199 citations · 412 across the 10 of their papers we have counts for
6 papers · 1 filter
Gemini Goes to Med School: Exploring the Capabilities of Multimodal Large Language Models on Medical Challenge Problems & Hallucinations
Ankit Pal, Malaikannan Sankarasubbu
Large language models have the potential to be valuable in the healthcare industry, but it's crucial to verify their safety and effectiveness through rigorous evaluation. For this…
CLIFT: Analysing Natural Distribution Shift on Question Answering Models in Clinical Domain
Ankit Pal
This paper introduces a new testbed CLIFT (Clinical Shift) for the clinical domain Question-answering task. The testbed includes 7.5k high-quality question answering samples to pro…
Med-HALT: Medical Domain Hallucination Test for Large Language Models
Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu
This research paper focuses on the challenges posed by hallucinations in large language models (LLMs), particularly in the context of the medical domain. Hallucination, wherein the…
DeepParliament: A Legal domain Benchmark & Dataset for Parliament Bills Prediction
Ankit Pal
This paper introduces DeepParliament, a legal domain Benchmark Dataset that gathers bill documents and metadata and performs various bill status classification tasks. The proposed…
MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering
Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu
This paper introduces MedMCQA, a new large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. More than 194k h…
Multi-Label Text Classification using Attention-based Graph Neural Network
Ankit Pal, Muru Selvakumar, Malaikannan Sankarasubbu
In Multi-Label Text Classification (MLTC), one sample can belong to more than one class. It is observed that most MLTC tasks, there are dependencies or correlations among labels. E…