AAAI 2026

4,920 papers

Physics-Informed Approach for Exploratory Hamilton–Jacobi–Bellman Equations via Policy Iterations

Yeongjong Kim, Namkyeong Cho, Minseok Kim, Yeoneung Kim

Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption

Sunwoo Kim, Soo Yong Lee, Kyungho Kim, Hyunjin Hwang, Jaemin Yoo

Client-level Active Error Correction in Distributed Learning

Kwang In Kim

A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm

Junhyung Lyle Kim, Nai-Hui Chia, Anastasios Kyrillidis

TabFlash: Efficient Table Understanding with Progressive Question Conditioning and Token Focusing

Jongha Kim, Minseong Bae, Sanghyeok Lee, Jinsung Yoon, Hyunwoo J. Kim

BD-Net: Has Depth-Wise Convolution Ever Been Applied in Binary Neural Networks?

Doyoung Kim, Jin-Seop Lee, Noo-ri Kim, SungJoon Lee, Jee-Hyong Lee

Step-by-step Layered Design Generation

Faizan Farooq Khan, Joseph K J, Koustava Goswami, Mohamed Elhoseiny, Balaji Vasan Srinivasan

GLANCE: Global Actions in a Nutshell for Counterfactual Explainability

Loukas Kavouras, Eleni Psaroudaki, Konstantinos Tsopelas, Dimitrios Rontogiannis, Nikolaos Theologitis

Detecting the Future: All-at-Once Event Sequence Forecasting with Horizon Matching

Ivan Karpukhin, Andrey Savchenko

Policy Zooming: Adaptive Discretization-based Infinite-Horizon Average-Reward Reinforcement Learning

Avik Kar, Rahul Singh

HiCL: Hippocampal-Inspired Continual Learning

Kushal Kapoor, Wyatt Mackey, Yiannis Aloimonos, Xiaomin Lin

GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation

Sungmin Kang, Jisoo Kim, Salman Avestimehr, Sunwoo Lee

Understanding and Enhancing Differentiable Architecture Search from Information Bottleneck Perspective

Haidong Kang, Lianbo Ma, Pengjun Chen, Qiang He, Bo Yi

Sparse Additive Model Pruning for Order-Based Causal Structure Learning

Kentaro Kanamori, Hirofumi Suzuki, Takuya Takagi

Quantum Transformer for Molecular Learning: Multi-Configuration Ground-State Energy Prediction

Yuichi Kamata, Quoc Hoan Tran, Yasuhiro Endo, Hirotaka Oshima

HALO: Hardware-Aware Quantization with Low Critical-Path-Delay Weights for LLM Acceleration

Rohan Juneja, Shivam Aggarwal, Safeen Huda, Tulika Mitra, Li-Shiuan Peh

EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models

Linglin Jing, Yuting Gao, Zhigang Wang, Wang Lan, Yiwen Tang

Signal Enhancement via Multi-view Dynamic Representation and Alignment-aware Fusion

Zikun Jin, Yuhua Qian, Xinyan Liang, Jiaqian Zhang, Jinpeng Yuan

SMIDT: High-Performance Inference Framework for MoE Models with Dynamic Top-K Routing

Zewen Jin, Shen Fu, Chengjie Tang, Youhui Bai, Shengnan Wang

Partial Action Replacement: Tackling Distribution Shift in Offline MARL

Yue Jin, Giovanni Montana

GeoNum: Bridging Numerical Continuity and Language Semantics via Geometric Embedding

Shengkai Jin, Tianyu Chen, Chonghan Gao, JUN HAN

Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projection

Pengfei Jin, Peng Shu, Sifan Song, Sekeun Kim, Qing Xiao

Addressing Polarization and Unfairness in Performative Prediction

Kun Jin, Tian Xie, Yang Liu, Xueru Zhang

Revisiting Differentiable Structure Learning: Inconsistency of L1 Penalty and Beyond

Kaifeng Jin, Ignavier Ng, Kun Zhang, Biwei Huang

A-FloPS: Accelerating Diffusion Models via Adaptive Flow Path Sampler

Cheng Jin, Zhenyu Xiao, Yuantao Gu

DeepProofLog: Efficient Proving in Deep Stochastic Logic Programs

Ying Jiao, Rodrigo Castellano Ontiveros, Luc De Raedt, Marco Gori, Francesco Giannini

DiffBench Meets DiffAgent: End-to-End LLM-Driven Diffusion Acceleration Code Generation

Jiajun Jiao, Haowei Zhu, Puyuan Yang, Jianghui Wang, Ji Liu

Multi-agent In-context Coordination via Decentralized Memory Retrieval

Tao Jiang, Zichuan Lin, Lihe Li, Yi-Chen Li, Cong Guan

UQ-ViT: Harmonizing Extreme Activations with Hardware-Friendly Uniform Quantization in Vision Transformers

Tao Jiang, Yucheng Jiang, Xiwen Yao, Gong Cheng, Junwei Han

Multi-Label Classification with Incremental and Decremental Features

Mingdie Jiang, Quanjiang Li, Tingjin Luo, Yiping Song, Chenping Hou

DAPrompt: Dual Alignment Prompt of Structure and Semantics for Few-shot Graph Learning

Lifan Jiang, Mengying Zhu, Yangyang Wu, Xuan Liu, Xiaolin Zheng

Variational OOD State Correction for Offline Reinforcement Learning

Ke Jiang, Wen Jiang, Xiaoyang Tan

Towards Better IncomLDL: We Are Unaware of Hidden Labels in Advance

Jiecheng Jiang, Jiawei Tang, Jiahao Jiang, Hui LIU, Junhui Hou

FD-MAGRPO: Functionality-Driven Multi-Agent Group Relative Policy Optimization for Analog-LDO Sizing

Haoning Jiang, Han Wu, Zhuoli Ouyang, Ziheng Wang, Tinghuan Chen

Refine-IQA: Multi-Stage Reinforcement Finetuning for Perceptual Image Quality Assessment

Ziheng Jia, Jiaying Qian, Zicheng Zhang, Zijian Chen, Xiongkuo Min

Scaling-up Perceptual Video Quality Assessment

Ziheng Jia, Zicheng Zhang, Xiaorong Zhu, Chunyi Li, Jinliang Han

Benchmarking Multimodal Knowledge Conflict for Large Multimodal Models

Yifan Jia, Yuntao Du, Kailin Jiang, Yuyang Liang, Qihan Ren

Cost-Sensitive Conformal Training with Provably Controllable Learning Bounds

Xuesong Jia, Yuanjie Shi, Ziquan Liu, Yi Xu, Yan Yan

M3Time: LLM-Enhanced Multi-Modal, Multi-Scale, and Multi-Frequency Multivariate Time Series Forecasting

Shuning Jia, Baijun Song, Canming Ye, Chun Yuan

PrAda-GAN: A Private Adaptive Generative Adversarial Network with Bayes Network Structure

Ke Jia, Yuheng Ma, Yang Li, Feifei Wang

PAGPL: Privacy-Aware Graph Prompt Learning Scheme via Adaptive Perturbation-Estimated Topology Recovery

Ju Jia, Jiansen Song, Jingxuan Yu, Jiabao Guo, Xiaoshuang Jia

STrans: Spontaneous Architecture Evolution for Adaptive Time Series Forecasting

Haoyi Jia

Optimized Algorithms for Text Clustering with LLM-Generated Constraints

Chaoqi Jia, Weihong Wu, Longkun Guo, Zhigang Lu, Chao Chen

Diff-V2M: A Hierarchical Conditional Diffusion Model with Explicit Rhythmic Modeling for Video-to-Music Generation

Shulei Ji, Zihao Wang, Jiaxing Yu, Xiangyuan Yang, Shuyu Li

HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning

Qirui Ji, Bin Qin, Yifan Jin, Yunze Zhao, Chuxiong Sun

Multi-View Differential Mixing and Graph-Guided Structural Region Selection for Cross-Modal Alignment

Linlin Ji, Li Liu

Jump-teaching: Combating Sample Selection Bias via Temporal Disagreement

Kangye Ji, Fei Cheng, Zeqing Wang, Qichang Zhang, Bohu Huang

CANVAS: A Benchmark for Vision-Language Models on Tool-Based User Interface Design

Daeheon Jeong, Seoyeon Byun, Kihoon Son, Dae Hyun Kim, Juho Kim

An Information Theoretic Evaluation Metric for Strong Unlearning

Dongjae Jeon, Wonje Jeung, Taeheon Kim, Albert No, Jonghyun Choi

LILAD: Learning In-context Lyapunov-stable Adaptive Dynamics Models

Amit Jena, Na Li, Le Xie

Enhancing Chemical Explainability Through Counterfactual Masking

Łukasz Janisiów, Marek Kochańczyk, Bartosz Michał Zieliński, Tomasz Danel

Quantifying and Improving Adaptivity in Conformal Prediction Through Input Transformations

Sooyong Jang, Insup Lee

On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples

Cheongjae Jang, Jonghyun Won, Soyeon Jun, Chun Kee Chung, Keehyoung Joo

FedPM: Federated Learning Using Second-order Optimization with Preconditioned Mixing of Local Parameters

Hiro Ishii, Kenta Niwa, Hiroshi Sawada, Akinori Fujino, Noboru Harada

Oxytrees: Model Trees for Bipartite Learning

Pedro Ilídio, Felipe Kenji Nakano, Alireza Gharahighehi, Robbe D'hondt, Ricardo Cerri

Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games

Bingyu Hui, Lebin Yu, Quanming Yao, Yunpeng Qu, Xudong Zhang

Wasserstein-Aware Transfer: Class-Level Alignment for Robust Diffusion Model Adaptation

Zixian Huang, Chuan-Xian Ren

FedSDWC: Federated Synergistic Dual-Representation Weak Causal Learning for OOD

Zhenyuan Huang, Hui Zhang, Wenzhong Tang, Haijun Yang

Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning

Yi Huang, Qingyun Sun, Yisen Gao, Haonan Yuan, Xingcheng Fu

M2FMoE: Multi-Resolution Multi-View Frequency Mixture-of-Experts for Extreme-Adaptive Time Series Forecasting

Yaohui Huang, Runmin Zou, Yun Wang, Laeeq Aslam, Ruipeng Dong

Federated Linear Dueling Bandits

Xuhan Huang, Yan Hu, Zhiyan Li, Zhiyong Wang, Zhongxiang Dai

PhysicsCorrect: A Training-Free Approach for Stable Neural PDE Simulations

Xinquan Huang, Paris Perdikaris

FedRNC: Addressing Spatio-Temporal Label Misalignment in Federated Noisy Class-Incremental Learning

Xingwei Huang, Zhaobin Sun, Junjie Shi, Xin Yang, Zengqiang Yan

CoLM: Collaborative Large Models via a Client-Server Paradigm

Siqi Huang, Sida Huang, Hongyuan Zhang

Feature Attribution for Human Sensing with Radio Signals

Shuokang Huang, Julie McCann

Sparse Poisson Gamma Belief Networks for High-Dimensional Sparse Count Data

Rui Huang, Dian Meng, Xun Zhou, Sikun Yang

HMformer: Unleashing Transformer’s Potential for Time Series Forecasting via Hierarchical Multi-Scale Modeling

Renjun Huang, Han Xiao, Bingqing Li, Baili Zhang, Jianhua Lyu

Trimming the Fat: Redundancy-Aware Acceleration Framework for DGNNs

Renhong Huang, Yuxuan Cao, Yi Li, Junwei Hu, Zihua Xiong

Function-on-Function Bayesian Optimization

Jingru Huang, Haijie Xu, Manrui Jiang, Chen Zhang

Self-Interpretable Subgraph Neural Network with Deep Reinforcement Walk Exploration

Jianming Huang, Hiroyuki Kasai

SemanticNN: Compressive and Error-Resilient Semantic Offloading for Extremely Weak Devices

Jiaming Huang, Yi Gao, Fuchang Pan, Renjie Li, Wei Dong

Richer Representations for Neural Algorithmic Reasoning via Auxiliary Reconstruction

Jiafu Huang, Chao Peng, Chenyang Xu, Zhengfeng Yang, Kecheng Cai

Recovering Coherent Affective Patterns: Addressing Modality Missing in Multimodal Sentiment Analysis

Huiting Huang, Tieliang Gong, Kai He, Wen Wen, Weizhan Zhang

Simulated Rewards, Skewed Strategies: Tracing the Acquired Preference Bias in LLM-Based Dialogue Planners

Heyan Huang, Yizhe Yang, Huashan Sun, Jiawei Li, Yang Gao

BayesAgent: Bayesian Agentic Reasoning Under Uncertainty via Verbalized Probabilistic Graphical Modeling

Hengguan Huang, Xing Shen, Guang-Yuan Hao, Songtao Wang, Lingfa Meng

PartialNet: Compute Less, Perform Better

Haiduo Huang, Tian Xia, Wenzhe Zhao, Pengju Ren

Double Rounding: Nearly Lossless Adaptive Bit Switching for QAT

Haiduo Huang, Zhenhua Liu, Tian Xia, Pengju Ren

Robust Decentralized Multi-armed Bandits: From Corruption-Resilience to Byzantine-Resilience

Zicheng Hu, Yuchen Wang, Cheng Chen

Towards Acyclic Preference Evaluation of Language Models via Multiple Evaluators

Zhengyu Hu, Jieyu Zhang, Zhihan Xiong, Alexander Ratner, Kaize Ding

Enhancing Diffusion Policies with Distribution-Matching Generator in Offline Reinforcement Learning

Xuemin Hu, Shen Li, Yingfen Xu, Bo Tang, Long Chen

Mosaic Pruning: A Hierarchical Framework for Generalizable Pruning of Mixture-of-Experts Models

Wentao Hu, Mingkuan Zhao, Shuangyong Song, Xiaoyan Zhu, Xin Lai

Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning

Tianmeng Hu, Yongzheng Cui, Rui Tang, Biao Luo, Ke Li

Prototype-Based Semantic Consistency Alignment for Domain Adaptive Retrieval

Tianle Hu, Weijun Lv, Na Han, Xiaozhao Fang, Jie Wen

FedLAGC: Towards High Performance System-Heterogeneous Federated Learning via Layer-Adaptive Submodel Extraction and Gradient Correction

Qing Hu, Tianchi Liao, Shuyi Wu, Lei Yang, Chuan Chen

FedTopo: Topology-Informed Representation Alignment in Federated Learning Under Non-I.I.D. Conditions

Ke Hu, Liyao Xiang, Peng Tang, Weidong Qiu

Look Closer! An Adversarial Parametric Editing Framework for Hallucination Mitigation in VLMs

Jiayu Hu, Beibei Li, Jiangwei Xia, Yanjun Qin, Bing Ji

Hyper-Opinion Vagueness Quantification for Robust Multimodal Learning

Disen Hu, Xun Jiang, Xiaofeng Cao, Zheng Wang, Jingkuan Song

Invariant Conditional Molecular Generation Under Distribution Shift

Chunyu Hu, Tianyin Liao, Yicheng Sui, Ran Zhang, Xiao Wang

Venom: Liquid Diffusion-Guided Gradient Inversion for Breaking Differential Privacy in Federated Learning

Bin Hu, Jingling Yuan, Jiawei Jiang, Chuang Hu

Denoising Mixup for Regression

Zhengzhang Hou, Zhanshan Li, Yanbo Liu, Geoff Nitschke, You Lu

Graph Out-of-Distribution Detection via Test-Time Calibration with Dual Dynamic Dictionaries

Yue Hou, Ruomei Liu, Yingke Su, Junran Wu, Ke Xu

A Theoretical Analysis of Detecting Large Model-Generated Time Series

Junji Hou, Junzhou Zhao, Shuo Zhang, Pinghui Wang

Gradient-Protected Value Decomposition for Cooperative Multi-Agent Reinforcement Learning

Jie Hou, Haowen Dou, Lujuan Dang, Liangjun Chen, Chenyang Ge

Harmonic Dataset Distillation for Time Series Forecasting

Seungha Hong, Sanghwan Jang, Wonbin Kweon, Suyeon Kim, Gyuseok Lee

Lost in Time? A Meta-Learning Framework for Time-Shift-Tolerant Physiological Signal Transformation

Qian Hong, Cheng Bian, Xiao Zhou, Xiaoyu Li, Yelei Li

HINPool: A Unified Heterogeneous Graph Pooling Framework for Accurate Molecular and Protein Property Prediction

Ming-Yi Hong, You-Chen Teng, Shao-En Lin, Chih-Yu Wang, Che Lin

Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes

Haokai Hong, Wanyu Lin, Ming Yang, Kay Chen Tan

From Attribution to Action: Jointly ALIGNing Predictions and Explanations

Dongsheng Hong, Chao Chen, Yanhui Chen, Shanshan Lin, Zhihao Chen

Uncertainty Quantification for Machine Learning: One Size Does Not Fit All

Paul Hofman, Yusuf Sale, Eyke Hüllermeier

Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily

Asela Hevapathige, Asiri Wijesinghe, Ahad N. Zehmakan