Continually Improving Extractive QA via Human Feedback

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Continually Improving Extractive QA via Human Feedback

21 May 2023

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Papers citing "Continually Improving Extractive QA via Human Feedback"

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Title
DRS: Deep Question Reformulation With Structured Output Zhecheng Li Yijiao Wang Bryan Hooi Yujun Cai Nanyun Peng Kai-Wei Chang KELM 209 0 0 27 Nov 2024
Retrospective Learning from Interactions Zizhao Chen Mustafa Omer Gul Yiwei Chen Gloria Geng Anne Wu Yoav Artzi LRM 106 1 0 17 Oct 2024
CoGen: Learning from Feedback with Coupled Comprehension and Generation Mustafa Omer Gul Yoav Artzi 83 5 0 28 Aug 2024
An Empirical Study on Self-correcting Large Language Models for Data Science Code Generation Thai Tang Quoc Duc Ha Minh Tho Quan Thanh Anh Nguyen-Duc LRM 121 1 0 28 Aug 2024
I Could've Asked That: Reformulating Unanswerable Questions Wenting Zhao Ge Gao Claire Cardie Alexander M. Rush ELM 111 3 0 24 Jul 2024
RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs Shreyas Chaudhari Pranjal Aggarwal Vishvak Murahari Tanmay Rajpurohit Ashwin Kalyan Karthik Narasimhan Ameet Deshpande Bruno Castro da Silva 91 38 0 12 Apr 2024
Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies Liangming Pan Michael Stephen Saxon Wenda Xu Deepak Nathani Xinyi Wang William Yang Wang KELM LRM 116 216 0 06 Aug 2023
Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios Yilun Zhao Haowei Zhang Shengyun Si Linyong Nan Xiangru Tang Arman Cohan LMTD 104 12 0 24 May 2023
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages J. Clark Eunsol Choi Michael Collins Dan Garrette Tom Kwiatkowski Vitaly Nikolaev J. Palomaki 231 613 0 10 Mar 2020