7 citations · 14 across the 6 of their papers we have counts for
6 papers
MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise
Chunyuan Deng, Xiangru Tang, Yilun Zhao +5
Recently, large language models (LLMs) have evolved into interactive agents, proficient in planning, tool use, and task execution across a wide variety of tasks. However, without s…
On Evaluating the Integration of Reasoning and Action in LLM Agents with Database Question Answering
Linyong Nan, Ellen Zhang, Weijin Zou +3
This study introduces a new long-form database question answering dataset designed to evaluate how Large Language Models (LLMs) interact with a SQL interpreter. The task necessitat…
L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models
Ansong Ni, Pengcheng Yin, Yilun Zhao +11
Recently, large language models (LLMs), especially those that are pretrained on code, have demonstrated strong capabilities in generating programs from natural language inputs in a…
ODSum: New Benchmarks for Open Domain Multi-Document Summarization
Yijie Zhou, Kejian Shi, Wencai Zhang +3
Open-domain Multi-Document Summarization (ODMDS) is a critical tool for condensing vast arrays of documents into coherent, concise summaries. With a more inter-related document set…
Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies
Linyong Nan, Yilun Zhao, Weijin Zou +5
In-context learning (ICL) has emerged as a new approach to various natural language processing tasks, utilizing large language models (LLMs) to make predictions based on context th…
LoFT: Enhancing Faithfulness and Diversity for Table-to-Text Generation via Logic Form Control
Yilun Zhao, Zhenting Qi, Linyong Nan +2
Logical Table-to-Text (LT2T) generation is tasked with generating logically faithful sentences from tables. There currently exists two challenges in the field: 1) Faithfulness: how…