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Agents, Think Only When it Helps
Min-Seon Kim, Seungdong Yoa, Sanghyu Yoon +4
LLM agent distillation transfers agentic capabilities to student models by training on complete teacher trajectories that typically interleave thoughts and actions. We question how…
Efficient Multi-Agent Reasoning via Confidence-Guided Adaptive Debate
Seungdong Yoa, Ye Seul Sim, Suhee Yoon +5
Multi-agent debate has shown promise for improving the reasoning of large language models, yet recent theory suggests its benefits are highly regime-dependent. While interaction ca…
ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection
Sanghyu Yoon, Dongmin Kim, Suhee Yoon +6
In tabular anomaly detection (AD), textual semantics often carry critical signals, as the definition of an anomaly is closely tied to domain-specific context. However, existing ben…