3 citations · 5 across the 8 of their papers we have counts for
8 papers · 1 filter
Probing Semantic Grounding in Language Models of Code with Representational Similarity Analysis
Shounak Naik, Rajaswa Patil, Swati Agarwal +1
Representational Similarity Analysis is a method from cognitive neuroscience, which helps in comparing representations from two different sources of data. In this paper, we propose…
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…
Towards Using Diachronic Distributed Word Representations as Models of Lexical Development
Arijit Gupta, Rajaswa Patil, Veeky Baths
Recent work has shown that distributed word representations can encode abstract information from child-directed speech. In this paper, we use diachronic distributed word representa…
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…
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…
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…
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…
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…