most citedTowards Modelling Coherence in Spoken Discourse

3 citations · 5 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL20211 cited

DRIFT: A Toolkit for Diachronic Analysis of Scientific Literature

Abheesht Sharma, Gunjan Chhablani, Harshit Pandey +1

In this work, we present to the NLP community, and to the wider research community as a whole, an application for the diachronic analysis of research corpora. We open source an eas…

cs.CL2021

Vyākarana: A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages

Rajaswa Patil, Jasleen Dhillon, Siddhant Mahurkar +3

While there has been significant progress towards developing NLU resources for Indic languages, syntactic evaluation has been relatively less explored. Unlike English, Indic langua…

cs.CL20203 cited

Towards Modelling Coherence in Spoken Discourse

Rajaswa Patil, Yaman Kumar Singla, Rajiv Ratn Shah +2

While there has been significant progress towards modelling coherence in written discourse, the work in modelling spoken discourse coherence has been quite limited. Unlike the cohe…

cs.CL20201 cited

BPGC at SemEval-2020 Task 11: Propaganda Detection in News Articles with Multi-Granularity Knowledge Sharing and Linguistic Features based Ensemble Learning

Rajaswa Patil, Somesh Singh, Swati Agarwal

Propaganda spreads the ideology and beliefs of like-minded people, brainwashing their audiences, and sometimes leading to violence. SemEval 2020 Task-11 aims to design automated sy…

cs.CL2020

CNRL at SemEval-2020 Task 5: Modelling Causal Reasoning in Language with Multi-Head Self-Attention Weights based Counterfactual Detection

Rajaswa Patil, Veeky Baths

In this paper, we describe an approach for modelling causal reasoning in natural language by detecting counterfactuals in text using multi-head self-attention weights. We use pre-t…

cs.CL2020

LRG at SemEval-2020 Task 7: Assessing the Ability of BERT and Derivative Models to Perform Short-Edits based Humor Grading

Siddhant Mahurkar, Rajaswa Patil

In this paper, we assess the ability of BERT and its derivative models (RoBERTa, DistilBERT, and ALBERT) for short-edits based humor grading. We test these models for humor grading…