AAAI 2025

3,486 papers

ConceptSearch: Towards Efficient Program Search Using LLMs for Abstraction and Reasoning Corpus (ARC)

Kartik Singhal, Gautam Shroff

Co-Dream: Collaborative Dream Synthesis over Decentralized Models

Abhishek Singh, Gauri Gupta, Yichuan Shi, Alex Dang, Ritvik Kapila

PatentLMM: Large Multimodal Model for Generating Descriptions for Patent Figures

Shreya Shukla, Nakul Sharma, Manish Gupta, Anand Mishra

Ambiguous Instance-Aware Contrastive Network with Multi-Level Matching for Multi-View Document Clustering

Zhenqiu Shu, Teng Sun, Yunwei Luo, Zhengtao Yu

TinySAM: Pushing the Envelope for Efficient Segment Anything Model

Han Shu, Wenshuo Li, Yehui Tang, Yiman Zhang, Yihao Chen

Faithful and Accurate Self-Attention Attribution for Message Passing Neural Networks via the Computation Tree Viewpoint

Yong-Min Shin, Siqing Li, Xin Cao, Won-Yong Shin

Replication-proof Bandit Mechanism Design with Bayesian Agents

Suho Shin, Seyed A. Esmaeili, MohammadTaghi Hajiaghayi

Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood

Yuta Shikuri

Stop Diverse OOD Attacks: Knowledge Ensemble for Reliable Defense

Zhenbo Shi, Xiaoman Liu, Yuxuan Zhang, Shuchang Wang, Rui Shu

Protecting Model Adaptation from Trojans in the Unlabeled Data

Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

Numerical Pruning for Efficient Autoregressive Models

Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Jing Liu

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers

Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Yanyu Li

Open-Set Cross-Network Node Classification via Unknown-Excluded Adversarial Graph Domain Alignment

Xiao Shen, Zhihao Chen, Shirui Pan, Shuang Zhou, Laurence T. Yang

Label-Free Backdoor Attacks in Vertical Federated Learning

Wei Shen, Wenke Huang, Guancheng Wan, Mang Ye

SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space Models

Shuaijie Shen, Chao Wang, Renzhuo Huang, Yan Zhong, Qinghai Guo

Boosting Test Performance with Importance Sampling--a Subpopulation Perspective

Hongyu Shen, Zhizhen Zhao

Offline-to-Online Hyperparameter Transfer for Stochastic Bandits

Dravyansh Sharma, Arun Suggala

Linear Streaming Bandit: Regret Minimization and Fixed-Budget Epsilon-Best Arm Identification

Yuming Shao, Zhixuan Fang

Know2Vec: A Black-Box Proxy for Neural Network Retrieval

Zhuoyi Shang, Yanwei Liu, Jinxia Liu, Xiaoyan Gu, Ying Ding

Improving Model Probability Calibration by Integration of Large Data Sources with Biased Labels

Renat Sergazinov, Richard Chen, Cheng Ji, Jing Wu, Daniel Cociorva

Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with Topology-grouping Strategy

Hyunjin Seo, Kyusung Seo, Joonhyung Park, Eunho Yang

General Uncertainty Estimation with Delta Variances

Simon Schmitt, John Shawe-Taylor, Hado van Hasselt

Delay as Payoff in MAB

Ofir Schlisselberg, Ido Cohen, Tal Lancewicki, Yishay Mansour

Zero-Shot Conditioning of Score-Based Diffusion Models by Neuro-Symbolic Constraints

Davide Scassola, Sebastiano Saccani, Ginevra Carbone, Luca Bortolussi

Layered-Parameter Perturbation for Zeroth-Order Optimization of Optical Neural Networks

Hiroshi Sawada, Kazuo Aoyama, Masaya Notomi

Explicit and Implicit Graduated Optimization in Deep Neural Networks

Naoki Sato, Hideaki Iiduka

A Robust Prototype-Based Network with Interpretable RBF Classifier Foundations

Sascha Saralajew, Ashish Rana, Thomas Villmann, Ammar Shaker

RESQUE: Quantifying Estimator to Task and Distribution Shift for Sustainable Model Reusability

Vishwesh Sangarya, Jung-Eun Kim

A Scalable and Effective Alternative to Graph Transformers

Kaan Sancak, Zhigang Hua, Jin Fang, Yan Xie, Andrey Malevich

User Preference Meets Pareto-Optimality in Multi-Objective Bayesian Optimization

Joshua Hang Sai Ip, Ankush Chakrabarty, Ali Mesbah, Diego Romeres

A Layer Selection Approach to Test Time Adaptation

Sabyasachi Sahoo, Mostafa ElAraby, Jonas Ngnawé, Yann Batiste Pequignot, Frederic Precioso

FedPIA – Permuting and Integrating Adapters Leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning

Pramit Saha, Divyanshu Mishra, Felix Wagner, Konstantinos Kamnitsas, J. Alison Noble

From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers

Bharat Runwal, Tejaswini Pedapati, Pin-Yu Chen

TTE: Two Tokens Are Enough to Improve Parameter-Efficient Tuning

Jiacheng Ruan, Mingye Xie, Jingsheng Gao, Xian Gao, Suncheng Xiang

Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs

Sergio Rozada, Dongsheng Ding, Antonio G. Marques, Alejandro Ribeiro

Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine

Luis Roque, Vítor Cerqueira, Carlos Soares, Luís Torgo

Monitoring Primitive Interactions During the Training of DNNs

Jie Ren, Xinhao Zheng, Jiyu Liu, Andrew Lizarraga, Ying Nian Wu

PrivDNFIS: Privacy-preserving and Efficient Deep Neuro-Fuzzy Inference System

Hao Ren, Xiao Lan, Rui Tang, Xingshu Chen

Improving Generalization for AI-Synthesized Voice Detection

Hainan Ren, Li Lin, Chun-Hao Liu, Xin Wang, Shu Hu

Error Bounds for Gaussian Process Regression Under Bounded Support Noise with Applications to Safety Certification

Robert Reed, Luca Laurenti, Morteza Lahijanian

The VOROS: Lifting ROC Curves to 3D to Summarize Unbalanced Classifier Performance

Christopher Ratigan, Lenore Cowen

Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage

Md Rafi Ur Rashid, Jing Liu, Toshiaki Koike-Akino, Ye Wang, Shagufta Mehnaz

Slice-and-Pack: Tailoring Deep Models for Customized Requirements

Ruice Rao, Dingwei Li, Ming Li

Can Private Machine Learning Be Fair?

Joseph Rance, Filip Svoboda

Kernel Learning for Sample Constrained Black-Box Optimization

Rajalaxmi Rajagopalan, Yu-Lin Wei, Romit Roy Choudhury

Fair Federated Survival Analysis

Md Mahmudur Rahman, Sanjay Purushotham

Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning

Yun Qu, Yuhang Jiang, Boyuan Wang, Yixiu Mao, Cheems Wang

Efficient 3D Recognition with Event-driven Spike Sparse Convolution

Xuerui Qiu, Man Yao, Jieyuan Zhang, Yuhong Chou, Ning Qiao

Enhancing Masked Time-Series Modeling via Dropping Patches

Tianyu Qiu, Yi Xie, Hao Niu, Yun Xiong, Xiaofeng Gao

PowerMLP: An Efficient Version of KAN

Ruichen Qiu, yibo miao, Shiwen Wang, Yifan Zhu, Lijia Yu

Multimodal Variational Autoencoder: A Barycentric View

Peijie Qiu, Wenhui Zhu, Sayantan Kumar, Xiwen Chen, Jin Yang

PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning

Yongchun Qin, Pengfei Fang, hui xue

Scalable One-Pass Incomplete Multi-View Clustering by Aligning Anchors

Yalan Qin, Guorui Feng, Xinpeng Zhang

SUMO: Search-Based Uncertainty Estimation for Model-Based Offline Reinforcement Learning

Zhongjian Qiao, Jiafei Lyu, Kechen Jiao, Qi Liu, Xiu Li

Certified Causal Defense with Generalizable Robustness

Yiran Qiao, Yu Yin, Chen Chen, Jing Ma

Federated t-SNE and UMAP for Distributed Data Visualization

Dong Qiao, Xinxian Ma, Jicong Fan

Advancing Retrosynthesis with Retrieval-Augmented Graph Generation

Anjie Qiao, Zhen Wang, Jiahua Rao, Yuedong Yang, Zhewei Wei

DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification

Feifei Qian, Lu Bai, Lixin Cui, Ming Li, Ziyu Lyu

Cross-Silo Feature Space Alignment for Federated Learning on Clients with Imbalanced Data

Zhuang Qi, Lei Meng, Zhaochuan Li, Han Hu, Xiangxu Meng

Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression

Ruizhi Pu, Gezheng Xu, Ruiyi Fang, Bing-Kun Bao, Charles Ling

Robust Self-Paced Hashing for Cross-Modal Retrieval with Noisy Labels

Ruitao Pu, Yuan Sun, Yang Qin, Zhenwen Ren, Xiaomin Song

Enhancing SQL Query Generation with Neurosymbolic Reasoning

Henrijs Princis, Cristina David, Alan Mycroft

Federated Unsupervised Domain Generalization Using Global and Local Alignment of Gradients

Farhad Pourpanah, Mahdiyar Molahasani, Milad Soltany, Michael Greenspan, Ali Etemad

On Corruption-Robustness in Performative Reinforcement Learning

Vasilis Pollatos, Debmalya Mandal, Goran Radanovic

Iterative Counterfactual Data Augmentation

Mitchell Plyler, Min Chi

Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors

Wasu Top Piriyakulkij, Yingheng Wang, Volodymyr Kuleshov

TinySubNets: An Efficient and Low Capacity Continual Learning Strategy

Marcin Pietron, Kamil Faber, Dominik Żurek, Roberto Corizzo

In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting

Constantin Philippenko, Kevin Scaman, Laurent Massoulié

Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm

Thai-Hoang Pham, Yuanlong Wang, Changchang Yin, Xueru Zhang, Ping Zhang

Qsco: A Quantum Scoring Module for Open-Set Supervised Anomaly Detection

Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

SOLA-GCL: Subgraph-Oriented Learnable Augmentation Method for Graph Contrastive Learning

Tianhao Peng, Xuhong Li, Haitao Yuan, Yuchen Li, Haoyi Xiong

BearLLM: A Prior Knowledge-Enhanced Bearing Health Management Framework with Unified Vibration Signal Representation

Haotian Peng, Jiawei Liu, Jinsong Du, Jie Gao, Wei Wang

Look Back for More: Harnessing Historical Sequential Updates for Personalized Federated Adapter Tuning

Danni Peng, Yuan Wang, Huazhu Fu, Jinpeng Jiang, Yong Liu

SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization

Kwangryeol Park, Seulki Lee

Riemannian Geometric-based Meta Learning

Juneyoung Park, YuMi Lee, Tae-Joon Kim, Jang-Hwan Choi

Deep Disentangled Metric Learning

Jinhee Park, Jisoo Park, Dagyeong Na, Junseok Kwon

Assessing Modality Bias in Video Question Answering Benchmarks with Multimodal Large Language Models

Jean Park, Kuk Jin Jang, Basam Alasaly, Sriharsha Mopidevi, Andrew Zolensky

Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation

Prashansa Panda, Shalabh Bhatnagar

Federated Unlearning with Gradient Descent and Conflict Mitigation

Zibin Pan, Zhichao Wang, Chi Li, Kaiyan Zheng, Boqi Wang

Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled Yet Hard-to-Learn Samples in Noisy Data

Weiran Pan, Wei Wei, Feida Zhu, Yong Deng

Reconsidering Feature Structure Information and Latent Space Alignment in Partial Multi-label Feature Selection

Hanlin Pan, Kunpeng Liu, Wanfu Gao

Learning Set Functions with Implicit Differentiation

Gözde Özcan, Chengzhi Shi, Stratis Ioannidis

Extracting PAC Decision Trees from Black Box Binary Classifiers: The Gender Bias Study Case on BERT-based Language Models

Ana Ozaki, Roberto Confalonieri, Ricardo Guimarães, Anders Imenes

Incomplete Multi-View Multi-Label Classification via Diffusion-Guided Redundancy Removal

Shilong Ou, Zhe Xue, lixiong Qin, Yawen Li, Meiyu Liang

Learning Deep Dissipative Dynamics

Yuji Okamoto, Ryosuke Kojima

Efficient Few-Shot Neural Architecture Search by Counting the Number of Nonlinear Functions

Youngmin Oh, Hyunju Lee, Bumsub Ham

DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series Analysis

YongKyung Oh, Dong-Young Lim, Sungil Kim

FedSPU: Personalized Federated Learning for Resource-Constrained Devices with Stochastic Parameter Update

Ziru Niu, Hai Dong, A. K. Qin

ALADE-SNN: Adaptive Logit Alignment in Dynamically Expandable Spiking Neural Networks for Class Incremental Learning

Wenyao Ni, Jiangrong Shen, Qi Xu, Huajin Tang

Benchmarking and Understanding Compositional Relational Reasoning of LLMs

Ruikang Ni, Da Xiao, Qingye Meng, Xiangyu Li, Shihui Zheng

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization

Van Khoa Nguyen, Yoann Boget, Frantzeska Lavda, Alexandros Kalousis

Attack on Prompt: Backdoor Attack in Prompt-Based Continual Learning

Trang Nguyen, Anh Tran, nhật Hồ

Improving Pareto Set Learning for Expensive Multi-objective Optimization via Stein Variational Hypernetworks

Minh-Duc Nguyen, Phuong Mai Dinh, Quang-Huy Nguyen, Long P. Hoang, Dung D. Le

CASUAL: Conditional Support Alignment for Domain Adaptation with Label Shift

Anh T Nguyen, Lam Tran, Anh Tong, Tuan-Duy H. Nguyen, Toan Tran

BOIDS: High-Dimensional Bayesian Optimization via Incumbent-Guided Direction Lines and Subspace Embeddings

Lam Ngo, Huong Ha, Jeffrey Chan, Hongyu Zhang

Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting

Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

Autonomous Option Invention for Continual Hierarchical Reinforcement Learning and Planning

Rashmeet Kaur Nayyar, Siddharth Srivastava

Decoupled Policy Actor-Critic: Bridging Pessimism and Risk Awareness in Reinforcement Learning

Michal Nauman, Marek Cygan

Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian Optimization

Nobuo Namura, Sho Takemori

Entropy Regularized Task Representation Learning for Offline Meta-Reinforcement Learning

Mohammadreza Nakhaeinezhadfard, Aidan Scannell, Joni Pajarinen