Papers by Huiyu Li

2 papers
SERM: Self-Evolving Relevance Model with Agent-Driven Learning from Massive Query Streams (2026.findings-acl)

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Challenge: Existing approaches to generate relevance judgments are limited due to dynamic nature of query distributions.
Approach: They propose a self-evolving relevance model approach to generalize queries to practical search scenarios . they use a multi-agent sample miner and a relevance annotator to generate reliable labels .
Outcome: The proposed approach can achieve significant performance gains on a large-scale industrial platform, validated by offline multilingual evaluations and online testing.
Dataset and Enhanced Model for Eligibility Criteria-to-SQL Semantic Parsing (2020.lrec-1)

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Challenge: Clinical trials require that patients meet eligibility criteria to ensure safety and effectiveness of studies.
Approach: They propose a dataset that includes the first-of-its-kind eligibility-criteria corpus and queries for criteria-to-sql . they propose 'neuro semantic parser' which can translate eligibility criteria to executable SQL queries .
Outcome: The proposed parser outperforms existing state-of-the-art general-purpose models while highlighting the challenges presented by the new dataset.

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