Papers by Daniel Watson
LAW: Legal Agentic Workflows for Custody and Fund Services Contracts (2025.coling-industry)
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William Watson, Nicole Cho, Nishan Srishankar, Zhen Zeng, Lucas Cecchi, Daniel Scott, Suchetha Siddagangappa, Rachneet Kaur, Tucker Balch, Manuela Veloso
| Challenge: | Currently, there are limited resources available to build a legal domain-specific Large Language Model (LLM) however, legal contracts are highly varied not only in terms of semantics but also accessibility. |
| Approach: | They propose a Large Language Model (LLM) that integrates multiple specialized agents and text agents to respond to user queries. |
| Outcome: | The proposed model outperforms the baseline model in complex tasks such as calculating a contract’s termination date by 92.9% points. |
Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models (D18-1)
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| Challenge: | Recent advances in text normalization have limited applications in other languages . a novel approach to text normalizing uses character embeddings and word embedds . |
| Approach: | They propose a sequence-to-sequence model with character-based attention that uses pre-trained word embeddings to model subword information. |
| Outcome: | The proposed model achieves state-of-the-art F1 score on Arabic spelling correction task despite being small and unsuited for the task. |