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Preprints

Lu H; Zhao C; Xue M; Yao L; Moore K; Gong D, 2026, Take Only What You Need: Rank Minimization as an Implicit Forgetting Regularizer in Continual Learning, http://dx.doi.org/10.48550/arxiv.2412.01004

Yao Y; Zhang J; Wu J; Huang C; Xia Y; Yu T; Zhang R; Kim S; Rossi R; Li A; Yao L; McAuley J; Chen Y; Joe-Wong C, 2026, Federated Large Language Models: Current Progress and Future Directions, http://dx.doi.org/10.48550/arxiv.2409.15723

Jiang S; Kong T; Qi Y; Zhang H; Yao L; Sheng QZ; Liu Q; Yang M-H, 2026, Teaching Prompts to Coordinate: Hierarchical Layer-Grouped Prompt Tuning for Continual Learning, http://dx.doi.org/10.48550/arxiv.2511.12090

Mundada G; Huang Z; Surana R; Yu S; Zhang JY; Li X; Yu T; Yao L; Shang J; McAuley J; Wu J, 2026, WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning, http://dx.doi.org/10.48550/arxiv.2602.17025

Jiang S; Feng X; Qi Y; Zhang H; Hang R; Liu Q; Yao L; Sheng QZ; Yang M-H, 2026, Unlocking Prototype Potential: An Efficient Tuning Framework for Few-Shot Class-Incremental Learning, http://dx.doi.org/10.48550/arxiv.2602.05271

Huang C; Chen X; Huang H; Sheng QZ; Yao L, 2026, Generative Chain of Behavior for User Trajectory Prediction, http://dx.doi.org/10.48550/arxiv.2601.18213

Wu J; Xiong Y; Li X; Xia Y; Wang R; Wang Y; Yu T; Kim S; Rossi RA; Yao L; Shang J; McAuley J, 2026, Mitigating Visual Knowledge Forgetting in MLLM Instruction-tuning via Modality-decoupled Gradient Descent, http://dx.doi.org/10.48550/arxiv.2502.11740

Jiao S; Xiao X; Wei Y; Qi S; Huang C; Sheng QZM; Yao L, 2026, PruneRAG: Confidence-Guided Query Decomposition Trees for Efficient Retrieval-Augmented Generation, http://dx.doi.org/10.48550/arxiv.2601.11024

Zhou G; Han Z; Chen S; Huang B; Zhu L; Liu T; Yao L; Zhang K, 2026, HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization, http://dx.doi.org/10.48550/arxiv.2401.09716

Lu H; Zhang X; Moore K; Xue J; Yao L; Hengel AVD; Gong D, 2025, Continual Learning on CLIP via Incremental Prompt Tuning with Intrinsic Textual Anchors, http://dx.doi.org/10.48550/arxiv.2505.20680

Yang S; Hu Z; Li X; Wang C; Yu T; Xu X; Zhu L; Yao L, 2025, DrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agents, http://dx.doi.org/10.48550/arxiv.2503.23804

Lou H; Paik H-Y; Hu W; Yao L, 2025, ParaStyleTTS: Toward Efficient and Robust Paralinguistic Style Control for Expressive Text-to-Speech Generation, http://dx.doi.org/10.48550/arxiv.2510.18308

Chen X; Wang S; Yao L, 2025, Energy-Guided Diffusion Sampling for Long-Term User Behavior Prediction in Reinforcement Learning-based Recommendation, http://dx.doi.org/10.48550/arxiv.2510.12815

Chen X; Wang S; Yao L, 2025, Maximum In-Support Return Modeling for Dynamic Recommendation with Language Model Prior, http://dx.doi.org/10.48550/arxiv.2510.12816

Wang X; Hu X; Huang C; Zeng Z; Nie G; Sheng QZ; Yao L, 2025, Self-Supervised Cross-Modal Learning for Image-to-Point Cloud Registration, http://dx.doi.org/10.48550/arxiv.2509.15882

Yang L; Zhang WE; Sheng QZ; Yao L; Chen W; Shakeri A, 2025, MMiC: Mitigating Modality Incompleteness in Clustered Federated Learning, http://dx.doi.org/10.48550/arxiv.2505.06911

Li X; Wang R; Gao E; Gong M; Yao L, 2025, Causality-aligned Prompt Learning via Diffusion-based Counterfactual Generation, http://dx.doi.org/10.48550/arxiv.2507.19882

Li Z; Yang C; Chen Y; Wang X; Chen H; Xu G; Yao L; Sheng QZ, 2025, Graph and Sequential Neural Networks in Session-based Recommendation: A Survey, http://dx.doi.org/10.48550/arxiv.2408.14851

Chen X; Wang S; Yu T; Yao L, 2025, Diffusion Policies for Risk-Averse Behavior Modeling in Offline Reinforcement Learning, http://dx.doi.org/10.48550/arxiv.2403.17646

Wang R; Wang Z; Huang C; Wang R; Yu T; Yao L; Lui JCS; Zhou D, 2025, Federated In-Context Learning: Iterative Refinement for Improved Answer Quality, http://dx.doi.org/10.48550/arxiv.2506.07440

Huang C; Huang H; Yu T; Xie K; Wu J; Zhang S; Mcauley J; Jannach D; Yao L, 2025, A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigms, http://dx.doi.org/10.48550/arxiv.2504.16420

Lou H; Paik H-Y; Li S; Hu W; Yao L, 2025, Generalized Multilingual Text-to-Speech Generation with Language-Aware Style Adaptation, http://dx.doi.org/10.48550/arxiv.2504.08274

Chua J; Wang C; Yao L, 2025, Superhuman Game AI Disclosure: Expertise and Context Moderate Effects on Trust and Fairness, http://dx.doi.org/10.48550/arxiv.2503.15514

Wang H; Lu H; Yao L; Gong D, 2025, Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning, http://dx.doi.org/10.48550/arxiv.2403.18886

Huang C; Wu J; Xia Y; Yu Z; Wang R; Yu T; Zhang R; Rossi RA; Kveton B; Zhou D; McAuley J; Yao L, 2025, Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models, http://dx.doi.org/10.48550/arxiv.2503.16734

Zhou G; Xie S; Hao G-Y; Chen S; Huang B; Xu X; Wang C; Zhu L; Yao L; Zhang K, 2025, Emerging Synergies in Causality and Deep Generative Models: A Survey, http://dx.doi.org/10.48550/arxiv.2301.12351

Cao Y; Sheng QZ; McAuley J; Yao L, 2025, Reinforcement Learning for Generative AI: A Survey, http://dx.doi.org/10.48550/arxiv.2308.14328

Wang S; Chen X; Yao L, 2025, Policy-Guided Causal State Representation for Offline Reinforcement Learning Recommendation, http://dx.doi.org/10.48550/arxiv.2502.02327

Lou H; Paik H; Haghighi PD; Hu W; Yao L, 2024, LatentSpeech: Latent Diffusion for Text-To-Speech Generation, http://dx.doi.org/10.48550/arxiv.2412.08117

Du J; Ye Z; Guo B; Yu Z; Wu J; Yang J; Sheng M; Yao L, 2024, Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference, http://dx.doi.org/10.48550/arxiv.2411.17361

Hu J; Jia H; Hassan M; Yao L; Kusy B; Hu W, 2024, LightLLM: A Versatile Large Language Model for Predictive Light Sensing, http://dx.doi.org/10.48550/arxiv.2411.15211

Wu J; Li X; Wang R; Xia Y; Xiong Y; Wang J; Yu T; Chen X; Kveton B; Yao L; Shang J; McAuley J, 2024, OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models, http://dx.doi.org/10.48550/arxiv.2410.23703

Huang C; Wang S; Wang X; Yao L, 2024, Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation, http://dx.doi.org/10.48550/arxiv.2410.22790

Huang C; Wang S; Wang X; Yao L, 2024, Modeling Temporal Positive and Negative Excitation for Sequential Recommendation, http://dx.doi.org/10.48550/arxiv.2410.22013

Wu J; Zhang Z; Xia Y; Li X; Xia Z; Chang A; Yu T; Kim S; Rossi RA; Zhang R; Mitra S; Metaxas DN; Yao L; Shang J; McAuley J, 2024, Visual Prompting in Multimodal Large Language Models: A Survey, http://dx.doi.org/10.48550/arxiv.2409.15310

Lou H; Paik H; Hu W; Yao L, 2024, StyleSpeech: Parameter-efficient Fine Tuning for Pre-trained Controllable Text-to-Speech, http://dx.doi.org/10.48550/arxiv.2408.14713

Wang H; Gao C; Wu Y; Jin D; Yao L; Li Y, 2024, PateGail: A Privacy-Preserving Mobility Trajectory Generator with Imitation Learning, http://dx.doi.org/10.48550/arxiv.2407.16729

Wang S; Chen X; Yao L, 2024, On Causally Disentangled State Representation Learning for Reinforcement Learning based Recommender Systems, http://dx.doi.org/10.48550/arxiv.2407.13091

Chua J; Li Y; Yang S; Wang C; Yao L, 2024, AI Safety in Generative AI Large Language Models: A Survey, http://dx.doi.org/10.48550/arxiv.2407.18369

Chen X; Wang S; Yao L, 2024, Maximum-Entropy Regularized Decision Transformer with Reward Relabelling for Dynamic Recommendation, http://dx.doi.org/10.48550/arxiv.2406.00725

Liu Y; Cui G; Luo J; Chang X; Yao L, 2024, Two-stream Multi-level Dynamic Point Transformer for Two-person Interaction Recognition, http://dx.doi.org/10.48550/arxiv.2307.11973

Liu Y; Sheng QZ; Yao L, 2024, Modeling Pedestrian Intrinsic Uncertainty for Multimodal Stochastic Trajectory Prediction via Energy Plan Denoising, http://dx.doi.org/10.48550/arxiv.2405.07164

Liu Y; Wang R; Cao Y; Sheng QZ; Yao L, 2024, Multi-agent Traffic Prediction via Denoised Endpoint Distribution, http://dx.doi.org/10.48550/arxiv.2405.07041

Liu Y; Ye Z; Wang R; Li B; Sheng QZ; Yao L, 2024, Uncertainty-Aware Pedestrian Trajectory Prediction via Distributional Diffusion, http://dx.doi.org/10.48550/arxiv.2303.08367

Wang S; Chen X; Yao L, 2024, Retentive Decision Transformer with Adaptive Masking for Reinforcement Learning based Recommendation Systems, http://dx.doi.org/10.48550/arxiv.2403.17634

Huang H; Chang X; Hu W; Yao L, 2024, MatchNAS: Optimizing Edge AI in Sparse-Label Data Contexts via Automating Deep Neural Network Porting for Mobile Deployment, http://dx.doi.org/10.48550/arxiv.2402.13525

Lu H; Gong D; Wang S; Xue J; Yao L; Moore K, 2024, Learning with Mixture of Prototypes for Out-of-Distribution Detection, http://dx.doi.org/10.48550/arxiv.2402.02653

Zhang D; Pan S; Hoang T; Xing Z; Staples M; Xu X; Yao L; Lu Q; Zhu L, 2024, To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods, http://dx.doi.org/10.48550/arxiv.2302.03350

He E; Hao Y; Zhang Y; Yin G; Yao L, 2024, SCALA: Sparsification-based Contrastive Learning for Anomaly Detection on Attributed Networks, http://dx.doi.org/10.48550/arxiv.2401.01625

Wang S; Chen X; Yao L; Cripps S; McAuley J, 2023, Plug-and-Play Model-Agnostic Counterfactual Policy Synthesis for Deep Reinforcement Learning based Recommendation, http://dx.doi.org/10.48550/arxiv.2208.05142


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