no code implementations • 30 Mar 2024 • Vivek Khetan
This position paper proposes a systematic approach towards developing a framework to help select the most effective embedding models for natural language processing (NLP) tasks, addressing the challenge posed by the proliferation of both proprietary and open-source encoder models.
no code implementations • 25 Oct 2023 • Devleena Das, Vivek Khetan
Recent advances have led to the availability of many pre-trained language models (PLMs); however, a question that remains is how much data is truly needed to fine-tune PLMs for downstream tasks?
no code implementations • 12 Oct 2022 • Somin Wadhwa, Vivek Khetan, Silvio Amir, Byron Wallace
Using this corpus, we introduce the task of retrieving trustworthy evidence relevant to a given claim made on social media.
1 code implementation • 9 Oct 2022 • Steven Y. Feng, Vivek Khetan, Bogdan Sacaleanu, Anatole Gershman, Eduard Hovy
We motivate and introduce CHARD: Clinical Health-Aware Reasoning across Dimensions, to investigate the capability of text generation models to act as implicit clinical knowledge bases and generate free-flow textual explanations about various health-related conditions across several dimensions.
1 code implementation • 1 Nov 2021 • Adrian Ahne, Vivek Khetan, Xavier Tannier, Md Imbessat Hassan Rizvi, Thomas Czernichow, Francisco Orchard, Charline Bour, Andrew Fano, Guy Fagherazzi
A cause-effect-tweet dataset was manually labeled and used to train 1) a fine-tuned Bertweet model to detect causal sentences containing a causal association 2) a CRF model with BERT based features to extract possible cause-effect associations.
no code implementations • 31 Oct 2021 • Dheeraj Rajagopal, Vivek Khetan, Bogdan Sacaleanu, Anatole Gershman, Andrew Fano, Eduard Hovy
To enable better controllability, we propose to study the commonsense reasoning as a template filling task (TemplateCSR) -- where the language models fills reasoning templates with the given constraints as control factors.
no code implementations • Findings (ACL) 2022 • Vivek Khetan, Md Imbesat Hassan Rizvi, Jessica Huber, Paige Bartusiak, Bogdan Sacaleanu, Andrew Fano
This will enhance healthcare providers' ability to identify aspects of a patient's story communicated in the clinical notes and help make more informed decisions.
no code implementations • 18 Apr 2021 • Vivek Khetan, Annervaz K M, Erin Wetherley, Elena Eneva, Shubhashis Sengupta, Andrew E. Fano
The growing quantity and complexity of data pose challenges for humans to consume information and respond in a timely manner.
no code implementations • 10 Dec 2020 • Vivek Khetan, Roshni Ramnani, Mayuresh Anand, Shubhashis Sengupta, Andrew E. Fano
Therefore, as expected these methods are more geared towards handling explicit causal relationships leading to limited coverage for implicit relationships and are hard to generalize.
no code implementations • 18 Nov 2016 • Ye Zhang, Md Mustafizur Rahman, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek Khetan, Tyler McDonnell, An Thanh Nguyen, Dan Xu, Byron C. Wallace, Matthew Lease
A recent "third wave" of Neural Network (NN) approaches now delivers state-of-the-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing.