AAAI 2026

4,920 papers

SecMoE: Communication-Efficient Secure MoE Inference via Select-Then-Compute

Bowen Shen, Yuyue Chen, Peng Yang, Bin Zhang, Xi Zhang

FlashSVD: Memory-Efficient Inference with Streaming for Low-Rank Models

Zishan Shao, Yixiao Wang, Qinsi Wang, Ting Jiang, Zhixu Du

Hypergraph-Based Multi-View Multi-Label Classification via Adaptive High-Order Semantic Fusion

Yi Shan, Liyang Gao, Yuena Lin, Zhen Yang, Gengyu Lyu

MUG: Meta-path-aware Universal Heterogeneous Graph Pre-Training

Lianze Shan, Jitao Zhao, Dongxiao He, Yongqi Huang, Zhiyong Feng

DQT: Dynamic Quantization Training via Dequantization-Free Nested Integer Arithmetic

Hazem Hesham Yousef Shalby, Fabrizio Pittorino, Francesca Palermo, Diana Trojaniello, Manuel Roveri

Neural-Augmented Kelvinlet for Real-Time Soft Tissue Deformation Modeling

Ashkan Shahbazi, Kyvia Pereira, Jon S. Heiselman, Elaheh Akbari, Annie C. Benson

Low-Rank Curvature for Zeroth-Order Optimization in LLM Fine-tuning

Hyunseok Seung, Jaewoo Lee, Hyunsuk Ko

A Solver-in-the-Loop Framework for Improving LLMs on Answer Set Programming for Logic Puzzle Solving

Timo Pierre Schrader, Lukas Lange, Tobias Kaminski, Simon Razniewski, Annemarie Friedrich

Logical Characterizations of GNNs with Mean Aggregation

Moritz Schönherr, Carsten Lutz

Graph-Conditional Flow Matching for Relational Data Generation

Davide Scassola, Sebastiano Saccani, Luca Bortolussi

HN-MVTS: HyperNetwork-based Multivariate Time Series Forecasting

Andrey Savchenko, Oleg Kachan

DP-NCB: Privacy Preserving Fair Bandits

Dhruv Sarkar, Nishant Pandey, Sayak Ray Chowdhury

HyRNN: Hybrid Recurrent Neural Networks for Approximating Hybrid Dynamical Systems

Ricardo G. Sanfelice

Koopman Invariants as Drivers of Emergent Time-Series Clustering in Joint-Embedding Predictive Architectures

Pablo Ruiz-Morales, Dries Vanoost, Davy Pissoort, Mathias Verbeke

Repetition Makes Perfect: Recurrent Graph Neural Networks Match Message Passing Limit

Eran Rosenbluth, Martin Grohe

A Differential Perspective on Distributional Reinforcement Learning

Juan Sebastian Rojas, Chi-Guhn Lee

A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication

Angelo Rodio, Giovanni Neglia, Zheng Chen, Erik G. Larsson

GCL-OT: Graph Contrastive Learning with Optimal Transport for Heterophilic Text-Attributed Graphs

Yating Ren, Yikun Ban, Huobin Tan

BitDP: Ultra-low-bit Communication for Data Parallelism in LLM Training

Xiaozhe Ren, Qiong Luo

Discrete Structure Augmentation for Graph Convolutional Networks

Jianxin Ren, Weining Wu

LexInstructEval: Lexical Instruction Following Evaluation for Large Language Models

Huimin Ren, Yan Liang, Baiqiao Su, Chaobo Sun, Hengtong Lu

TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting

Chuanru Ren, Yao Lu, Tianjin Huang, Haowen Zheng, Hengde Zhu

ShapBPT: Image Feature Attributions Using Data-Aware Binary Partition Trees

Muhammad Rashid, Elvio G. Amparore, Enrico Ferrari, Damiano Verda

Compensating Distribution Drifts in Continual Learning with Pre-trained Vision Transformers

Xuan Rao, Simian Xu, Zheng Li, Bo Zhao, Derong Liu

Catastrophic Forgetting in Kolmogorov-Arnold Networks

Mohammad Marufur Rahman, Guanchu Wang, Kaixiong Zhou, Minghan Chen, Fan Yang

On the Calibration of Image Semi-Supervised Learning Models

Mehrab Mustafy Rahman, Jayanth Mohan, Tiberiu Sosea, Cornelia Caragea

QAPNet: A Quantum-Attentive Patchwise Network for Robust Medical Image Classification Under Noisy Inputs

Maqsudur Rahman, Jun Zhuang

PANDA – Patch and Distribution-Aware Augmentation for Long-Tailed Exemplar-Free Continual Learning

Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu

MoE^2: A Mixture-of-Mixtures of Experts for Ensemble-Free Domain Generalization

Ahmed Radwan, Mahmoud Soliman, Omar Abdelaziz, Ahmad Abdel-Qader, Mohamed S. Shehata

Unsupervised Combinatorial Probabilistic Reasoning: Probabilistic Coin Change Problem

Zhongdi Qu, Yingheng Wang, Utku Umur ACIKALIN, Aaron M. Ferber, Goncalo J. Gouveia

Exploiting Geometric Structures for Modeling Multi-Agent Behaviors: A New Thinking

Bohao Qu, Xiaofeng Cao, Bing Li, Menglin Zhang, Tuan-Anh Vu

Inverse Optimal Transport for Efficient Adaptation of Vision-Language Models

Shupeng Qiu, Chuan-Xian Ren

LPPG-RL: Lexicographically Projected Policy Gradient Reinforcement Learning with Subproblem Exploration

Ruiyu Qiu, Rui Wang, Guanghui Yang, Xiang Li, Zhijiang Shao

Decentralized Online Convex Optimization with Unknown Feedback Delays

Hao Qiu, Mengxiao Zhang, Juliette Achddou

Parameter Merging with Gradient-Guided Supermasks in Online Continual Learning

Benliu Qiu, Heqian Qiu, Lanxiao Wang, Taijin Zhao, Yu Dai

Head-Aware KV Cache Compression for Efficient Visual Autoregressive Modeling

Ziran Qin, Youru Lv, Mingbao Lin, Hang Guo, Zeren Zhang

HumanSense: From Multimodal Perception to Empathetic Context-Aware Responses Through Reasoning MLLMs

Zheng Qin, Ruobing Zheng, Yabing Wang, Tianqi Li, Yi Yuan

Robust Semi-paired Multimodal Learning for Cross-modal Retrieval

Yang Qin, Yuan Sun, Xi Peng, Dezhong Peng, Joey Tianyi Zhou

Multi-view Learning via Trusted Pairwise Entity Energy

Yalan Qin, Guorui Feng, Xinpeng Zhang

Beyond Missing Data Imputation: Information-Theoretic Coupling of Missingness and Class Imbalance for Optimal Irregular Time Series Classification

Xin Qin, Mengna Liu, Wenjie Wang, Shuxin Li, Tianjiao Li

Beyond Binary Erasure: Soft-Weighted Unlearning for Fairness and Robustness

Xinbao Qiao, Ningning Ding, Yushi Cheng, Meng Zhang

CR³: Boosting Compositional Reasoning in MLLMs Through Rule-Based Reinforcement Learning

Shun Qian, Bingquan Liu, Chengjie Sun, Peijin Xie, Zhen Xu

Full-Atom Peptide Design via Riemannian–Euclidean Bayesian Flow Networks

Hao Qian, Shikui Tu, Lei Xu

Next Generation Active Learning: Mixture of LLMs in the Loop

Yuanyuan Qi, Xiaohao Yang, Jueqing Lu, Guoxiang Guo, Joanne Enticott

Continuous Vision-Language-Action Co-Learning with Semantic-Physical Alignment for Behavioral Cloning

Xiuxiu Qi, Yu Yang, Jiannong Cao, Luyao Bai, Chongshan Fan

Revisiting the Data Sampling in Multimodal Post-training from a Difficulty-Distinguish View

Jianyu Qi, Ding Zou, Wenrui Yan, Rui Ma, Jiaxu Li

CoCo-MILP: Inter-Variable Contrastive and Intra-Constraint Competitive MILP Solution Prediction

Tianle Pu, Jianing Li, Yingying Gao, Shixuan Liu, Zijie Geng

Graph Contrastive Learning with Balanced Hard Negatives and Fine-grained Semantic-aware Positives

Hongshan Pu, Haoxu Zhang, Ye Liu, Hongmin Cai

Learning Fair Representations with Kolmogorov-Arnold Networks

Amisha Priyadarshini, Sergio Gago-Masague

Online Multi-LLM Selection via Contextual Bandits Under Unstructured Context Evolution

Manhin Poon, Xiangxiang Dai, Xutong Liu, Fang Kong, John C.S. Lui

On Stealing Graph Neural Network Models

Marcin Podhajski, Jan Dubiński, Franziska Boenisch, Adam Dziedzic, Agnieszka Pręgowska

ReBoot: Encrypted Training of Deep Neural Networks with CKKS Bootstrapping

Alberto Pirillo, Luca Colombo

A Novel Sliced Fused Gromov-Wasserstein Distance

Moritz Piening, Robert Beinert

Surrogate as Teacher: Distillation-Guided Graph Poisoning Attack

Xingyu Peng, Ke Xu

Semantic-Consistent Bidirectional Contrastive Hashing for Noisy Multi-Label Cross-Modal Retrieval

Likang Peng, Chao Su, Wenyuan Wu, Yuan Sun, Dezhong Peng

What Makes a Good Generated Image? Investigating Human and Multimodal LLM Image Preference Alignment

Rishab Parthasarathy, Jasmine Collins, Cory Stephenson

How Many Experts Are Enough? Towards Optimal Semantic Specialization for Mixture-of-Experts

Sumin Park, Noseong Park

ProLoG: Hybrid Prompt and LoRA Based Adaptation of Vision-Language Models for OOD Generalization

Jungwuk Park, Dong-Jun Han, Jaekyun Moon

Fair Model-based Clustering

Jinwon Park, Kunwoong Kim, Jihu Lee, Yongdai Kim

Transferable Model-agnostic Vision-Language Model Adaptation for Efficient Weak-to-Strong Generalization

Jihwan Park, Taehoon Song, Sanghyeok Lee, Miso Choi, Hyunwoo J. Kim

MoCHA: Advanced Vision-Language Reasoning with MoE Connector and Hierarchical Group Attention

Yuqi Pang, Bowen Yang, Yun Cao, Rong Fan, Xiaoyu Li

Decoupling Shared and Personalized Knowledge: A Dual-Branch Federated Learning Framework for Multi-Domain with Non-IID Data

Yiran Pang, Zhen Ni, Xiangnan Zhong

Forest vs Tree: The (N, K) Trade-off in Reproducible ML Evaluation

Deepak Pandita, Flip Korn, Chris Welty, Christopher M Homan

Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks

Muthukumar Pandaram, Jakob Hollenstein, David Drexel, Samuele Tosatto, Antonio Rodriguez-Sanchez

On the Misalignment Between Data Learnability and Forgettability in Machine Unlearning

Zijie Pan, Zuobin Ying, Yajie Wang, Wanlei Zhou

Prototype Entropy Alignment: Reinforcing Structured Uncertainty in LLM Reasoning

Zhengyuan Pan, Yanhao Chen, Zhongquan Jian, Wanru Zhao, Haonan Ma

Re-architecting Personalized Federated Learning for Demanding Edge Environments

Quyang Pan, Sheng Sun, Tingting Wi, Zhiyuan Wu, Yuwei Wang

Correcting False Alarms from Unseen: Adapting Graph Anomaly Detectors at Test Time

Junjun Pan, Yixin Liu, Chuan Zhou, Fei Xiong, Alan Wee-Chung Liew

OPTION: An Online Pricing Strategy for Asynchronous Federated Learning Against Free-Riding Attacks

Bangqi Pan, Jianfeng Lu, Shuqin Cao, Xiao Zhang, Gang Li

Policy Newton Methods for Distortion Riskmetrics

Soumen Pachal, Mizhaan Prajit Maniyar, Prashanth L. A.

Learn from Global Correlations: Enhancing Evolutionary Algorithm via Spectral GNN

Kaichen Ouyang, Zong Ke, Shengwei Fu, Lingjie Liu, Puning Zhao

DisCo DETR: Distance-aware Multi-view Contrastive Learning for DETR Pre-training

Chao Ouyang, Yuyang Bai, Jun Zhang, Tianlu Gao, Jun Hao

ParaDySe: A Parallel Strategy Switching Framework for Dynamic Sequences in Transformer-based Large Language Models

Zhixin Ou, Peng Liang, Linbo Qiao, Jianchen Han, Baihui Liu

The Strong Lottery Ticket Hypothesis for Multi-Head Attention Mechanisms

Hikari Otsuka, Daiki Chijiwa, Yasuyuki Okoshi, Daichi Fujiki, Susumu Takeuchi

Large Language Models Meet Extreme Multi-label Classification: Scaling and Multi-modal Framework

Diego Ortego, Marlon Rodríguez, Mario Almagro, Kunal Dahiya, David Jimenez

Computing Probabilistic Explanations for ML Models: Fixed-Parameter Algorithms

Sebastian Ordyniak, Mateusz Rychlicki, Stefan Szeider

Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning

Pierriccardo Olivieri, Fausto Lasca, Alessandro Gianola, Matteo Papini

Task Prototype-Based Knowledge Retrieval for Multi-Task Learning from Partially Annotated Data

Youngmin Oh, Hyung-Il Kim, Jung Uk Kim

FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification

YongKyung Oh, Dong-Young Lim, Sungil Kim

Object-Centric World Models for Causality-Aware Reinforcement Learning

Yosuke Nishimoto, Takashi Matsubara

Mitigating Endogenous Confirmation Bias in Noisy Label Learning for Vision-Language Models

Feiyang Ning, Xinyang Chen

AutoSchA: Automatic Hierarchical Music Representations via Multi-Relational Node Isolation

Stephen Ni-Hahn, Rico Zhu, Jerry Yin, Yue Jiang, Cynthia Rudin

Disentangled Generation-Based Prototypical Alignment for Few-Shot Unsupervised Domain Adaptation in Graph-Level Anomaly Detection

Zhibin Ni, Chenghao Zhang, Hai Wan, Xibin Zhao

PKR-QA: A Benchmark for Procedural Knowledge Reasoning with Knowledge Module Learning

Thanh-Son Nguyen, Hong Yang, Tzeh Yuan Neoh, Hao Zhang, Ee Yeo Keat

Provably Data-Driven Projection Method for Quadratic Programming

Anh Tuan Nguyen, Viet Anh Nguyen

Hexaïssa: Standing on Giants’ Shoulders—Routing the Best Chess Engines with Mixture-of-Experts and Latent Reward Learning

Bach Ngo, Nguyen Hoang Khoi Do

Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions

Rashmeet Kaur Nayyar, Naman Shah, Siddharth Srivastava

GP-MoLFormer-Sim: Test Time Molecular Optimization Through Contextual Similarity Guidance

Jiri Navratil, Jarret Ross, Payel Das, Youssef Mroueh, Samuel C Hoffman

Policy Search, Retrieval, and Composition via Task Similarity in Collaborative Agentic Systems

Saptarshi Nath, Christos Peridis, Eseoghene Benjamin, Xinran Liu, Soheil Kolouri

Parameter-free Optimal Rates for Nonlinear Semi-Norm Contractions with Applications to Q-Learning

Ankur Naskar, Gugan Thoppe, Vijay Gupta

RankList – a Listwise Preference Learning Framework for Predicting Subjective Preferences

Abinay Reddy Naini, Fernando Diaz, Carlos Busso

From Decision Trees to Boolean Logic: A Fast and Unified SHAP Algorithm

Alexander Nadel, Ron Wettenstein

Unlocking Efficient Vehicle Dynamics Modeling via Analytic World Models

Asen Nachkov, Danda Pani Paudel, Jan-Nico Zaech, Davide Scaramuzza, Luc Van Gool

CoRe-Fed: Bridging Collaborative and Representation Fairness via Federated Embedding Distillation

Noorain Mukhtiar, Adnan Mahmood, Quan Z. Sheng

Inference Offloading for Cost-Sensitive Binary Classification at the Edge

Vishnu Narayanan Moothedath, Umang Agarwal, Umeshraja N, James Richard Gross, Jaya Prakash Champati

Expandable and Differentiable Dual Memories with Orthogonal Regularization for Exemplar-free Continual Learning

Hyung-Jun Moon, Sung-Bae Cho

Bant: Byzantine Antidote via Trial Function and Trust Scores

Gleb Molodtsov, Daniil Medyakov, Sergey Skorik, Nikolas Khachaturov, Shahane Tigranyan

Neuro-Symbolic Federated Learning over Heterogeneous Data-Views: A Structured Approach to Distributive EHR Modelling

Soheila Molaei, Bahareh Fatemi, Anshul Thakur, Andrew Soltan, Fazle Rabbi

Exact Shapley Attributions in Quadratic-time for FANOVA Gaussian Processes

Majid Mohammadi, Krikamol Muandet, Ilaria Tiddi, Annette Ten Teije, Siu Lun Chau

Neural Architecture and Hyperparameter Selection Through Meta-Learning on Time Series

Erfan Moeini, Christopher Vox, Marie Anastacio, Wadie Skaf, Mitra Baratchi