Papers with expert feedback

2 papers
STACKFEED: Structured Textual Actor-Critic Knowledge base editing with FEEDback (2025.emnlp-industry)

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Challenge: Large Language Models (LLMs) often generate incorrect or outdated information, especially in low-resource settings or when dealing with private data.
Approach: They propose a framework that iteratively refines the knowledge base based on expert feedback . they define a ReACT actor agent on each document to perform structured edits .
Outcome: The proposed framework improves the quality and performance of the RAG system on low-resource programming problems, modified Python packages, and factual question-answering tasks.
CentaurTA: A Self-Improving Human-Agents Collaboration Framework for Thematic Analysis (2026.findings-acl)

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Challenge: Existing large language model approaches for qualitative analysis are labor-intensive and costly.
Approach: They propose an iterative human–agent framework for scalable thematic analysis that integrates structured human feedback with rubric-based evaluation.
Outcome: The proposed framework improves coding alignment and transparency across multiple datasets, baselines, and LLM families.

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