no code implementations • EMNLP 2021 • Sharmila Reddy Nangi, Atharv Tyagi, Jay Mundra, Sagnik Mukherjee, Raj Snehal, Niyati Chhaya, Aparna Garimella
Recent efforts to develop deep learning models for text generation tasks such as extractive and abstractive summarization have resulted in state-of-the-art performances on various datasets.
no code implementations • Findings (ACL) 2022 • Navita Goyal, Roodram Paneri, Ayush Agarwal, Udit Kalani, Abhilasha Sancheti, Niyati Chhaya
We leverage causal inference techniques to identify causally significant aspects of a text that lead to the target metric and then explicitly guide generative models towards these by a feedback mechanism.
no code implementations • LREC 2022 • Sravani Boinepelli, Tathagata Raha, Harika Abburi, Pulkit Parikh, Niyati Chhaya, Vasudeva Varma
We leverage accounts of depression taken from this dataset to infuse domain-specific elements into our framework.
no code implementations • 1 Jun 2023 • Abisek Rajakumar Kalarani, Pushpak Bhattacharyya, Niyati Chhaya, Sumit Shekhar
We exploit context by pretraining our model with datasets of three tasks: news image captioning where the news article is the context, contextual visual entailment, and keyword extraction from the context.
no code implementations • ACL 2021 • Sharmila Reddy Nangi, Niyati Chhaya, Sopan Khosla, Nikhil Kaushik, Harshit Nyati
Disentanglement of latent representations into content and style spaces has been a commonly employed method for unsupervised text style transfer.
no code implementations • NAACL 2021 • Kokil Jaidka, Andrea Ceolin, Iknoor Singh, Niyati Chhaya, Lyle Ungar
We show how the data supports the classic understanding of style matching, where positive emotion and the use of first-person pronouns predict a positive emotional change in a Wikipedia contributor.
no code implementations • EACL 2021 • Bhanu Prakash Reddy Guda, Aparna Garimella, Niyati Chhaya
Affect preferences vary with user demographics, and tapping into demographic information provides important cues about the users' language preferences.
1 code implementation • 22 Dec 2020 • Soujanya Poria, Navonil Majumder, Devamanyu Hazarika, Deepanway Ghosal, Rishabh Bhardwaj, Samson Yu Bai Jian, Pengfei Hong, Romila Ghosh, Abhinaba Roy, Niyati Chhaya, Alexander Gelbukh, Rada Mihalcea
We address the problem of recognizing emotion cause in conversations, define two novel sub-tasks of this problem, and provide a corresponding dialogue-level dataset, along with strong Transformer-based baselines.
Ranked #1 on Recognizing Emotion Cause in Conversations on RECCON
1 code implementation • COLING 2020 • Harika Abburi, Pulkit Parikh, Niyati Chhaya, Vasudeva Varma
Sexism, a form of oppression based on one{'}s sex, manifests itself in numerous ways and causes enormous suffering.
1 code implementation • 19 Nov 2020 • Soumyadeep Roy, Shamik Sural, Niyati Chhaya, Anandhavelu Natarajan, Niloy Ganguly
A consumer-dependent (business-to-consumer) organization tends to present itself as possessing a set of human qualities, which is termed as the brand personality of the company.
no code implementations • 24 Oct 2020 • Navita Goyal, Roodram Paneri, Ayush Agarwal, Udit Kalani, Abhilasha Sancheti, Niyati Chhaya
We leverage causal inference techniques to identify causally significant aspects of a text that lead to the target metric and then explicitly guide generative models towards these by a feedback mechanism.
no code implementations • 5 Jun 2020 • Gaurav Verma, Niyati Chhaya, Vishwa Vinay
With rising concern around abusive and hateful behavior on social media platforms, we present an ensemble learning method to identify and analyze the linguistic properties of such content.
no code implementations • CONLL 2019 • Kushal Chawla, Balaji Vasan Srinivasan, Niyati Chhaya
Abstractive text summarization aims at generating human-like summaries by understanding and paraphrasing the given input content.
1 code implementation • IJCNLP 2019 • Pulkit Parikh, Harika Abburi, Pinkesh Badjatiya, Radhika Krishnan, Niyati Chhaya, Manish Gupta, Vasudeva Varma
Sexism, an injustice that subjects women and girls to enormous suffering, manifests in blatant as well as subtle ways.
no code implementations • 4 Sep 2019 • Tommaso Teofili, Niyati Chhaya
Distributed representations of words have shown to be useful to improve the effectiveness of IR systems in many sub-tasks like query expansion, retrieval and ranking.
2 code implementations • IJCNLP 2019 • Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, Alexander Gelbukh
Emotion recognition in conversation (ERC) has received much attention, lately, from researchers due to its potential widespread applications in diverse areas, such as health-care, education, and human resources.
Ranked #1 on Emotion Recognition in Conversation on SEMAINE
no code implementations • 13 Aug 2019 • Navonil Majumder, Soujanya Poria, Gangeshwar Krishnamurthy, Niyati Chhaya, Rada Mihalcea, Alexander Gelbukh
Multimodal fusion is considered a key step in multimodal tasks such as sentiment analysis, emotion detection, question answering, and others.
no code implementations • 23 Jan 2019 • Navonil Majumder, Soujanya Poria, Haiyun Peng, Niyati Chhaya, Erik Cambria, Alexander Gelbukh
We argue that knowledge in sarcasm detection can also be beneficial to sentiment classification and vice versa.
no code implementations • ACL 2018 • Kokil Jaidka, Niyati Chhaya, Lyle Ungar
It asks the question: given that the social media platform and its users remain the same, how is language changing over time?
no code implementations • WS 2018 • Niyati Chhaya, Kushal Chawla, Tanya Goyal, Ch, Projjal a, Jaya Singh
We present a novel approach to model human frustration in text.
no code implementations • COLING 2018 • Sopan Khosla, Niyati Chhaya, Kushal Chawla
Human communication includes information, opinions, and reactions.
no code implementations • ICLR 2018 • Kushal Chawla, Sopan Khosla, Niyati Chhaya, Kokil Jaidka
Our work addresses the question: can affect lexica improve the word representations learnt from a corpus?