Papers by Haesung Pyun
Don’t Adapt Small Language Models for Tools; Adapt Tool Schemas to the Models (2026.acl-long)
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| Challenge: | Small language models struggle with tool-use tasks, particularly in selecting appropriate tools and identifying correct parameters. |
| Approach: | They propose a training-free method that leverages peakedness to align schemas with pretraining knowledge to rename tool components. |
| Outcome: | Experiments on MetaTool and RoTBench show that PA-Tool significantly improves tool-use accuracy without retraining. |
Improving Dialogue State Tracking through Combinatorial Search for In-Context Examples (2025.acl-long)
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| Challenge: | Existing methods for training dialogue state tracking data are suboptimal . existing methods rely on suboptimized data, resulting in poor performance . |
| Approach: | They propose a method that scores effective in-context examples based on their combinatorial impact on DST performance. |
| Outcome: | The proposed method achieves a 20% gain in data efficiency and generalizing well to the SGD dataset. |