Lawyers are Dishonest? Quantifying Representational Harms in Commonsense
Knowledge Resources

Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources

21 March 2021

Ninareh Mehrabi

Fred Morstatter

Xiang Ren

Papers citing "Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources"

16 / 16 papers shown

Title
Ask LLMs Directly, "What shapes your bias?": Measuring Social Bias in Large Language Models Jisu Shin Hoyun Song Huije Lee Soyeong Jeong Jong C. Park 38 6 0 06 Jun 2024
Graph Reasoning for Question Answering with Triplet Retrieval Shiyang Li Yifan Gao Hao Jiang Qingyu Yin Zheng Li Xifeng Yan Chao Zhang Bing Yin RALM ReLM 18 29 0 30 May 2023
Similarity-weighted Construction of Contextualized Commonsense Knowledge Graphs for Knowledge-intense Argumentation Tasks Moritz Plenz Juri Opitz Philipp Heinisch Philipp Cimiano Anette Frank 30 9 0 15 May 2023
Deep Bidirectional Language-Knowledge Graph Pretraining Michihiro Yasunaga Antoine Bosselut Hongyu Ren Xikun Zhang Christopher D. Manning Percy Liang J. Leskovec 36 193 0 17 Oct 2022
The State of Profanity Obfuscation in Natural Language Processing Debora Nozza Dirk Hovy 42 7 0 14 Oct 2022
The Lifecycle of "Facts": A Survey of Social Bias in Knowledge Graphs Angelie Kraft Ricardo Usbeck KELM 32 9 0 07 Oct 2022
PInKS: Preconditioned Commonsense Inference with Minimal Supervision Ehsan Qasemi Piyush Khanna Qiang Ning Muhao Chen ReLM LRM 30 8 0 16 Jun 2022
Target-Guided Dialogue Response Generation Using Commonsense and Data Augmentation Prakhar Gupta Harsh Jhamtani Jeffrey P. Bigham 49 12 0 19 May 2022
Towards Multi-Objective Statistically Fair Federated Learning Ninareh Mehrabi Cyprien de Lichy John McKay C. He William Campbell FedML 30 9 0 24 Jan 2022
Refined Commonsense Knowledge from Large-Scale Web Contents Tuan-Phong Nguyen Simon Razniewski Julien Romero Gerhard Weikum 39 32 0 30 Nov 2021
Think Before You Speak: Explicitly Generating Implicit Commonsense Knowledge for Response Generation Pei Zhou Karthik Gopalakrishnan Behnam Hedayatnia Seokhwan Kim Jay Pujara Xiang Ren Yang Liu Dilek Z. Hakkani-Tür 39 41 0 16 Oct 2021
On Measures of Biases and Harms in NLP Sunipa Dev Emily Sheng Jieyu Zhao Aubrie Amstutz Jiao Sun ... M. Sanseverino Jiin Kim Akihiro Nishi Nanyun Peng Kai-Wei Chang 31 80 0 07 Aug 2021
RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms Pei Zhou Rahul Khanna Seyeon Lee Bill Yuchen Lin Daniel E. Ho Jay Pujara Xiang Ren ReLM 19 36 0 02 May 2020
The Woman Worked as a Babysitter: On Biases in Language Generation Emily Sheng Kai-Wei Chang Premkumar Natarajan Nanyun Peng 223 618 0 03 Sep 2019
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 425 2,588 0 03 Sep 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 329 4,223 0 23 Aug 2019