3 papers
cs.CL2026
Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions
Yoonah Park, Haesung Pyun, Yohan Jo
While large language models (LLMs) perform strongly on diverse tasks, their trustworthiness is limited by erratic behavior that is unfaithful to their internal knowledge. In partic…
cs.CL2026
Don't Adapt Small Language Models for Tools; Adapt Tool Schemas to the Models
Jonggeun Lee, Woojung Song, Jongwook Han +2
Small language models (SLMs) enable scalable tool-augmented multi-agent systems where multiple SLMs handle subtasks orchestrated by a powerful coordinator. However, they struggle w…
cs.CL2025
Improving Dialogue State Tracking through Combinatorial Search for In-Context Examples
Haesung Pyun, Yoonah Park, Yohan Jo
In dialogue state tracking (DST), in-context learning comprises a retriever that selects labeled dialogues as in-context examples and a DST model that uses these examples to infer…