Papers by Reza Averly

2 papers
Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework (2025.naacl-long)

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Challenge: Recent studies have demonstrated that large language models (LLMs) can perform in named entity recognition tasks.
Approach: They propose a framework for clinical named entity recognition that decomposes the entity recognition task into several retrievals of sub-types and then filters them.
Outcome: The proposed framework improves on the clinical named entity recognition task.
LIDDIA: Language-based Intelligent Drug Discovery Agent (2025.emnlp-main)

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Challenge: Recent advances in artificial intelligence for chemistry have sought to expedite individual drug discovery tasks.
Approach: They propose an autonomous agent capable of intelligently navigating the drug discovery process in silico.
Outcome: The proposed agent can generate molecules meeting key pharmaceutical criteria on over 70% of 30 clinically relevant targets and intelligently balances exploration and exploitation in the chemical space.

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