5 citations · 11 across the 5 of their papers we have counts for
6 papers
ClinEdge: An Expert-Graded Benchmark of Real Patient Edge Cases Where Frontier Multimodal Models Fail
Anurag Sharma, Aditya Sharma, Sapna Baalwan
Most benchmarks for large language models in medicine are built from licensing examinations and theoretical questions. The few that draw on real clinical data do so only in part, a…
PROSLEX: A Novel Dataset for Expert-Annotated Legal Statute Prediction for Indian Judiciary
Subinay Adhikary, Upal Bhattacharya, Vivek Kumar Singh +6
Legal Statute Prediction (LSP) involves automatically identifying relevant legal statutes given factual descriptions in legal documents, typically framed as a multi-label classific…
REMEDI: A Benchmark for Retention and Unlearning Evaluation in Multi-label Clinical Disease Inference
Anurag Sharma, Sai Teja Chunchu, Prasenjit Mitra +2
Language models trained for clinical disease inference are trained on patient data, which may include sensitive and private information, and data owners may request the removal of…
Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts
Shubham Kumar Nigam, Anurag Sharma, Danush Khanna +3
In the era of Large Language Models (LLMs), predicting judicial outcomes poses significant challenges due to the complexity of legal proceedings and the scarcity of expert-annotate…
LaMSUM: Amplifying Voices Against Harassment through LLM Guided Extractive Summarization of User Incident Reports
Garima Chhikara, Anurag Sharma, V. Gurucharan +2
Citizen reporting platforms help the public and authorities stay informed about sexual harassment incidents. However, the high volume of data shared on these platforms makes review…
Few-Shot Fairness: Unveiling LLM's Potential for Fairness-Aware Classification
Garima Chhikara, Anurag Sharma, Bhaskara Hanuma Vedula +3
Large Language Models (LLMs) are increasingly being employed for downstream tasks such as tabular classification, where predictions can directly influence individuals in high-stake…