activity
20202025
most citedAn Interpretable Deep Learning System for Automatically Scoring Request for Proposals

8 citations · 19 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CL2025

LeMAJ (Legal LLM-as-a-Judge): Bridging Legal Reasoning and LLM Evaluation

Joseph Enguehard, Morgane Van Ermengem, Kate Atkinson +8

Evaluating large language model (LLM) outputs in the legal domain presents unique challenges due to the complex and nuanced nature of legal analysis. Current evaluation approaches…

cs.CL2024

From Prejudice to Parity: A New Approach to Debiasing Large Language Model Word Embeddings

Aishik Rakshit, Smriti Singh, Shuvam Keshari +3

Embeddings play a pivotal role in the efficacy of Large Language Models. They are the bedrock on which these models grasp contextual relationships and foster a more nuanced underst…

cs.CL2023★ 1 cited

Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges

Vinay Samuel, Houda Aynaou, Arijit Ghosh Chowdhury +2

Large Language Models (LLMs) have demonstrated impressive zero shot performance on a wide range of NLP tasks, demonstrating the ability to reason and apply commonsense. A relevant…

cs.CL2023★ 2 cited

Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answering

Arijit Ghosh Chowdhury, Aman Chadha

Robustness in Natural Language Processing continues to be a pertinent issue, where state of the art models under-perform under naturally shifted distributions. In the context of Qu…

cs.CL2020★ 8 cited

An Interpretable Deep Learning System for Automatically Scoring Request for Proposals

Subhadip Maji, Anudeep Srivatsav Appe, Raghav Bali +3

The Managed Care system within Medicaid (US Healthcare) uses Request For Proposals (RFP) to award contracts for various healthcare and related services. RFP responses are very deta…

cs.CL2020★ 1 cited

Exclusion and Inclusion -- A model agnostic approach to feature importance in DNNs

Subhadip Maji, Arijit Ghosh Chowdhury, Raghav Bali +1

Deep Neural Networks in NLP have enabled systems to learn complex non-linear relationships. One of the major bottlenecks towards being able to use DNNs for real world applications…