1 citations · 2 across the 5 of their papers we have counts for
5 papers
Mind the Generation Process: Fine-Grained Confidence Estimation During LLM Generation
Jinyi Han, Tingyun Li, Shisong Chen +8
While large language models (LLMs) have demonstrated remarkable performance across diverse tasks, they fundamentally lack self-awareness and frequently exhibit overconfidence, assi…
DEEPER Insight into Your User: Directed Persona Refinement for Dynamic Persona Modeling
Aili Chen, Chengyu Du, Jiangjie Chen +6
To advance personalized applications such as recommendation systems and user behavior prediction, recent research increasingly adopts large language models (LLMs) for human -readab…
Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Chengyu Du, Jinyi Han, Yizhou Ying +9
Recent advancements in large language models (LLMs) have demonstrated that progressive refinement, rather than providing a single answer, results in more accurate and thoughtful ou…
AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation
Wenhao Huang, Zhouhong Gu, Chenghao Peng +5
Web scraping is a powerful technique that extracts data from websites, enabling automated data collection, enhancing data analysis capabilities, and minimizing manual data entry ef…
Character is Destiny: Can Role-Playing Language Agents Make Persona-Driven Decisions?
Rui Xu, Xintao Wang, Jiangjie Chen +6
Can Large Language Models (LLMs) simulate humans in making important decisions? Recent research has unveiled the potential of using LLMs to develop role-playing language agents (RP…