Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code

25 August 2023

Papers citing "Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code"

8 / 8 papers shown

Title
QuestBench: Can LLMs ask the right question to acquire information in reasoning tasks? Belinda Z. Li Been Kim Z. Wang LRM 25 2 0 28 Mar 2025
ProductAgent: Benchmarking Conversational Product Search Agent with Asking Clarification Questions Jingheng Ye Yong Jiang Xiaobin Wang Yinghui Li Yangning Li Hai-Tao Zheng Pengjun Xie Fei Huang 27 0 0 01 Jul 2024
Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs Sylvain Kouemo Ngassom Arghavan Moradi Dakhel Florian Tambon Foutse Khomh 19 2 0 22 May 2024
Rethinking with Retrieval: Faithful Large Language Model Inference Hangfeng He Hongming Zhang Dan Roth KELM LRM 138 151 0 31 Dec 2022
Improving alignment of dialogue agents via targeted human judgements Amelia Glaese Nat McAleese Maja Trkebacz John Aslanides Vlad Firoiu ... John F. J. Mellor Demis Hassabis Koray Kavukcuoglu Lisa Anne Hendricks G. Irving ALM AAML 222 495 0 28 Sep 2022
Productivity Assessment of Neural Code Completion Albert Ziegler Eirini Kalliamvakou Shawn Simister Ganesh Sittampalam Alice Li Andrew Rice Devon Rifkin E. Aftandilian 102 176 0 13 May 2022
A Systematic Evaluation of Large Language Models of Code Frank F. Xu Uri Alon Graham Neubig Vincent J. Hellendoorn ELM ALM 193 624 0 26 Feb 2022
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation Yue Wang Weishi Wang Shafiq R. Joty S. Hoi 199 1,451 0 02 Sep 2021