22 citations · 22 across the 4 of their papers we have counts for
7 papers
Don't Start Over: A Cost-Effective Framework for Migrating Personalized Prompts Between LLMs
Ziyi Zhao, Chongming Gao, Yang Zhang +5
Personalization in Large Language Models (LLMs) often relies on user-specific soft prompts. However, these prompts become obsolete when the foundation model is upgraded, necessitat…
MGFRec: Towards Reinforced Reasoning Recommendation with Multiple Groundings and Feedback
Shihao Cai, Chongming Gao, Haoyan Liu +4
The powerful reasoning and generative capabilities of large language models (LLMs) have inspired researchers to apply them to reasoning-based recommendation tasks, which require in…
Navigating Through Paper Flood: Advancing LLM-based Paper Evaluation through Domain-Aware Retrieval and Latent Reasoning
Wuqiang Zheng, Yiyan Xu, Xinyu Lin +3
With the rapid and continuous increase in academic publications, identifying high-quality research has become an increasingly pressing challenge. While recent methods leveraging La…
K-order Ranking Preference Optimization for Large Language Models
Shihao Cai, Chongming Gao, Yang Zhang +5
To adapt large language models (LLMs) to ranking tasks, existing list-wise methods, represented by list-wise Direct Preference Optimization (DPO), focus on optimizing partial-order…
Process-Supervised LLM Recommenders via Flow-guided Tuning
Chongming Gao, Mengyao Gao, Chenxiao Fan +3
While large language models (LLMs) are increasingly adapted for recommendation systems via supervised fine-tuning (SFT), this approach amplifies popularity bias due to its likeliho…
Fine-grained Alignment of Large Language Models for General Medication Recommendation without Overprescription
Zihao Zhao, Chenxiao Fan, Junlong Liu +5
Large language models (LLMs) holds significant promise in achieving general medication recommendation systems owing to their comprehensive interpretation of clinical notes and flex…