench: A Benchmark for AI Agents’ Ability to Exploit Real-World Web Application Vulnerabilities
Yuxuan Zhu, Antony Kellermann, Dylan Bowman et al.
Backdoor Attacks in Token Selection of Attention Mechanism
Yunjuan Wang, Raman Arora
Differentiable Structure Learning with Ancestral Constraints
Taiyu Ban, Changxin Rong, Xiangyu Wang et al.
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
Sebastian Farquhar, Vikrant Varma, David Lindner et al.
Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
Aditya Taparia, Som Sagar, Ransalu Senanayake
Independence Tests for Language Models
Sally Zhu, Ahmed Ahmed, Rohith Kuditipudi et al.
QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration
HamidReza Imani, Jiaxin Peng, Peiman Mohseni et al.
Stability and Generalization Analysis of Decentralized SGD: Sharper Bounds Beyond Lipschitzness and Smoothness
Shuang Zeng, Yunwen Lei
Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan
PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design
Zhenqiao Song, Tianxiao Li, Lei Li et al.
Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
Marta Gentiloni Silveri, Antonio Ocello
Robust Secure Swap: Responsible Face Swap With Persons of Interest Redaction and Provenance Traceability
Yunshu Dai, Jianwei Fei, Fangjun Huang et al.
Stronger Neyman Regret Guarantees for Adaptive Experimental Design
Georgy Noarov, Riccardo Fogliato, Martin A Bertran et al.
When, Where and Why to Average Weights?
Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du et al.
Vintix: Action Model via In-Context Reinforcement Learning
Andrei Polubarov, Nikita Lyubaykin, Alexander Derevyagin et al.
Minimum Width for Universal Approximation using Squashable Activation Functions
Jonghyun Shin, Namjun Kim, Geonho Hwang et al.
Permutation-Free High-Order Interaction Tests
Zhaolu Liu, Robert Peach, Mauricio Barahona
Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks
Rohit Sonker, Alexandre Capone, Andrew Rothstein et al.
On the Learnability of Distribution Classes with Adaptive Adversaries
Tosca Lechner, Alex Bie, Gautam Kamath
Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs
Xun Wang, Jing Xu, Franziska Boenisch et al.
RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
Quan Wei, Chung-Yiu Yau, Hoi To Wai et al.
Towards Attributions of Input Variables in a Coalition
Xinhao Zheng, Huiqi Deng, Quanshi Zhang
B-score: Detecting biases in large language models using response history
An Vo, Mohammad Reza Taesiri, Daeyoung Kim et al.
NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernel
Gabriel Thompson, Kai Yue, Chau-Wai Wong et al.
R.I.P.: Better Models by Survival of the Fittest Prompts
Ping Yu, Weizhe Yuan, Olga Golovneva et al.
From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning
Noa Rubin, Kirsten Fischer, Javed Lindner et al.
Diversified Flow Matching with Translation Identifiability
Sagar Shrestha, Xiao Fu
Data-Driven Selection of Instrumental Variables for Additive Nonlinear, Constant Effects Models
Xichen Guo, Feng Xie, Yan Zeng et al.
The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
Shiwei Li, Xiandi Luo, Haozhao Wang et al.
Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation
Bohan Lyu, Yadi Cao, Duncan Watson-Parris et al.
Discovering Spoofing Attempts on Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab et al.
Integration-free Kernels for Equivariant Gaussian Process Modelling
Tim Steinert, David Ginsbourger, August Lykke-Møller et al.
Copilot Arena: A Platform for Code LLM Evaluation in the Wild
Wayne Chi, Valerie Chen, Anastasios Angelopoulos et al.
Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments
Mikel Malagón, Josu Ceberio, Jose A Lozano
Instance Correlation Graph-based Naive Bayes
Chengyuan Li, Liangxiao Jiang, Wenjun Zhang et al.
Graph Minimum Factor Distance and Its Application to Large-Scale Graph Data Clustering
Jicong Fan
A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features
Ihab Bendidi, Yassir El Mesbahi, Alisandra Denton et al.
Discovering Physics Laws of Dynamical Systems via Invariant Function Learning
Shurui Gui, Xiner Li, Shuiwang Ji
Human-Aligned Image Models Improve Visual Decoding from the Brain
Nona Rajabi, Antonio Ribeiro, Miguel Vasco et al.
Primal-Dual Neural Algorithmic Reasoning
Yu He, Ellen Vitercik
Test-Time Learning for Large Language Models
Jinwu Hu, Zitian Zhang, Guohao Chen et al.
The Batch Complexity of Bandit Pure Exploration
Adrienne Tuynman, Rémy Degenne
Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
Juha Harviainen, Frank Sommer, Manuel Sorge et al.
ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks
Saurabh Jha, Rohan Arora, Yuji Watanabe et al.
Minerva: A Programmable Memory Test Benchmark for Language Models
Menglin Xia, Victor Ruehle, Saravanakumar Rajmohan et al.
NeuralCohort: Cohort-aware Neural Representation Learning for Healthcare Analytics
Changshuo Liu, Lingze Zeng, Kaiping Zheng et al.
Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees
Thien Nguyen, Huy Nguyen
Interaction-Aware Gaussian Weighting for Clustered Federated Learning
Alessandro Licciardi, Davide Leo, Eros Fanì et al.
Private Federated Learning using Preference-Optimized Synthetic Data
Charlie Hou, Mei-Yu Wang, Yige Zhu et al.
EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations
Haotian Zhai, Connor Lawless, Ellen Vitercik et al.
Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery
Pratinav Seth, Michelle Lin, BREFO YAW et al.
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
Yifeng Wang, Xueying Zhan, Siyu Huang
Solving Zero-Sum Convex Markov Games
Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp et al.
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces
Rashid Mushkani, Perampalli Shravan Nayak, Hugo Berard et al.
Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves
Amer Krivosija, Alexander Munteanu, André Nusser et al.
Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach
Xu Zhang, Kaidi Xu, Ziqing Hu et al.
A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity
Yufei Huang, Changhu Wang, Junjie Tang et al.
Towards Global-level Mechanistic Interpretability: A Perspective of Modular Circuits of Large Language Models
Yinhan He, Wendy Zheng, Yushun Dong et al.
Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis
Christophe Vauthier, Anna Korba, Quentin Mérigot
Density Ratio Estimation with Conditional Probability Paths
Hanlin Yu, Arto Klami, Aapo Hyvarinen et al.
LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
Xinyue Zeng, Haohui Wang, Junhong Lin et al.
Generative Social Choice: The Next Generation
Niclas Boehmer, Sara Fish, Ariel Procaccia
UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
Fangchen Yu, Yanzhen Chen, Jiaxing Wei et al.
TabFlex: Scaling Tabular Learning to Millions with Linear Attention
Yuchen Zeng, Tuan Dinh, Wonjun Kang et al.
Not All Wrong is Bad: Using Adversarial Examples for Unlearning
Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran
In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Shen et al.
Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction
Yudong W Xu, Wenhao Li, Scott Sanner et al.
Efficiently Vectorized MCMC on Modern Accelerators
Hugh Dance, Pierre Glaser, Peter Orbanz et al.
Understanding Complexity in VideoQA via Visual Program Generation
Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave et al.
Optimization for Neural Operators can Benefit from Width
Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee
Reasoning-as-Logic-Units: Scaling Test-Time Reasoning in Large Language Models Through Logic Unit Alignment
Cheryl Li, Tianyuan Xu, Yiwen Guo
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg et al.
Proto Successor Measure: Representing the Behavior Space of an RL Agent
Siddhant Agarwal, Harshit Sikchi, Peter Stone et al.
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
Yitian Zhang, Liheng Ma, Antonios Valkanas et al.
Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective
Steve Azzolin, SAGAR MALHOTRA, Andrea Passerini et al.
Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective
Hao Dai, Jagmohan Chauhan
Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms
Kei Sen Fong, Mehul Motani
Towards Cost-Effective Reward Guided Text Generation
Ahmad Rashid, Ruotian Wu, Rongqi Fan et al.
Adaptive Data Collection for Robust Learning Across Multiple Distributions
Chengbo Zang, Mehmet Turkcan, Gil Zussman et al.
The Best of Both Worlds: Bridging Quality and Diversity in Data Selection with Bipartite Graph
Minghao Wu, Thuy-Trang Vu, Lizhen Qu et al.
The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products
YuQing Xie, Ameya Daigavane, Mit Kotak et al.
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik et al.
Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics
Puli Wang, Yu Qi, Yueming Wang et al.
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
Jiawei Zhang, Xuan Yang, Taiqi Wang et al.
Nemotron-CORTEXA: Enhancing LLM Agents for Software Engineering Tasks via Improved Localization and Solution Diversity
Atefeh Sohrabizadeh, Jialin Song, Mingjie Liu et al.
One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
Gabriel Kasmi, Amandine Brunetto, Thomas Fel et al.
TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks
Mathilde Papillon, Guillermo Bernardez, Claudio Battiloro et al.
Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
Yunzhen Yao, Lie He, Michael Gastpar
Whitened CLIP as a Likelihood Surrogate of Images and Captions
Roy Betser, Meir Yossef Levi, Guy Gilboa
EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
Leo de Castro, Daniel Escudero, Adya Agrawal et al.
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu, Zhichao Huang, Mathieu Salzmann et al.
Universal Neural Optimal Transport
Jonathan Geuter, Gregor Kornhardt, Ingimar Tomasson et al.
Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems
Botao Chen, Jongyeong Lee, Junya Honda
Synthetic Text Generation for Training Large Language Models via Gradient Matching
Dang Nguyen, Zeman Li, MohammadHossein Bateni et al.
An analytic theory of creativity in convolutional diffusion models
Mason Kamb, Surya Ganguli
Measuring In-Context Computation Complexity via Hidden State Prediction
Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber
Teaching Transformers Causal Reasoning through Axiomatic Training
Aniket Vashishtha, Abhinav Kumar, Atharva Pandey et al.
Training Deep Learning Models with Norm-Constrained LMOs
Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos et al.
MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification
Suchith Chidananda Prabhu, Bhavyajeet Singh, Anshul Mittal et al.
CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging
Wenju Sun, Qingyong Li, Yangliao Geng et al.
SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields
David K Park, Xihaier Luo, Guang Zhao et al.
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
Jacopo Talpini, Marco Savi, Giovanni Neglia
Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
Youran Dong, Junfeng Yang, Wei Yao et al.
POQD: Performance-Oriented Query Decomposer for Multi-vector retrieval
Yaoyang Liu, Junlin Li, Yinjun Wu et al.
Dynamic Similarity Graph Construction with Kernel Density Estimation
Steinar Laenen, Peter Macgregor, He Sun
The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning
Dulhan Jayalath, Gilad Landau, Brendan Shillingford et al.
Federated Learning for Feature Generalization with Convex Constraints
Dongwon Kim, Donghee Kim, Sung Kuk Shyn et al.
Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
Siddarth Venkatraman, Mohsin Hasan, Minsu Kim et al.
CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition
Zebin Wang, Menghan Lin, Bolin Shen et al.
On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving
Yeonju Ro, Zhenyu Zhang, Souvik Kundu et al.
DIS-CO: Discovering Copyrighted Content in VLMs Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing
Dongliang Guo, Mengxuan Hu, Zihan Guan et al.
WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs
Lukas Thede, Karsten Roth, Matthias Bethge et al.
Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks
Etienne Boursier, Nicolas Flammarion
Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
Xunkai Li, Zhengyu Wu, Kaichi Yu et al.
TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation
Hyeongwon Jang, Changhun Kim, Eunho Yang
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead
Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee
Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning
Mengmeng Chen, Xiaohu Wu, QIQI LIU et al.
Time-Aware World Model for Adaptive Prediction and Control
Anh Nhu, Sanghyun Son, Ming Lin
Minimalist Concept Erasure in Generative Models
Yang Zhang, Er Jin, Yanfei Dong et al.
Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions
Supratim Shit, Gurmehak chadha, Surendra kumar et al.
Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio et al.
Highly Compressed Tokenizer Can Generate Without Training
Lukas Lao Beyer, Tianhong Li, Xinlei Chen et al.
Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
Shyam Nuggehalli, Jifan Zhang, Lalit Jain et al.
ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning
Yuchen Lin, Ronan Le Bras, Kyle Richardson et al.
Strong and Weak Identifiability of Optimization-based Causal Discovery in Non-linear Additive Noise Models
Mingjia Li, Hong Qian, Tian-Zuo Wang et al.
Resolving Lexical Bias in Model Editing
Hammad Rizwan, Domenic Rosati, Ga Wu et al.
Nearly Optimal Sample Complexity for Learning with Label Proportions
Robert Busa-Fekete, Travis Dick, Claudio Gentile et al.
Scalable Private Partition Selection via Adaptive Weighting
Justin Chen, Vincent Cohen-Addad, Alessandro Epasto et al.
FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials
Seung Lee, Hojoon Kim, Yutack Park et al.
GSM-$\infty$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?
Yang Zhou, Hongyi Liu, Zhuoming Chen et al.
On the Local Complexity of Linear Regions in Deep ReLU Networks
Niket Patel, Guido Montufar
Safely Learning Optimal Auctions: A Testable Learning Framework for Mechanism Design
Vikram Kher, Manolis Zampetakis
PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
Aaron Wenteler, Martina Occhetta, Nikhil Branson et al.
Perceptual-GS: Scene-adaptive Perceptual Densification for Gaussian Splatting
Hongbi ZHOU, Zhangkai NI
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Beguelin et al.
Scaling Trends in Language Model Robustness
Nikolaus Howe, Ian McKenzie, Oskar Hollinsworth et al.
Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering
Yaoqin He, Junchen Fu, Kaiwen Zheng et al.
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
KaShun SHUM, Yuzhen Huang, Hongjian Zou et al.
Graph-Based Algorithms for Diverse Similarity Search
Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy et al.
BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare
Yanchao Tan, Hang Lv, Yunfei Zhan et al.
Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts
Mateo Espinosa Zarlenga, Gabriele Dominici, Pietro Barbiero et al.
Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation
D. Sculley, William Cukierski, Phil Culliton et al.
The Power of Random Features and the Limits of Distribution-Free Gradient Descent
Ari Karchmer, Eran Malach
scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data
Olga Ovcharenko, Florian Barkmann, Philip Toma et al.
SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning
Jinpeng Chen, Runmin Cong, Yuzhi Zhao et al.
MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge
Yue Dai, Liang Liu, Xulong Tang et al.
Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems
Huigen Ye, Hua Xu, An Yan et al.
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
Jie Wang, March Boedihardjo, Yao Xie
I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian et al.
Unnatural Languages Are Not Bugs but Features for LLMs
Keyu Duan, Yiran Zhao, Zhili Feng et al.
TokenSwift: Lossless Acceleration of Ultra Long Sequence Generation
Tong Wu, Junzhe Shen, Zixia Jia et al.
Robot-Gated Interactive Imitation Learning with Adaptive Intervention Mechanism
Haoyuan Cai, Zhenghao Peng, Bolei Zhou
Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance
Lisha Chen, Quan Xiao, Ellen Fukuda et al.
Quantum Algorithms for Finite-horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock et al.
Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data
Mohammad Hosseini, Maryam Shanechi
LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation
Piyush Lalitkumar Tiwary, Kinjawl Bhattacharyya, Prathosh AP
Does learning the right latent variables necessarily improve in-context learning?
Sarthak Mittal, Eric Elmoznino, Léo Gagnon et al.
Feedforward Few-shot Species Range Estimation
Christian Lange, Max Hamilton, Elijah Cole et al.
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N
Tianyu Zhang, Andrew Williams, Phillip Wozny et al.
TopInG: Topologically Interpretable Graph Learning via Persistent Rationale Filtration
Cheng Xin, Fan Xu, Xin Ding et al.
GMAIL: Generative Modality Alignment for generated Image Learning
Shentong Mo, Sukmin Yun
Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity
Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini et al.