Saptarshi Ghosh

CAVES: A Dataset to facilitate Explainable Classification and Summarization of Concerns towards COVID Vaccines

Apr 28, 2022
Soham Poddar, Azlaan Mustafa Samad, Rajdeep Mukherjee, Niloy Ganguly, Saptarshi Ghosh

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* Accepted to appear at SIGIR'22 (Resource Track)

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FaiRIR: Mitigating Exposure Bias from Related Item Recommendations in Two-Sided Platforms

Apr 01, 2022
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi

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* This work has been accepted as a regular paper in IEEE Transactions on Computational Social Systems 2022 (IEEE TCSS'22)

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Alexa, in you, I trust! Fairness and Interpretability Issues in E-commerce Search through Smart Speakers

Feb 09, 2022
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi

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* This work has been accepted at The Web Conference 2022 (WWW'22)

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LeSICiN: A Heterogeneous Graph-based Approach for Automatic Legal Statute Identification from Indian Legal Documents

Dec 29, 2021
Shounak Paul, Pawan Goyal, Saptarshi Ghosh

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* This paper has been accepted at the Main Track of the AAAI Conference on Artificial Intelligence (AAAI) 2022. Dataset and codes are available at https://github.com/Law-AI/LeSICiN

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Incorporating Domain Knowledge for Extractive Summarization of Legal Case Documents

Jun 30, 2021
Paheli Bhattacharya, Soham Poddar, Koustav Rudra, Kripabandhu Ghosh, Saptarshi Ghosh

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* Accepted at the 18th International Conference on Artificial Intelligence and Law (ICAIL) 2021

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Fairness for Whom? Understanding the Reader's Perception of Fairness in Text Summarization

Feb 02, 2021
Anurag Shandilya, Abhisek Dash, Abhijnan Chakraborty, Kripabandhu Ghosh, Saptarshi Ghosh

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* This work has been accepted at International Workshop on Fair and Interpretable Learning Algorithms 2020 (FILA 2020), which was held in conjunction with IEEE BigData 2020

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When the Umpire is also a Player: Bias in Private Label Product Recommendations on E-commerce Marketplaces

Feb 02, 2021
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi

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* This work has been accepted for presentation at the ACM Conference on Fairness, Accountability, and Transparency 2021 (ACM FAccT 2021)

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An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance Detection

Jan 09, 2021
Anurag Roy, Shalmoli Ghosh, Kripabandhu Ghosh, Saptarshi Ghosh

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* Will be appearing in the ACM Journal of Data and Information Quality. Implementation available at https://github.com/ranarag/UnsupClean

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