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AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective Intelligence

AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective Intelligence

18 April 2024
Minbeom Kim
Hwanhee Lee
Joonsuk Park
Hwaran Lee
Kyomin Jung
ArXivPDFHTML

Papers citing "AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective Intelligence"

3 / 3 papers shown
Title
Are LLM-Judges Robust to Expressions of Uncertainty? Investigating the effect of Epistemic Markers on LLM-based Evaluation
Are LLM-Judges Robust to Expressions of Uncertainty? Investigating the effect of Epistemic Markers on LLM-based Evaluation
Dongryeol Lee
Yerin Hwang
Yongil Kim
Joonsuk Park
Kyomin Jung
ELM
68
4
0
28 Oct 2024
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally
  Across Scales and Tasks
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
Xiao Liu
Kaixuan Ji
Yicheng Fu
Weng Lam Tam
Zhengxiao Du
Zhilin Yang
Jie Tang
VLM
236
780
0
14 Oct 2021
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information
  Retrieval Models
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Nandan Thakur
Nils Reimers
Andreas Rucklé
Abhishek Srivastava
Iryna Gurevych
VLM
229
961
0
17 Apr 2021
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