A survey on bias in machine learning research

A Mikołajczyk-Bareła, M Grochowski - arxiv preprint arxiv:2308.11254, 2023 - arxiv.org
Current research on bias in machine learning often focuses on fairness, while overlooking
the roots or causes of bias. However, bias was originally defined as a" systematic error," …

A natural language processing approach to detect inconsistencies in death investigation notes attributing suicide circumstances

S Wang, Y Zhou, Z Han, C Tao, Y **ao, Y Ding… - Communications …, 2024 - nature.com
Background Data accuracy is essential for scientific research and policy development. The
National Violent Death Reporting System (NVDRS) data is widely used for discovering the …

The Problem of Coherence in Natural Language Explanations of Recommendations

J Raczyński, M Lango, J Stefanowski - ECAI 2023, 2023 - ebooks.iospress.nl
Providing natural language explanations for recommendations is particularly useful from the
perspective of a non-expert user. Although several methods for providing such explanations …

Statistical dataset evaluation: Reliability, difficulty, and validity

C Wang, Q Dong, X Wang, H Wang, Z Sui - arxiv preprint arxiv …, 2022 - arxiv.org
Datasets serve as crucial training resources and model performance trackers. However,
existing datasets have exposed a plethora of problems, inducing biased models and …

ChatEL: Entity Linking with Chatbots

Y Ding, Q Zeng, T Weninger - arxiv preprint arxiv:2402.14858, 2024 - arxiv.org
Entity Linking (EL) is an essential and challenging task in natural language processing that
seeks to link some text representing an entity within a document or sentence with its …

Uncovering Misattributed Suicide Causes through Annotation Inconsistency Detection in Death Investigation Notes

S Wang, Y Zhou, Z Han, C Tao, Y **ao, Y Ding… - arxiv preprint arxiv …, 2024 - arxiv.org
Data accuracy is essential for scientific research and policy development. The National
Violent Death Reporting System (NVDRS) data is widely used for discovering the patterns …

Statistical dataset evaluation: A case study on named entity recognition

C Wang, Q Dong, X Wang, Z Sui - Natural Language Processing, 2025 - cambridge.org
Datasets serve as crucial training resources and model performance trackers. However,
existing datasets have exposed a plethora of problems, inducing biased models and …

Review of Technology Term Recognition Studies Based on Machine Learning

H Yamin, W **aoyan, C Fang - Data Analysis and …, 2022 - manu44.magtech.com.cn
[Objective] This paper reviews the status quo and future directions of technology term
recognition studies based on machine learning.[Coverage] We searched “technology term …

Using Custom NER Models to Extract DOD Specific Entities from Contracts

KP Haberstich - 2021 - scholar.afit.edu
Abstract The Air Force Sustainment Center collected 3.7 million contracts onto the Air Force
Research Laboratory's high power computers. They are in the format of a. pdf or scanned …

[HTML][HTML] A survey on bias in machine learning research

AMBM Grochowski - ar5iv.org
Current research on bias in machine learning often focuses on fairness, while overlooking
the roots or causes of bias. However, bias was originally defined as a” systematic error,” …