3 citations · 9 across the 8 of their papers we have counts for
8 papers
CoRT: Code-integrated Reasoning within Thinking
Chengpeng Li, Zhengyang Tang, Ziniu Li +8
Large Reasoning Models (LRMs) like o1 and DeepSeek-R1 have shown remarkable progress in natural language reasoning with long chain-of-thought (CoT), yet they remain inefficient or…
Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning
Keqin Bao, Ming Yan, Yang Zhang +4
Frequently updating Large Language Model (LLM)-based recommender systems to adapt to new user interests -- as done for traditional ones -- is impractical due to high training costs…
Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation
Yang Zhang, Juntao You, Yimeng Bai +4
Recent advancements in recommender systems have focused on leveraging Large Language Models (LLMs) to improve user preference modeling, yielding promising outcomes. However, curren…
GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation
Shihao Cai, Keqin Bao, Hangyu Guo +3
Large language models have seen widespread adoption in math problem-solving. However, in geometry problems that usually require visual aids for better understanding, even the most…
Text-like Encoding of Collaborative Information in Large Language Models for Recommendation
Yang Zhang, Keqin Bao, Ming Yan +3
When adapting Large Language Models for Recommendation (LLMRec), it is crucial to integrate collaborative information. Existing methods achieve this by learning collaborative embed…
Prospect Personalized Recommendation on Large Language Model-based Agent Platform
Jizhi Zhang, Keqin Bao, Wenjie Wang +5
The new kind of Agent-oriented information system, exemplified by GPTs, urges us to inspect the information system infrastructure to support Agent-level information processing and…