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cs.CL2026
Quantifying Faithful Confidence Expression in Large Reasoning Models
Areeb Gani, Asal Meskin, Gabrielle Kaili-May Liu +1
Reliable uncertainty communication is critical to the trustworthiness of LLMs, yet faithful calibration (FC)--the alignment between models' intrinsic and (linguistically) expressed…
cs.CL2026
Can LLMs Use Linguistic Uncertainty Markers to Reliably Reflect Intrinsic Confidence?
Gabrielle Kaili-May Liu, Arman Cohan
LLMs' linguistically expressed confidence should faithfully reflect their intrinsic uncertainty. While recent work shows LLMs struggle to use epistemic markers (e.g., "it is likely…
cs.CL2026
Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents?
Leyao Wang, Yanan He, Peng Chen +5
Deep research agents increasingly automate complex information-seeking tasks, producing evidence-grounded reports via multi-step reasoning, tool use, and synthesis. Their growing r…