Papers by Tzu-Hsin Chou
NASH: Numerically Aware Scoring Heuristic for Robust Semantic Similarity (2026.findings-acl)
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| Challenge: | Numerical precision is critical in financial NLP, yet embedding-based semantic similarity metrics exhibit numerical blindness. |
| Approach: | They propose a model-agnostic metric that decouples numerical verification from textual semantic evaluation. |
| Outcome: | The proposed metric improves numerical sensitivity while maintaining general semantic performance. |