no code implementations • 3 May 2024 • Tanya Chowdhury, Yair Zick, James Allan
Next, we introduce Rank-SHAP, a feature attribution algorithm for the general ranking task, which is an extension to classical Shapley values.
no code implementations • 29 Nov 2023 • Abhishek Madaan, Tanya Chowdhury, Neha Rana, James Allan, Tanmoy Chakraborty
As a result, we propose a measure to quantify the relative complexity of a blackbox classifier.
no code implementations • 24 Dec 2022 • Tanya Chowdhury, Razieh Rahimi, James Allan
In this work, we extend LIME to propose Rank-LIME, a model-agnostic, local, post-hoc linear feature attribution method for the task of learning to rank that generates explanations for ranked lists.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Alvin Dey, Tanya Chowdhury, Yash Kumar Atri, Tanmoy Chakraborty
Owing to no standard definition of the task, we encounter a plethora of datasets with varying levels of overlap and conflict between participating documents.
no code implementations • 21 Apr 2020 • Tanya Chowdhury, Sachin Kumar, Tanmoy Chakraborty
This problem is exacerbated in multi-document summarization tasks such as summarizing the popular opinion in threads present in community question answering (CQA) websites such as Yahoo!
Abstractive Text Summarization Community Question Answering +4