Large language models are increasingly used as math tutors, raising two questions: can a single LLM detect a student's error, diagnose the underlying misconception, and remediate it through multi-turn dialogue - and can we trust the numbers that report how well it does? We address both with MISCONCEPTDIALOGUE, a fully...
Woo-Jin Lee, Yoonkyu Woo, Jinah Kim et al.· 0 citations
End-to-end research agents can now produce complete scientific papers, yet manuscript claims often diverge from executed experiments. This gap is structural: research state, failure histories, and claim-evidence alignment are not maintained as persistent, verifiable state across long-horizon pipelines. We present YouRA...
Experiments on MultiWOZ 2.1 show that the proposed RLHF approach consistently improves corpus‐based evaluation over supervised baselines, while simulator‐based effects remain mixed and backbone‐dependent.
Fundamental trade-offs are revealed: domain-invariant features enable zero-shot deployment when no real data exists, while SSL methods achieve higher performance but require real samples and compute.
Jeongmin Lee, Seung Yun, Minkyu Lee et al.· 0 citations
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