338 citations · 387 across the 10 of their papers we have counts for
11 papers
SocialCoach: Personalized Social Skill Learning with Agentic Tutoring and Practice
Tianfu Wang, Max Xiong, Jianxun Lian +9
Social skills such as negotiation and leadership are crucial for personal and professional success in today's interconnected world. However, scalable and effective training remains…
EvoDesign: Agentic Editable Diagram Creation via Design Expertise Evolution
Tianfu Wang, Leilei Ding, Ziyang Tao +13
High-fidelity diagram creation requires the complex orchestration of semantic topology, visual styling, and spatial layout, posing a significant challenge for automated systems. Ex…
Social-R1: Towards Human-like Social Reasoning in LLMs
Jincenzi Wu, Yuxuan Lei, Jianxun Lian +5
While large language models demonstrate remarkable capabilities across numerous domains, social intelligence - the capacity to perceive social cues, infer mental states, and genera…
HumanLLM: Towards Personalized Understanding and Simulation of Human Nature
Yuxuan Lei, Tianfu Wang, Jianxun Lian +3
Motivated by the remarkable progress of large language models (LLMs) in objective tasks like mathematics and coding, there is growing interest in their potential to simulate human…
Interactive AI NPCs Powered by LLMs: Technical Report for the CPDC Challenge 2025
Yitian Huang, Yuxuan Lei, Jianxun Lian +1
This report presents the solution and results of our team MSRA\_SC in the Commonsense Persona-Grounded Dialogue Challenge (CPDC 2025). We propose a simple yet effective framework t…
Population-Aligned Persona Generation for LLM-based Social Simulation
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao +7
Recent advances in large language models (LLMs) have enabled human-like social simulations at unprecedented scale and fidelity, offering new opportunities for computational social…
RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems
Jianxun Lian, Yuxuan Lei, Xu Huang +3
This paper introduces RecAI, a practical toolkit designed to augment or even revolutionize recommender systems with the advanced capabilities of Large Language Models (LLMs). RecAI…
Aligning Language Models for Versatile Text-based Item Retrieval
Yuxuan Lei, Jianxun Lian, Jing Yao +3
This paper addresses the gap between general-purpose text embeddings and the specific demands of item retrieval tasks. We demonstrate the shortcomings of existing models in capturi…
RecExplainer: Aligning Large Language Models for Explaining Recommendation Models
Yuxuan Lei, Jianxun Lian, Jing Yao +3
Recommender systems are widely used in online services, with embedding-based models being particularly popular due to their expressiveness in representing complex signals. However,…
Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations
Xu Huang, Jianxun Lian, Yuxuan Lei +3
Recommender models excel at providing domain-specific item recommendations by leveraging extensive user behavior data. Despite their ability to act as lightweight domain experts, t…
When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities
Jin Chen, Zheng Liu, Xu Huang +9
The advent of large language models marks a revolutionary breakthrough in artificial intelligence. With the unprecedented scale of training and model parameters, the capability of…