no code implementations • EMNLP 2020 • Avinash Swaminathan, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah, Amanda Stent
We observed that our model achieves state-of-the-art performance in the generation of abstractive keyphrases and is comparable to the best performing extractive techniques.
no code implementations • 18 Jan 2024 • Tahiya Chowdhury, Veronica Romero, Amanda Stent
The diagnosis of autism spectrum disorder (ASD) is a complex, challenging task as it depends on the analysis of interactional behaviors by psychologists rather than the use of biochemical diagnostics.
no code implementations • 1 Aug 2021 • Yuval Pinter, Amanda Stent, Mark Dredze, Jacob Eisenstein
Commonly-used transformer language models depend on a tokenization schema which sets an unchangeable subword vocabulary prior to pre-training, destined to be applied to all downstream tasks regardless of domain shift, novel word formations, or other sources of vocabulary mismatch.
2 code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Shagun Uppal, Vivek Gupta, Avinash Swaminathan, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah, Amanda Stent
We further improve the performance by using a joint-objective for classification and textual entailment.
no code implementations • 19 Oct 2019 • Dhruva Sahrawat, Debanjan Mahata, Mayank Kulkarni, Haimin Zhang, Rakesh Gosangi, Amanda Stent, Agniv Sharma, Yaman Kumar, Rajiv Ratn Shah, Roger Zimmermann
In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where the words in the input text are represented using deep contextualized embeddings.
no code implementations • 7 Jun 2019 • Katherine A. Keith, Amanda Stent
Every fiscal quarter, companies hold earnings calls in which company executives respond to questions from analysts.
no code implementations • 10 May 2019 • Nilay Shrivastava, Astitwa Saxena, Yaman Kumar, Rajiv Ratn Shah, Debanjan Mahata, Amanda Stent
Visual speech recognition (VSR) is the task of recognizing spoken language from video input only, without any audio.
1 code implementation • 29 Jan 2019 • Yaman Kumar, Dhruva Sahrawat, Shubham Maheshwari, Debanjan Mahata, Amanda Stent, Yifang Yin, Rajiv Ratn Shah, Roger Zimmermann
To solve this problem, we present a novel approach to zero-shot learning by generating new classes using Generative Adversarial Networks (GANs), and show how the addition of unseen class samples increases the accuracy of a VSR system by a significant margin of 27% and allows it to handle speaker-independent out-of-vocabulary phrases.
no code implementations • LREC 2016 • Dragomir Radev, Amanda Stent, Joel Tetreault, Aasish Pappu, Aikaterini Iliakopoulou, Agustin Chanfreau, Paloma de Juan, Jordi Vallmitjana, Alejandro Jaimes, Rahul Jha, Bob Mankoff
The New Yorker publishes a weekly captionless cartoon.
no code implementations • CVPR 2015 • Yale Song, Jordi Vallmitjana, Amanda Stent, Alejandro Jaimes
We observe that a video title is often carefully chosen to be maximally descriptive of its main topic, and hence images related to the title can serve as a proxy for important visual concepts of the main topic.