Tanmoy Chakraborty
Biographic Data
| ID | 3925566 |
|---|---|
| NAME | Tanmoy Chakraborty |
| GIVEN NAMES | Tanmoy |
| FAMILY NAME | Chakraborty |
| SIGNATURE | CHAKRABORTY T |
| AFFILIATIONS | Indian Institute of Technology Delhi |
| ORCID | 0000-0002-3374-8125 |
| VERIFIED | Yes |
| TOTAL WORKS | 13 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 13 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Benchmarking Large Language Models Against Psychiatry Residents Using Traditional Institutional Assessments
Background: Artificial intelligence (AI) models demonstrate remarkable capabilities in healthcare applications, yet their performance compared to medical trainees in psychiatric education remains unexplored. This study evaluated the comparative performance of large language models (LLMs) against first-year psychiatry residents in standardized assessments at a premier Indian medical educational institute. Methods: For this study, the already-score…
AI Across Borders
This study investigates students’ perceptions of Generative Artificial Intelligence (GenAI), with a focus on Higher Education institutions in Northern Ireland and India. We collect quantitative Likert ratings and qualitative comments from 1211 students on their awareness and perceptions of AI and investigate variations in attitudes toward AI across institutions and subject areas, as well as interactions between these variables with demographic va…
Social, economic, and demographic factors drive the emergence of Hinglish code-mixing on social media
The advent of globalization and adaptation to multiple cultures has emanated a fusion of Hindi and English, casually known as Hinglish . The phenomenon of mixing multiple languages (such as Hindi and English) within a single utterance is often called code-mixing . Lately, code-mixed Hinglish has emerged as a dominant conversational language for Hindi-speaking citizens both online (on social media platforms) and offline. Although previous studies …
A Comprehensive Understanding of Code-Mixed Language Semantics Using Hierarchical Transformer
Being a popular mode of text-based communication in multilingual communities, code mixing in online social media has become an important subject to study. Learning the semantics and morphology of code-mixed language remains a key challenge due to the scarcity of data, the unavailability of robust, and language-invariant representation learning techniques. Any morphologically rich language can benefit from character, subword, and word-level embedd…
HostileNet
In this article, we deal with the task of hostile post detection in Hindi. The objective is to predict whether a social media post is hostile or not. Furthermore, if the post is hostile, we identify one or more fine-grained hostile dimensions out of the following four—fake, hate, offensive, and defamation. We propose HostileNet , a novel deep-learning framework that leverages HindiBERT-based contextual representations and hand-crafted features li…
Model-Agnostic Meta-Learning for Multilingual Hate Speech Detection
Hate speech in social media is a growing phenomenon, and detecting such toxic content has recently gained significant traction in the research community. Existing studies have explored fine-tuning language models (LMs) to perform hate speech detection, and these solutions have yielded significant performance. However, most of these studies are limited to detecting hate speech only in English, neglecting the bulk of hateful content that is generat…
Data Science for Fake News
Hide and Seek
Community affiliation of a node plays an important role in determining its contextual position in the network, which may raise privacy concerns when a sensitive node wants to hide its identity in a network. Oftentimes, a target community seeks to protect itself from adversaries so that its constituent members remain hidden inside the network. The current study focuses on hiding such sensitive communities so that the community affiliation of the t…
Syntactically Coherent Text Augmentation for Sequence Classification
In this article, we address the problem of data scarcity for the sequence classification tasks. We propose AugmentGAN, a simple-yet-effective generative adversarial network-based text augmentation model, which ensures syntactic coherency in the newly generated samples. Given an input with a label, AugmentGAN aims to generate a semantically similar sequence that follows the syntactic structure of the original sample. Exhaustive task-based evaluati…
Detecting and Characterizing Extremist Reviewer Groups in Online Product Reviews
Online marketplaces often witness opinion spam in the form of reviews. People are often hired to target specific brands for promoting or impeding them by writing highly positive or negative reviews. This often is done collectively in groups. Although some previous studies attempted to identify and analyze such opinion spam groups, little has been explored to spot those groups who target a brand as a whole, instead of just products. In this articl…
A scale of atomic electronegativity in terms of atomic nucleophilicity index
An author is known by the context she keeps
Citation interactions among computer science fields
Citation interactions among computer science fields
An author is known by the context she keeps
Detecting and Characterizing Extremist Reviewer Groups in Online Product Reviews
Online marketplaces often witness opinion spam in the form of reviews. People are often hired to target specific brands for promoting or impeding them by writing highly positive or negative reviews. This often is done collectively in groups. Although some previous studies attempted to identify and analyze such opinion spam groups, little has been explored to spot those groups who target a brand as a whole, instead of just products. In this articl…
A scale of atomic electronegativity in terms of atomic nucleophilicity index
Data Science for Fake News
Hide and Seek
Community affiliation of a node plays an important role in determining its contextual position in the network, which may raise privacy concerns when a sensitive node wants to hide its identity in a network. Oftentimes, a target community seeks to protect itself from adversaries so that its constituent members remain hidden inside the network. The current study focuses on hiding such sensitive communities so that the community affiliation of the t…
Syntactically Coherent Text Augmentation for Sequence Classification
In this article, we address the problem of data scarcity for the sequence classification tasks. We propose AugmentGAN, a simple-yet-effective generative adversarial network-based text augmentation model, which ensures syntactic coherency in the newly generated samples. Given an input with a label, AugmentGAN aims to generate a semantically similar sequence that follows the syntactic structure of the original sample. Exhaustive task-based evaluati…
Social, economic, and demographic factors drive the emergence of Hinglish code-mixing on social media
The advent of globalization and adaptation to multiple cultures has emanated a fusion of Hindi and English, casually known as Hinglish . The phenomenon of mixing multiple languages (such as Hindi and English) within a single utterance is often called code-mixing . Lately, code-mixed Hinglish has emerged as a dominant conversational language for Hindi-speaking citizens both online (on social media platforms) and offline. Although previous studies …
A Comprehensive Understanding of Code-Mixed Language Semantics Using Hierarchical Transformer
Being a popular mode of text-based communication in multilingual communities, code mixing in online social media has become an important subject to study. Learning the semantics and morphology of code-mixed language remains a key challenge due to the scarcity of data, the unavailability of robust, and language-invariant representation learning techniques. Any morphologically rich language can benefit from character, subword, and word-level embedd…
HostileNet
In this article, we deal with the task of hostile post detection in Hindi. The objective is to predict whether a social media post is hostile or not. Furthermore, if the post is hostile, we identify one or more fine-grained hostile dimensions out of the following four—fake, hate, offensive, and defamation. We propose HostileNet , a novel deep-learning framework that leverages HindiBERT-based contextual representations and hand-crafted features li…
Model-Agnostic Meta-Learning for Multilingual Hate Speech Detection
Hate speech in social media is a growing phenomenon, and detecting such toxic content has recently gained significant traction in the research community. Existing studies have explored fine-tuning language models (LMs) to perform hate speech detection, and these solutions have yielded significant performance. However, most of these studies are limited to detecting hate speech only in English, neglecting the bulk of hateful content that is generat…
AI Across Borders
This study investigates students’ perceptions of Generative Artificial Intelligence (GenAI), with a focus on Higher Education institutions in Northern Ireland and India. We collect quantitative Likert ratings and qualitative comments from 1211 students on their awareness and perceptions of AI and investigate variations in attitudes toward AI across institutions and subject areas, as well as interactions between these variables with demographic va…
Benchmarking Large Language Models Against Psychiatry Residents Using Traditional Institutional Assessments
Background: Artificial intelligence (AI) models demonstrate remarkable capabilities in healthcare applications, yet their performance compared to medical trainees in psychiatric education remains unexplored. This study evaluated the comparative performance of large language models (LLMs) against first-year psychiatry residents in standardized assessments at a premier Indian medical educational institute. Methods: For this study, the already-score…
Computer Science (10 works) · Artificial Intelligence (6 works) · Mathematics (5 works) · Machine learning (4 works) · Natural language processing (4 works) · Complex Network Analysis Techniques (3 works) · Data science (3 works) · Engineering (3 works) · Geography (3 works) · Misinformation and Its Impacts (3 works)