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Author

Tun Lu

Observed name: Lu, Tun
Institution: Fudan University
Observed institution: Fudan University
ORCID: 0000-0002-6633-4826
Observed ORCID: 0000-0002-6633-4826
OpenAlex ID: A5125065674
Dynamic Feature-Embedding Communication via Codebook Distillation for Federated Recommendation
2026 · Mingzhe Han, Jiahao Liu, et al. · ACM International Conference on Information and Knowledge Management (CIKM) · 6
From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agents
2026 · Liu, Jiahao, Han, Mingzhe, et al. · arXiv (Cornell University) · 6
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SD-MoE: Spectral Decomposition for Effective Expert Specialization
2026 · Huang, Ruijun, Dong, Fang, et al. · arXiv (Cornell University) · 6
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StreamMemBench: Streaming Evaluation of Agent Memory for Future-Oriented Assistance
2026 · Guanming Liu, Yuqi Ren, et al. · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · 6
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Spectra: Rethinking Optimizers for LLMs Under Spectral Anisotropy
2026 · Huang, Zhendong, Cao, Hengjie, et al. · arXiv (Cornell University) · 5
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Transparent and Controllable Recommendation Filtering via Multimodal Multi-Agent Collaboration
2026 · Zhang, Chi, Xu, Zhipeng, et al. · arXiv (Cornell University) · 2
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Multi-Head Attention as a Source of Catastrophic Forgetting in MoE Transformers
2026 · Chen, Anrui, Huang, Ruijun, et al. · arXiv (Cornell University) · 2
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IntPro: A Proxy Agent for Context-Aware Intent Understanding via Retrieval-conditioned Inference
2026 · Liu, Guanming, Wu, Meng, et al. · arXiv (Cornell University) · 2
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The Curse and Blessing of Mean Bias in FP4-Quantized LLM Training
2026 · Cao, Hengjie, Huang, Zhendong, et al. · arXiv (Cornell University) · 1
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SoulSeek: Exploring the Use of Social Cues in LLM-based Information Seeking
2026 · Shu, Yubo, Zhang, Peng, et al. · arXiv (Cornell University) · 1
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Fast-Slow Thinking RM: Efficient Integration of Scalar and Generative Reward Models
2026 · Jiayun Wu, Peng Zhang, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 1
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FedHUR: Learning Hierarchical Utility-Guided Client Relations for Personalized Federated Recommendation
2026 · Mingzhe Han, Jiahao Liu, et al. · ACM International Conference on Information and Knowledge Management (CIKM)
Works count: 12
Citation count: 38
H-index: 5
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