1 code implementation • LREC 2022 • Sayontan Ghosh, Amanpreet Singh, Alex Merenstein, Wei Su, Scott A. Smolka, Erez Zadok, Niranjan Balasubramanian
Evaluations show that even when using a state-of-the-art language model, there is significant room for improvement, with the best models achieving an F1 score of only 60. 5 and 33. 3 in the named-entity-recognition and dependency-link-prediction sub-tasks, respectively.
1 code implementation • 5 Dec 2022 • Sai Vallurupalli, Sayontan Ghosh, Katrin Erk, Niranjan Balasubramanian, Francis Ferraro
Knowledge about outcomes is critical for complex event understanding but is hard to acquire.
1 code implementation • 12 Oct 2022 • Sayontan Ghosh, Tanvi Aggarwal, Minh Hoai, Niranjan Balasubramanian
Anticipating future actions in a video is useful for many autonomous and assistive technologies.
no code implementations • 31 Jul 2022 • Sayontan Ghosh, Mahnaz Koupaee, Isabella Chen, Francis Ferraro, Nathanael Chambers, Niranjan Balasubramanian
This dataset contains inferable participant states; a counterfactual perturbation to each state; and the changes to the story that would be necessary if the counterfactual were true.