activity
20242026
collaborators

5 papers

cs.CL2026

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents

Sam Yu-Te Lee, Chenyang Ji, Shicheng Wen +3

Text analytics has traditionally required specialized knowledge in Natural Language Processing (NLP) or text analysis, which presents a barrier for entry-level analysts. Recent adv…

cs.AI2026

From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models

Jiaxin Zhang, Wendi Cui, Zhuohang Li +4

While Large Language Models (LLMs) show remarkable capabilities, their unreliability remains a critical barrier to deployment in high-stakes domains. This survey charts a functiona…

cs.CL2025

RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models

Bang An, Shiyue Zhang, Mark Dredze

Efforts to ensure the safety of large language models (LLMs) include safety fine-tuning, evaluation, and red teaming. However, despite the widespread use of the Retrieval-Augmented…

cs.CL2024

DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models

Yiming Huang, Jianwen Luo, Yan Yu +8

We introduce DA-Code, a code generation benchmark specifically designed to assess LLMs on agent-based data science tasks. This benchmark features three core elements: First, the ta…

cs.CL2024

TrustLLM: Trustworthiness in Large Language Models

Yue Huang, Lichao Sun, Haoran Wang +67

Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…