3 citations · 3 across the 4 of their papers we have counts for
4 papers
SPARE: Single-Pass Annotation with Reference-Guided Evaluation for Automatic Process Supervision and Reward Modelling
Md Imbesat Hassan Rizvi, Xiaodan Zhu, Iryna Gurevych
Process or step-wise supervision has played a crucial role in advancing complex multi-step reasoning capabilities of Large Language Models (LLMs). However, efficient, high-quality…
SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models
Md Imbesat Hassan Rizvi, Xiaodan Zhu, Iryna Gurevych
Spatial reasoning is a crucial component of both biological and artificial intelligence. In this work, we present a comprehensive study of the capability of current state-of-the-ar…
Identifying causal relations in tweets using deep learning: Use case on diabetes-related tweets from 2017-2021
Adrian Ahne, Vivek Khetan, Xavier Tannier +6
Objective: Leveraging machine learning methods, we aim to extract both explicit and implicit cause-effect associations in patient-reported, diabetes-related tweets and provide a to…
MIMICause: Representation and automatic extraction of causal relation types from clinical notes
Vivek Khetan, Md Imbesat Hassan Rizvi, Jessica Huber +3
Understanding causal narratives communicated in clinical notes can help make strides towards personalized healthcare. Extracted causal information from clinical notes can be combin…