1 citations · 1 across the 2 of their papers we have counts for
6 papers
Code as Agent Harness
Xuying Ning, Katherine Tieu, Dongqi Fu +39
Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to repository-level software engineerin…
Agentic Reasoning for Large Language Models
Tianxin Wei, Ting-Wei Li, Zhining Liu +26
Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) demonstrate strong reasoning capabilitie…
AutoDCWorkflow: LLM-based Data Cleaning Workflow Auto-Generation and Benchmark
Lan Li, Liri Fang, Bertram Ludäscher +1
Data cleaning is a time-consuming and error-prone manual process, even with modern workflow tools such as OpenRefine. We present AutoDCWorkflow, an LLM-based pipeline for automatic…
ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method
Dongqi Fu, Yada Zhu, Zhining Liu +10
Climate science studies the structure and dynamics of Earth's climate system and seeks to understand how climate changes over time, where the data is usually stored in the format o…
What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs
Dongqi Fu, Liri Fang, Zihao Li +3
Graphs, as a relational data structure, have been widely used for various application scenarios, like molecule design and recommender systems. Recently, large language models (LLMs…
T-KAER: Transparency-enhanced Knowledge-Augmented Entity Resolution Framework
Lan Li, Liri Fang, Yiren Liu +2
Entity resolution (ER) is the process of determining whether two representations refer to the same real-world entity and plays a crucial role in data curation and data cleaning. Re…