Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models

1 code implementation • 20 Nov 2022 • Karan Uppal, Jaeah Kim, Shashank Singh

Eye-tracking has potential to provide rich behavioral data about human cognition in ecologically valid environments.

valid

Reproducibility of "FDA: Fourier Domain Adaptation forSemantic Segmentation

1 code implementation • 30 Apr 2021 • Arnesh Kumar Issar, Kirtan Mali, Aryan Mehta, Karan Uppal, Saurabh Mishra, Debashish Chakravarty

The following paper is a reproducibility report for "FDA: Fourier Domain Adaptation for Semantic Segmentation" published in the CVPR 2020 as part of the ML Reproducibility Challenge 2020.

Semantic Segmentation Unsupervised Domain Adaptation

Suggestion Mining from Online Reviews using ULMFiT

1 code implementation • 19 Apr 2019 • Sarthak Anand, Debanjan Mahata, Kartik Aggarwal, Laiba Mehnaz, Simra Shahid, Haimin Zhang, Yaman Kumar, Rajiv Ratn Shah, Karan Uppal

In this paper we present our approach and the system description for Sub Task A of SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums.

General Classification Language Modelling +4

Identifying Offensive Posts and Targeted Offense from Twitter

no code implementations • 19 Apr 2019 • Haimin Zhang, Debanjan Mahata, Simra Shahid, Laiba Mehnaz, Sarthak Anand, Yaman Singla, Rajiv Ratn Shah, Karan Uppal

In this paper we present our approach and the system description for Sub-task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Media.

RIDDL at SemEval-2018 Task 1: Rage Intensity Detection with Deep Learning

no code implementations • SEMEVAL 2018 • Venkatesh Elango, Karan Uppal

We present our methods and results for affect analysis in Twitter developed as a part of SemEval-2018 Task 1, where the sub-tasks involve predicting the intensity of emotion, the intensity of sentiment, and valence for tweets.

Decoder Sentiment Analysis