23 citations · 29 across the 8 of their papers we have counts for
9 papers
Pathways of Thoughts: Multi-Directional Thinking for Long-form Personalized Question Answering
Alireza Salemi, Cheng Li, Mingyang Zhang +7
Personalization is well studied in search and recommendation, but personalized question answering remains underexplored due to challenges in inferring preferences from long, noisy,…
Reasoning-Enhanced Self-Training for Long-Form Personalized Text Generation
Alireza Salemi, Cheng Li, Mingyang Zhang +6
Personalized text generation requires a unique ability of large language models (LLMs) to learn from context that they often do not encounter during their standard training. One wa…
Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach
Zhuowan Li, Cheng Li, Mingyang Zhang +2
Retrieval Augmented Generation (RAG) has been a powerful tool for Large Language Models (LLMs) to efficiently process overly lengthy contexts. However, recent LLMs like Gemini-1.5…
Bridging the Preference Gap between Retrievers and LLMs
Zixuan Ke, Weize Kong, Cheng Li +3
Large Language Models (LLMs) have demonstrated superior results across a wide range of tasks, and Retrieval-augmented Generation (RAG) is an effective way to enhance the performanc…
Unlocking the `Why' of Buying: Introducing a New Dataset and Benchmark for Purchase Reason and Post-Purchase Experience
Tao Chen, Siqi Zuo, Cheng Li +3
In business and marketing, analyzing the reasons behind buying is a fundamental step towards understanding consumer behaviors, shaping business strategies, and predicting market ou…
PRewrite: Prompt Rewriting with Reinforcement Learning
Weize Kong, Spurthi Amba Hombaiah, Mingyang Zhang +2
Prompt engineering is critical for the development of LLM-based applications. However, it is usually done manually in a "trial and error" fashion that can be time consuming, ineffe…
Creator Context for Tweet Recommendation
Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang +6
When discussing a tweet, people usually not only refer to the content it delivers, but also to the person behind the tweet. In other words, grounding the interpretation of the twee…
Automated Evaluation of Personalized Text Generation using Large Language Models
Yaqing Wang, Jiepu Jiang, Mingyang Zhang +4
Personalized text generation presents a specialized mechanism for delivering content that is specific to a user's personal context. While the research progress in this area has bee…
Learning to Rewrite Prompts for Personalized Text Generation
Cheng Li, Mingyang Zhang, Qiaozhu Mei +2
Facilitated by large language models (LLMs), personalized text generation has become a rapidly growing research direction. Most existing studies focus on designing specialized mode…