The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct Representation

2 May 2024

Papers citing "The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct Representation"

8 / 8 papers shown

Title
M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation Zhaopeng Feng Jiayuan Su Jiamei Zheng Jiahan Ren Yan Zhang Jian Wu Hongwei Wang Zuozhu Liu ELM 198 0 0 21 Feb 2025
Can LLMs Rank the Harmfulness of Smaller LLMs? We are Not There Yet Berk Atil Vipul Gupta Sarkar Snigdha Sarathi Das R. Passonneau 71 0 0 07 Feb 2025
MBIAS: Mitigating Bias in Large Language Models While Retaining Context Shaina Raza Ananya Raval Veronica Chatrath 34 6 0 18 May 2024
SemEval-2023 Task 11: Learning With Disagreements (LeWiDi) Elisa Leonardelli Alexandra Uma Gavin Abercrombie Dina Almanea Valerio Basile Tommaso Fornaciari Barbara Plank Verena Rieser Massimo Poesio 37 41 0 28 Apr 2023
Stop Measuring Calibration When Humans Disagree Joris Baan Wilker Aziz Barbara Plank Raquel Fernández 16 53 0 28 Oct 2022
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 2,712 0 24 May 2022
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 301 11,730 0 04 Mar 2022
Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement Elisa Leonardelli Stefano Menini Alessio Palmero Aprosio Marco Guerini Sara Tonelli 36 97 0 28 Sep 2021