Papers by Chris Brown

3 papers
Human and LLM-Based Resume Matching: An Observational Study (2025.findings-naacl)

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Challenge: Resume matching assesses the extent to which candidates qualify for jobs based on the content of resumes.
Approach: They compare GPT-4 and human ratings for resumes submitted to job openings from diverse fields using real-world evaluation criteria.
Outcome: The proposed model improves the quality of LLM ratings and does not show bias.
Human-in-the-loop Schema Induction (2023.acl-demo)

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Challenge: Existing approaches to event-centric natural language understanding (NLU) have been limited to linear and temporal ones.
Approach: They propose a human-in-the-loop schema induction system powered by GPT-3 . they show that it transfers to new domains more easily than previous approaches .
Outcome: The proposed system transfers to new domains more easily than previous approaches and reduces human curation.
RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System (2021.naacl-demos)

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Challenge: We present a new information extraction system that can construct temporal event graphs from news documents.
Approach: They propose a temporal event graph extraction system that can extract news documents . they extend the system from sentence-level event extraction to cross-document cross-media event extraction .
Outcome: The proposed system can extract temporal event graphs from news documents in multiple languages and multiple data modalities.

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