38 citations · 59 across the 4 of their papers we have counts for
6 papers · 1 filter
Calibrating Sequence likelihood Improves Conditional Language Generation
Yao Zhao, Misha Khalman, Rishabh Joshi +3
Conditional language models are predominantly trained with maximum likelihood estimation (MLE), giving probability mass to sparsely observed target sequences. While MLE trained mod…
DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues
Rishabh Joshi, Vidhisha Balachandran, Shikhar Vashishth +2
To successfully negotiate a deal, it is not enough to communicate fluently: pragmatic planning of persuasive negotiation strategies is essential. While modern dialogue agents excel…
RESPER: Computationally Modelling Resisting Strategies in Persuasive Conversations
Ritam Dutt, Sayan Sinha, Rishabh Joshi +5
Modelling persuasion strategies as predictors of task outcome has several real-world applications and has received considerable attention from the computational linguistics communi…
Keeping Up Appearances: Computational Modeling of Face Acts in Persuasion Oriented Discussions
Ritam Dutt, Rishabh Joshi, Carolyn Penstein Rose
The notion of face refers to the public self-image of an individual that emerges both from the individual's own actions as well as from the interaction with others. Modeling face a…
LTIatCMU at SemEval-2020 Task 11: Incorporating Multi-Level Features for Multi-Granular Propaganda Span Identification
Sopan Khosla, Rishabh Joshi, Ritam Dutt +2
In this paper we describe our submission for the task of Propaganda Span Identification in news articles. We introduce a BERT-BiLSTM based span-level propaganda classification mode…
RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information
Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga +2
Distantly-supervised Relation Extraction (RE) methods train an extractor by automatically aligning relation instances in a Knowledge Base (KB) with unstructured text. In addition t…