Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach.

Param Kulkarni|Yingchi Liu|Hao-Ming Fu|Shaohua Yang|Isuru Gunasekara|Matt Peloquin|Noah Spitzer-Williams|Xiaotian Zhou|Xiaozhong Liu|Zhengping Ji|Yasser Ibrahim


Anthology ID:DBLP:conf/www/KulkarniLFYGPSZ25
Volume:Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025
Year:2025
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:2859-2862
URL:https://doi.org/10.1145/3701716.3715166
DOI:https://doi.org/10.1145/3701716.3715166
DBLP:conf/www/KulkarniLFYGPSZ25
BibTeX:
@inproceedings{kulkarni-2025-autodrafting, author = {Param Kulkarni and Yingchi Liu and Hao-Ming Fu and Shaohua Yang and Isuru Gunasekara and Matt Peloquin and Noah Spitzer-Williams and Xiaotian Zhou and Xiaozhong Liu and Zhengping Ji and Yasser Ibrahim}, editor = {Guodong Long and Michale Blumestein and Yi Chang and Liane Lewin-Eytan and Zi Huang and Elad Yom-Tov}, title = {{Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach}}, booktitle = {{Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025}}, pages = {2859--2862}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3701716.3715166}, doi = {https://doi.org/10.1145/3701716.3715166} }