42 citations · 93 across the 31 of their papers we have counts for
32 papers
DMDIntel: Interpreting Large Language Models via Dynamic Mode Decomposition
Amogh Joshi, Animesh Mukherjee, Sergey Utyuzhnikov
In this work, we introduce DMDIntel which uses dynamic mode decomposition (DMD) to make the predictions made by LLMs in a classification task interpretable. It develops an input at…
CrowdCounter: A benchmark type-specific multi-target counterspeech dataset
Punyajoy Saha, Abhilash Datta, Abhik Jana +1
Counterspeech presents a viable alternative to banning or suspending users for hate speech while upholding freedom of expression. However, writing effective counterspeech is challe…
Sampling-Based Attack for Centrality Disruption in Complex Networks
Fariba Afrin Irany, Soumya Sarakar, Animesh Mukherjee +1
Many mobile networks are represented as graphs to obtain insight to their connectivity and transmission properties. Among these properties centrality resilience, that is, how well…
On Zero-Shot Counterspeech Generation by LLMs
Punyajoy Saha, Aalok Agrawal, Abhik Jana +2
With the emergence of numerous Large Language Models (LLM), the usage of such models in various Natural Language Processing (NLP) applications is increasing extensively. Counterspe…
InfFeed: Influence Functions as a Feedback to Improve the Performance of Subjective Tasks
Somnath Banerjee, Maulindu Sarkar, Punyajoy Saha +2
Recently, influence functions present an apparatus for achieving explainability for deep neural models by quantifying the perturbation of individual train instances that might impa…
Low-Resource Counterspeech Generation for Indic Languages: The Case of Bengali and Hindi
Mithun Das, Saurabh Kumar Pandey, Shivansh Sethi +2
With the rise of online abuse, the NLP community has begun investigating the use of neural architectures to generate counterspeech that can "counter" the vicious tone of such abusi…
Exploring the Limits of Zero Shot Vision Language Models for Hate Meme Detection: The Vulnerabilities and their Interpretations
Naquee Rizwan, Paramananda Bhaskar, Mithun Das +3
There is a rapid increase in the use of multimedia content in current social media platforms. One of the highly popular forms of such multimedia content are memes. While memes have…
Probing LLMs for hate speech detection: strengths and vulnerabilities
Sarthak Roy, Ashish Harshavardhan, Animesh Mukherjee +1
Recently efforts have been made by social media platforms as well as researchers to detect hateful or toxic language using large language models. However, none of these works aim t…
BanglaAbuseMeme: A Dataset for Bengali Abusive Meme Classification
Mithun Das, Animesh Mukherjee
The dramatic increase in the use of social media platforms for information sharing has also fueled a steep growth in online abuse. A simple yet effective way of abusing individuals…
A Deep Dive into the Disparity of Word Error Rates Across Thousands of NPTEL MOOC Videos
Anand Kumar Rai, Siddharth D Jaiswal, Animesh Mukherjee
Automatic speech recognition (ASR) systems are designed to transcribe spoken language into written text and find utility in a variety of applications including voice assistants and…
Evaluating ChatGPT's Performance for Multilingual and Emoji-based Hate Speech Detection
Mithun Das, Saurabh Kumar Pandey, Animesh Mukherjee
Hate speech is a severe issue that affects many online platforms. So far, several studies have been performed to develop robust hate speech detection systems. Large language models…
HateMM: A Multi-Modal Dataset for Hate Video Classification
Mithun Das, Rohit Raj, Punyajoy Saha +3
Hate speech has become one of the most significant issues in modern society, having implications in both the online and the offline world. Due to this, hate speech research has rec…
HateProof: Are Hateful Meme Detection Systems really Robust?
Piush Aggarwal, Pranit Chawla, Mithun Das +4
Exploiting social media to spread hate has tremendously increased over the years. Lately, multi-modal hateful content such as memes has drawn relatively more traction than uni-moda…
Rationale-Guided Few-Shot Classification to Detect Abusive Language
Punyajoy Saha, Divyanshu Sheth, Kushal Kedia +2
Abusive language is a concerning problem in online social media. Past research on detecting abusive language covers different platforms, languages, demographies, etc. However, mode…
Hate Speech and Offensive Language Detection in Bengali
Mithun Das, Somnath Banerjee, Punyajoy Saha +1
Social media often serves as a breeding ground for various hateful and offensive content. Identifying such content on social media is crucial due to its impact on the race, gender,…
Decoding Demographic un-fairness from Indian Names
Medidoddi Vahini, Jalend Bantupalli, Souvic Chakraborty +1
Demographic classification is essential in fairness assessment in recommender systems or in measuring unintended bias in online networks and voting systems. Important fields like e…
Placing (Historical) Facts on a Timeline: A Classification cum Coref Resolution Approach
Sayantan Adak, Altaf Ahmad, Aditya Basu +1
A timeline provides one of the most effective ways to visualize the important historical facts that occurred over a period of time, presenting the insights that may not be so appar…
CounterGeDi: A controllable approach to generate polite, detoxified and emotional counterspeech
Punyajoy Saha, Kanishk Singh, Adarsh Kumar +2
Recently, many studies have tried to create generation models to assist counter speakers by providing counterspeech suggestions for combating the explosive proliferation of online…
CRUSH: Contextually Regularized and User anchored Self-supervised Hate speech Detection
Souvic Chakraborty, Parag Dutta, Sumegh Roychowdhury +1
The last decade has witnessed a surge in the interaction of people through social networking platforms. While there are several positive aspects of these social platforms, the prol…
HateCheckHIn: Evaluating Hindi Hate Speech Detection Models
Mithun Das, Punyajoy Saha, Binny Mathew +1
Due to the sheer volume of online hate, the AI and NLP communities have started building models to detect such hateful content. Recently, multilingual hate is a major emerging chal…
Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages
Mithun Das, Somnath Banerjee, Animesh Mukherjee
Abusive language is a growing concern in many social media platforms. Repeated exposure to abusive speech has created physiological effects on the target users. Thus, the problem o…
hate-alert@DravidianLangTech-ACL2022: Ensembling Multi-Modalities for Tamil TrollMeme Classification
Mithun Das, Somnath Banerjee, Animesh Mukherjee
Social media platforms often act as breeding grounds for various forms of trolling or malicious content targeting users or communities. One way of trolling users is by creating mem…
Marching with the Pink Parade: Evaluating Visual Search Recommendations for Non-binary Clothing Items
Siddharth D Jaiswal, Animesh Mukherjee
Fashion, a highly subjective topic is interpreted differently by all individuals. E-commerce platforms, despite these diverse requirements, tend to cater to the average buyer inste…
Two-Face: Adversarial Audit of Commercial Face Recognition Systems
Siddharth D Jaiswal, Karthikeya Duggirala, Abhisek Dash +1
Computer vision applications like automated face detection are used for a variety of purposes ranging from unlocking smart devices to tracking potential persons of interest for sur…