no code implementations • 21 Feb 2024 • Ashutosh Sathe, Prachi Jain, Sunayana Sitaram
In this study, we propose a unified framework for systematically evaluating gender, race, and age biases in VLMs with respect to professions.
no code implementations • 12 Feb 2024 • Prachi Jain, Ashutosh Sathe, Varun Gumma, Kabir Ahuja, Sunayana Sitaram
In this work, we aim to modularly debias a pretrained language model across multiple dimensions.
no code implementations • 13 Nov 2023 • Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, Ishaan Watts, Ashutosh Sathe, Millicent Ochieng, Rishav Hada, Prachi Jain, Maxamed Axmed, Kalika Bali, Sunayana Sitaram
We also perform a study on data contamination and find that several models are likely to be contaminated with multilingual evaluation benchmarks, necessitating approaches to detect and handle contamination while assessing the multilingual performance of LLMs.
1 code implementation • 22 Mar 2023 • Kabir Ahuja, Harshita Diddee, Rishav Hada, Millicent Ochieng, Krithika Ramesh, Prachi Jain, Akshay Nambi, Tanuja Ganu, Sameer Segal, Maxamed Axmed, Kalika Bali, Sunayana Sitaram
Most studies on generative LLMs have been restricted to English and it is unclear how capable these models are at understanding and generating text in other languages.
no code implementations • AKBC 2021 • Harkanwar Singh, Prachi Jain, Mausam, Soumen Chakrabarti
Almost all of existing KGC research is applicable to only one KG at a time, and in one language only.
Ranked #2 on
Knowledge Graph Completion
on DBP-5L (Greek)
1 code implementation • 2 May 2020 • Prachi Jain, Sushant Rathi, Mausam, Soumen Chakrabarti
Most existing methods train with a small number of negative samples for each positive instance in these datasets to save computational costs.
1 code implementation • EMNLP 2020 • Prachi Jain, Sushant Rathi, Mausam, Soumen Chakrabarti
Temporal knowledge bases associate relational (s, r, o) triples with a set of times (or a single time instant) when the relation is valid.
Ranked #1 on
Link Prediction
on Wikidata12k
1 code implementation • ACL 2018 • Prachi Jain, Pankaj Kumar, {Mausam}, Soumen Chakrabarti
State-of-the-art knowledge base completion (KBC) models predict a score for every known or unknown fact via a latent factorization over entity and relation embeddings.
2 code implementations • 2 Jun 2017 • Prachi Jain, Shikhar Murty, Mausam, Soumen Chakrabarti
If not, what characteristics of a dataset determine the performance of MF and TF models?