no code implementations • 19 Apr 2024 • Qinyuan Wu, Mohammad Aflah Khan, Soumi Das, Vedant Nanda, Bishwamittra Ghosh, Camila Kolling, Till Speicher, Laurent Bindschaedler, Krishna P. Gummadi, Evimaria Terzi
We propose an approach for estimating the latent knowledge embedded inside large language models (LLMs).
no code implementations • 8 Mar 2024 • Soumi Das, Shubhadip Nag, Shreyyash Sharma, Suparna Bhattacharya, Sourangshu Bhattacharya
In this work, we propose a controllable framework for data-centric trustworthy AI (DCTAI)- VTruST, that allows users to control the trade-offs between the different trustworthiness metrics of the constructed training datasets.
no code implementations • 3 May 2023 • Kiran Purohit, Soumi Das, Sourangshu Bhattacharya, Santu Rana
We also show that LearnDefend is robust to size and noise in the marking of clean examples in the defense dataset.
no code implementations • 14 Mar 2022 • Soumi Das, Manasvi Sagarkar, Suparna Bhattacharya, Sourangshu Bhattacharya
Another key contribution is the study of data valuation in the domain adaptation setting, where a data value estimator obtained using checkpoints from training trajectory in the source domain training dataset is used for data valuation in a target domain training dataset.
1 code implementation • 28 Apr 2021 • Soumi Das, Arshdeep Singh, Saptarshi Chatterjee, Suparna Bhattacharya, Sourangshu Bhattacharya
In this paper, we study the problem of selecting high-value subsets of training data.
no code implementations • 24 Mar 2021 • Soumi Das, Harikrishna Patibandla, Suparna Bhattacharya, Kshounis Bera, Niloy Ganguly, Sourangshu Bhattacharya
We design a novel convex optimization-based multi-criteria online subset selection algorithm that uses a thresholded concave function of selection variables.
no code implementations • ICCV 2021 • Soumi Das, Harikrishna Patibandla, Suparna Bhattacharya, Kshounis Bera, Niloy Ganguly, Sourangshu Bhattacharya
Training vision-based Autonomous driving models is a challenging problem with enormous practical implications.
no code implementations • 6 Nov 2019 • Soumi Das, Rajath Nandan Kalava, Kolli Kiran Kumar, Akhil Kandregula, Kalpam Suhaas, Sourangshu Bhattacharya, Niloy Ganguly
Travel time estimation is a fundamental problem in transportation science with extensive literature.