activity
20192022
most citedLearn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

215 citations · 259 across the 20 of their papers we have counts for

collaborators

22 papers

cs.CL2022215 cited

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

Pan Lu, Swaroop Mishra, Tony Xia +6

When answering a question, humans utilize the information available across different modalities to synthesize a consistent and complete chain of thought (CoT). This process is norm…

cs.CL20221 cited

Pretrained Transformers Do not Always Improve Robustness

Swaroop Mishra, Bhavdeep Singh Sachdeva, Chitta Baral

Pretrained Transformers (PT) have been shown to improve Out of Distribution (OOD) robustness than traditional models such as Bag of Words (BOW), LSTMs, Convolutional Neural Network…

cs.CL20221 cited

Hardness of Samples Need to be Quantified for a Reliable Evaluation System: Exploring Potential Opportunities with a New Task

Swaroop Mishra, Anjana Arunkumar, Chris Bryan +1

Evaluation of models on benchmarks is unreliable without knowing the degree of sample hardness; this subsequently overestimates the capability of AI systems and limits their adopti…

cs.CL20221 cited

A Survey of Parameters Associated with the Quality of Benchmarks in NLP

Swaroop Mishra, Anjana Arunkumar, Chris Bryan +1

Several benchmarks have been built with heavy investment in resources to track our progress in NLP. Thousands of papers published in response to those benchmarks have competed to t…

cs.CL2022

Investigating the Failure Modes of the AUC metric and Exploring Alternatives for Evaluating Systems in Safety Critical Applications

Swaroop Mishra, Anjana Arunkumar, Chitta Baral

With the increasing importance of safety requirements associated with the use of black box models, evaluation of selective answering capability of models has been critical. Area un…

cs.LG2022

Let the Model Decide its Curriculum for Multitask Learning

Neeraj Varshney, Swaroop Mishra, Chitta Baral

Curriculum learning strategies in prior multi-task learning approaches arrange datasets in a difficulty hierarchy either based on human perception or by exhaustively searching the…