CLAMBER: A Benchmark of Identifying and Clarifying Ambiguous Information
Needs in Large Language Models

CLAMBER: A Benchmark of Identifying and Clarifying Ambiguous Information Needs in Large Language Models

20 May 2024

Tong Zhang

Papers citing "CLAMBER: A Benchmark of Identifying and Clarifying Ambiguous Information Needs in Large Language Models"

6 / 6 papers shown

Title
Semantic Volume: Quantifying and Detecting both External and Internal Uncertainty in LLMs Xiaomin Li Zhou Yu Ziji Zhang Yingying Zhuang Shri Kiran Srinivasan Narayanan Sadagopan Anurag Beniwal HILM 60 0 0 28 Feb 2025
Can Tool-augmented Large Language Models be Aware of Incomplete Conditions? Seungbin Yang chaeHun Park Taehee Kim Jaegul Choo 46 2 0 18 Jun 2024
Asking Clarification Questions to Handle Ambiguity in Open-Domain QA Dongryeol Lee Segwang Kim Minwoo Lee Hwanhee Lee Joonsuk Park Sang-Woo Lee Kyomin Jung UQLM 60 13 0 23 May 2023
Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration Yang Deng Lizi Liao Liang Chen Hongru Wang Wenqiang Lei Tat-Seng Chua 86 79 0 23 May 2023
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 339 12,003 0 04 Mar 2022
Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions Mohammad Aliannejadi Julia Kiseleva A. Chuklin Jeffrey Stephen Dalton Andrey Kravchenko 76 97 0 13 Sep 2021