Papers by Suchetha Siddagangappa
LAW: Legal Agentic Workflows for Custody and Fund Services Contracts (2025.coling-industry)
Copied to clipboard
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. |
Large Language Models as Financial Data Annotators: A Study on Effectiveness and Efficiency (2024.lrec-main)
Copied to clipboard
Toyin D. Aguda, Suchetha Siddagangappa, Elena Kochkina, Simerjot Kaur, Dongsheng Wang, Charese Smiley
| Challenge: | Large Language Models (LLMs) have demonstrated remarkable performance in data annotation tasks on general domain datasets, but their effectiveness on domain specific datasets remains under-explored. |
| Approach: | They compare the annotations produced by three LLMs against expert annotators and crowdworkers. |
| Outcome: | The proposed models outperform expert crowdworkers and crowd-sourced annotators on domain specific datasets. |