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LLM reranker leads ADHD symptom sentence ranking at eRisk 2026

Researchers from DS@GT-ARC have developed a system for the eRisk 2026 Task 3, which involves ranking Reddit sentences based on their relevance to 18 symptoms of attention deficit hyperactivity disorder (ADHD). Due to the absence of annotated training data, the team employed zero-shot experimentation and unsupervised retrieval methods. Their approach combines BM25 retrieval with evidence-aware rescoring, embedding-based reranking, query-prototype expansion, and LLM-based reranking, with the LLM reranker achieving the best official scores. AI

IMPACT Demonstrates LLM reranking effectiveness in zero-shot scenarios for specialized information retrieval tasks.

RANK_REASON Academic paper detailing a system submission for a specific task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM reranker leads ADHD symptom sentence ranking at eRisk 2026

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0 / 100
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Academic paper detailing a system submission for a specific task. [lever_c_demoted from research: ic=1 ai=1.0]
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paper, other
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High
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52 days old
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · David Guecha ·

    DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM Reranking for ADHD Symptom Sentences

    arXiv:2608.03883v1 Announce Type: new Abstract: This paper describes our submissions to eRisk 2026 Task 3, ADHD Symptom Sentence Ranking. The task requires systems to rank candidate Reddit sentences according to their relevance to each of the 18 symptoms in the Adult ADHD Self-Re…