What BERTs and GPTs know about your brand? Probing contextual language models for affect associations

no code implementations • NAACL (DeeLIO) 2021 • Vivek Srivastava, Stephen Pilli, Savita Bhat, Niranjan Pedanekar, Shirish Karande

In the era of digital marketing, both brand managers and consumers engage with a vast amount of digital marketing content.

Attribute Marketing +3

Style-based Clustering of Visual Artworks and the Play of Neural Style-Representations

no code implementations • 12 Sep 2024 • Abhishek Dangeti, Pavan Gajula, Vivek Srivastava, Vikram Jamwal

Clustering artworks based on style can have many potential real-world applications like art recommendations, style-based search and retrieval, and the study of artistic style evolution of an artist or in an artwork corpus.

Clustering Style Transfer

MMT: A Multilingual and Multi-Topic Indian Social Media Dataset

no code implementations • 2 Apr 2023 • Dwip Dalal, Vivek Srivastava, Mayank Singh

Social media plays a significant role in cross-cultural communication.

Diversity Language Identification +2

MUTANT: A Multi-sentential Code-mixed Hinglish Dataset

no code implementations • 23 Feb 2023 • Rahul Gupta, Vivek Srivastava, Mayank Singh

As a use case, we leverage multilingual articles from two different data sources and build a first-of-its-kind multi-sentential code-mixed Hinglish dataset i. e., MUTANT.

Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish Text

no code implementations • INLG (ACL) 2021 • Vivek Srivastava, Mayank Singh

In this shared task, we seek the participating teams to investigate the factors influencing the quality of the code-mixed text generation systems.

Prediction Text Generation

MIPE: A Metric Independent Pipeline for Effective Code-Mixed NLG Evaluation

no code implementations • EMNLP (Eval4NLP) 2021 • Ayush Garg, Sammed S Kagi, Vivek Srivastava, Mayank Singh

Code-mixing is a phenomenon of mixing words and phrases from two or more languages in a single utterance of speech and text.

Diversity nlg evaluation +1

HinGE: A Dataset for Generation and Evaluation of Code-Mixed Hinglish Text

no code implementations • EMNLP (Eval4NLP) 2021 • Vivek Srivastava, Mayank Singh

Text generation is a highly active area of research in the computational linguistic community.

Text Generation

Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text

no code implementations • NAACL (CALCS) 2021 • Vivek Srivastava, Mayank Singh

Code-mixing is a frequent communication style among multilingual speakers where they mix words and phrases from two different languages in the same utterance of text or speech.

Challenges and Considerations with Code-Mixed NLP for Multilingual Societies

no code implementations • 15 Jun 2021 • Vivek Srivastava, Mayank Singh

Multilingualism refers to the high degree of proficiency in two or more languages in the written and oral communication modes.

Management Multilingual NLP

IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection

no code implementations • SEMEVAL 2020 • Vivek Srivastava, Mayank Singh

Code-mixing is the phenomenon of using multiple languages in the same utterance of a text or speech.

Humor Detection intent-classification +4

PHINC: A Parallel Hinglish Social Media Code-Mixed Corpus for Machine Translation

no code implementations • EMNLP (WNUT) 2020 • Vivek Srivastava, Mayank Singh

Code-mixing is the phenomenon of using more than one language in a sentence.

Machine Translation Sentence +1