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This paper introduces RESCUE-BENCH, a benchmark for evaluating large language models on relation-aware emotional support in multi-party conversations, revealing limitations in current models' ability to model interpersonal dynamics.
This paper presents REAP, a two-stage pipeline for closed-book knowledge base construction from LLMs that combines relation-specific elicitation strategies with deterministic JSON parsing, achieving a macro-F1 of 0.62 on the AKBC Shared Task 2026 test set using Mistral-Small-24B-Instruct-2501.