Search Results for author:
Found 9 papers, 2 papers with code
IITkgp at FinCausal 2020, Shared Task 1: Causality Detection using Sentence Embeddings in Financial Reports
The experiments have shown BERT (Large) performed the best, giving a F1 score of 0. 958, in the task of detecting the causality of sentences in financial texts and reports.
Poirot at SemEval-2022 Task 5: Leveraging Graph Network for Misogynistic Meme Detection
In recent years, there has been an upsurge in a new form of entertainment medium called memes.
Poirot at CMCL 2022 Shared Task: Zero Shot Crosslingual Eye-Tracking Data Prediction using Multilingual Transformer Models
Eye tracking data during reading is a useful source of information to understand the cognitive processes that take place during language comprehension processes.
CoRE-CoG: Conversational Recommendation of Entities using Constrained Generation
End-to-end conversational recommendation systems (CRS) generate responses by leveraging both dialog history and a knowledge base (KB).
M-MELD: A Multilingual Multi-Party Dataset for Emotion Recognition in Conversations
Expression of emotions is a crucial part of daily human communication.
Misogynistic Meme Detection using Early Fusion Model with Graph Network
In recent years , there has been an upsurge in a new form of entertainment medium called memes.
MMER: Multimodal Multi-task Learning for Speech Emotion Recognition
In this paper, we propose MMER, a novel Multimodal Multi-task learning approach for Speech Emotion Recognition.
Ranked #2 on
Speech Emotion Recognition
on IEMOCAP
(using extra training data)
Zero Shot Crosslingual Eye-Tracking Data Prediction using Multilingual Transformer Models
Eye tracking data during reading is a useful source of information to understand the cognitive processes that take place during language comprehension processes.
IIT_kgp at FinCausal 2020, Shared Task 1: Causality Detection using Sentence Embeddings in Financial Reports
The experiments have shown BERT (Large) performed the best, giving a F1 score of 0. 958, in the task of detecting the causality of sentences in financial texts and reports.
