5 citations · 6 across the 8 of their papers we have counts for
8 papers
Discrete Diffusion Models: A Unified Framework from Tokenization to Generation
Ye Yuan, Weien Li, Rui Song +20
Discrete denoising diffusion models (DDMs) have recently emerged as a compelling alternative to autoregressive (AR) modeling for discrete data, offering parallel generation and ite…
Restoring Collaborative Signals in Semantic-ID Generative Recommendation via Personalized Natural Language
Changjiang Han, Qingyang Li, Yaqiang Zang +4
Making LLM-based generative recommendation models stronger and more personalized through natural language and explicit reasoning is a widely anticipated yet still unsolved goal. Su…
Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization
Weixu Zhang, Ye Yuan, Changjiang Han +7
Large Language Models (LLMs) exhibit strong implicit personalization ability, yet most existing approaches treat this behavior as a black box, relying on prompt engineering or fine…
Beyond Message Passing: A Semantic View of Agent Communication Protocols
Dun Yuan, Fuyuan Lyu, Ye Yuan +11
Agent communication protocols are becoming critical infrastructure for large language model (LLM) systems that must use tools, coordinate with other agents, and operate across hete…
Optimizing User Profiles via Contextual Bandits for Retrieval-Augmented LLM Personalization
Linfeng Du, Ye Yuan, Zichen Zhao +8
Large language models (LLMs) excel at general-purpose tasks, yet adapting their responses to individual users remains challenging. Retrieval augmentation provides a lightweight alt…
Think Before You Act: Decision Transformers with Working Memory
Jikun Kang, Romain Laroche, Xingdi Yuan +3
Decision Transformer-based decision-making agents have shown the ability to generalize across multiple tasks. However, their performance relies on massive data and computation. We…
Multi-agent Attention Actor-Critic Algorithm for Load Balancing in Cellular Networks
Jikun Kang, Di Wu, Ju Wang +3
In cellular networks, User Equipment (UE) handoff from one Base Station (BS) to another, giving rise to the load balancing problem among the BSs. To address this problem, BSs can w…
Learning Multi-Objective Curricula for Robotic Policy Learning
Jikun Kang, Miao Liu, Abhinav Gupta +3
Various automatic curriculum learning (ACL) methods have been proposed to improve the sample efficiency and final performance of deep reinforcement learning (DRL). They are designe…