Chitta Baral

Declarative Question Answering over Knowledge Bases Containing Natural Language Text with Answer Set Programming

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

While in recent years machine learning (ML) based approaches have been the popular approach in developing endto-end question answering systems, such systems often struggle when additional knowledge is needed to correctly answer the questions. Proposed …

ILDAE: Instance-Level Difficulty Analysis of Evaluation Data

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Knowledge of difficulty level of questions helps a teacher in several ways, such as estimating students' potential quickly by asking carefully selected questions and improving quality of examination by modifying trivial and hard questions. Can …

A Simple Approach to Jointly Rank Passages and Select Relevant Sentences in the OBQA Context

2021 · arXiv (Cornell University)

In the open book question answering (OBQA) task, selecting the relevant passages and sentences from distracting information is crucial to reason the answer to a question. HotpotQA dataset is designed to teach and evaluate systems …

TarGEN: Targeted Data Generation with Large Language Models

2023 · arXiv (Cornell University)

The rapid advancement of large language models (LLMs) has sparked interest in data synthesis techniques, aiming to generate diverse and high-quality synthetic datasets. However, these synthetic datasets often suffer from a lack of diversity and …

LongBoX: Evaluating Transformers on Long-Sequence Clinical Tasks

2023 · arXiv (Cornell University)

Many large language models (LLMs) for medicine have largely been evaluated on short texts, and their ability to handle longer sequences such as a complete electronic health record (EHR) has not been systematically explored. Assessing …