CUE-R uses REMOVE, REPLACE, and DUPLICATE interventions on individual evidence items to quantify their per-item utility in RAG along correctness, grounding faithfulness, and confidence axes.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
CONDITIONAL 2representative citing papers
AgenticPosesRanker ranks docking poses using six deterministic physical tools and LLM reasoning, achieving 50% best-pose accuracy that matches the Smina baseline on a balanced 10-system, 162-pose benchmark.
citing papers explorer
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CUE-R: Beyond the Final Answer in Retrieval-Augmented Generation
CUE-R uses REMOVE, REPLACE, and DUPLICATE interventions on individual evidence items to quantify their per-item utility in RAG along correctness, grounding faithfulness, and confidence axes.
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AgenticPosesRanker: An Agentic AI Framework for Physically Grounded Ranking of Protein-Ligand Docking Poses
AgenticPosesRanker ranks docking poses using six deterministic physical tools and LLM reasoning, achieving 50% best-pose accuracy that matches the Smina baseline on a balanced 10-system, 162-pose benchmark.