Search Results for author: Gaurav Verma

Found 14 papers, 2 papers with code

Robustness of Fusion-based Multimodal Classifiers to Cross-Modal Content Dilutions

no code implementations4 Nov 2022 Gaurav Verma, Vishwa Vinay, Ryan A. Rossi, Srijan Kumar

Our work aims to highlight and encourage further research on the robustness of deep multimodal models to realistic variations, especially in human-facing societal applications.

The Impact of COVID-19 Pandemic on LGBTQ Online Communities

no code implementations19 May 2022 Yunhao Yuan, Gaurav Verma, Barbara Keller, Talayeh Aledavood

In this paper, we identify a group of Twitter users who self-disclose to belong to the LGBTQ community.

Overcoming Language Disparity in Online Content Classification with Multimodal Learning

1 code implementation19 May 2022 Gaurav Verma, Rohit Mujumdar, Zijie J. Wang, Munmun De Choudhury, Srijan Kumar

Advances in Natural Language Processing (NLP) have revolutionized the way researchers and practitioners address crucial societal problems.

Emotion Recognition

Characterizing, Detecting, and Predicting Online Ban Evasion

1 code implementation10 Feb 2022 Manoj Niverthi, Gaurav Verma, Srijan Kumar

We find that evasion child accounts demonstrate similarities with respect to their banned parent accounts on several behavioral axes - from similarity in usernames and edited pages to similarity in content added to the platform and its psycholinguistic attributes.

BeautifAI -- A Personalised Occasion-oriented Makeup Recommendation System

no code implementations13 Sep 2021 Kshitij Gulati, Gaurav Verma, Mukesh Mohania, Ashish Kundu

The proposed work's novel contributions, including the incorporation of occasion context, region-wise makeup recommendation, real-time makeup previews and continuous makeup feedback, set our system apart from the current work in makeup recommendation.

DRAG: Director-Generator Language Modelling Framework for Non-Parallel Author Stylized Rewriting

no code implementations EACL 2021 Hrituraj Singh, Gaurav Verma, Aparna Garimella, Balaji Vasan Srinivasan

In this paper, we propose a Director-Generator framework to rewrite content in the target author's style, specifically focusing on certain target attributes.

Denoising Language Modelling

Incorporating Stylistic Lexical Preferences in Generative Language Models

no code implementations Findings of the Association for Computational Linguistics 2020 Hrituraj Singh, Gaurav Verma, Balaji Vasan Srinivasan

While recent advances in language modeling have resulted in powerful generation models, their generation style remains implicitly dependent on the training data and can not emulate a specific target style.

Language Modelling reinforcement Learning

"To Target or Not to Target": Identification and Analysis of Abusive Text Using Ensemble of Classifiers

no code implementations5 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.

BIG-bench Machine Learning Ensemble Learning

Using Image Captions and Multitask Learning for Recommending Query Reformulations

no code implementations2 Mar 2020 Gaurav Verma, Vishwa Vinay, Sahil Bansal, Shashank Oberoi, Makkunda Sharma, Prakhar Gupta

Interactive search sessions often contain multiple queries, where the user submits a reformulated version of the previous query in response to the original results.

Image Captioning Image Retrieval

Adapting Language Models for Non-Parallel Author-Stylized Rewriting

no code implementations22 Sep 2019 Bakhtiyar Syed, Gaurav Verma, Balaji Vasan Srinivasan, Anandhavelu Natarajan, Vasudeva Varma

Given the recent progress in language modeling using Transformer-based neural models and an active interest in generating stylized text, we present an approach to leverage the generalization capabilities of a language model to rewrite an input text in a target author's style.

Denoising Language Modelling

A Lexical, Syntactic, and Semantic Perspective for Understanding Style in Text

no code implementations18 Sep 2019 Gaurav Verma, Balaji Vasan Srinivasan

With a growing interest in modeling inherent subjectivity in natural language, we present a linguistically-motivated process to understand and analyze the writing style of individuals from three perspectives: lexical, syntactic, and semantic.

Learning Affective Correspondence between Music and Image

no code implementations30 Mar 2019 Gaurav Verma, Eeshan Gunesh Dhekane, Tanaya Guha

We introduce the problem of learning affective correspondence between audio (music) and visual data (images).

Emotion Recognition

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