58 citations · 215 across the 27 of their papers we have counts for
28 papers
Are Large Language Models Economically Viable for Industry Deployment?
Abdullah Mohammad, Sushant Kumar Ray, Pushkar Arora +5
Generative AI-powered by Large Language Models (LLMs)-is increasingly deployed in industry across healthcare decision support, financial analytics, enterprise retrieval, and conver…
AlignCultura: Towards Culturally Aligned Large Language Models?
Gautam Siddharth Kashyap, Mark Dras, Usman Naseem
Cultural alignment in Large Language Models (LLMs) is essential for producing contextually aware, respectful, and trustworthy outputs. Without it, models risk generating stereotype…
Are Aligned Large Language Models Still Misaligned?
Usman Naseem, Gautam Siddharth Kashyap, Rafiq Ali +4
Misalignment in Large Language Models (LLMs) arises when model behavior diverges from human expectations and fails to simultaneously satisfy safety, value, and cultural dimensions,…
Can Large Language Models Make Everyone Happy?
Usman Naseem, Gautam Siddharth Kashyap, Ebad Shabbir +3
Misalignment in Large Language Models (LLMs) refers to the failure to simultaneously satisfy safety, value, and cultural dimensions, leading to behaviors that diverge from human ex…
When the Model Said 'No Comment', We Knew Helpfulness Was Dead, Honesty Was Alive, and Safety Was Terrified
Gautam Siddharth Kashyap, Mark Dras, Usman Naseem
Large Language Models (LLMs) need to be in accordance with human values-being helpful, harmless, and honest (HHH)-is important for safe deployment. Existing works use Supervised Fi…
Do Large Language Models Reflect Demographic Pluralism in Safety?
Usman Naseem, Gautam Siddharth Kashyap, Sushant Kumar Ray +3
Large Language Model (LLM) safety is inherently pluralistic, reflecting variations in moral norms, cultural expectations, and demographic contexts. Yet, existing alignment datasets…
They Said Memes Were Harmless-We Found the Ones That Hurt: Decoding Jokes, Symbols, and Cultural References
Sahil Tripathi, Gautam Siddharth Kashyap, Mehwish Nasim +3
Meme-based social abuse detection is challenging because harmful intent often relies on implicit cultural symbolism and subtle cross-modal incongruence. Prior approaches, from fusi…
Revealing the Truth with ConLLM for Detecting Multi-Modal Deepfakes
Gautam Siddharth Kashyap, Harsh Joshi, Niharika Jain +4
The rapid rise of deepfake technology poses a severe threat to social and political stability by enabling hyper-realistic synthetic media capable of manipulating public perception.…
Do Clinical Question Answering Systems Really Need Specialised Medical Fine Tuning?
Sushant Kumar Ray, Gautam Siddharth Kashyap, Sahil Tripathi +5
Clinical Question-Answering (CQA) industry systems are increasingly rely on Large Language Models (LLMs), yet their deployment is often guided by the assumption that domain-specifi…
MAGIC-Enhanced Keyword Prompting for Zero-Shot Audio Captioning with CLIP Models
Vijay Govindarajan, Pratik Patel, Sahil Tripathi +2
Automated Audio Captioning (AAC) generates captions for audio clips but faces challenges due to limited datasets compared to image captioning. To overcome this, we propose the zero…
Too Helpful, Too Harmless, Too Honest or Just Right?
Gautam Siddharth Kashyap, Mark Dras, Usman Naseem
Large Language Models (LLMs) exhibit strong performance across a wide range of NLP tasks, yet aligning their outputs with the principles of Helpfulness, Harmlessness, and Honesty (…
We Think, Therefore We Align LLMs to Helpful, Harmless and Honest Before They Go Wrong
Gautam Siddharth Kashyap, Mark Dras, Usman Naseem
Alignment of Large Language Models (LLMs) is the ability to satisfy desired objectives during generation, which is critical for trustworthy deployment. In practice, alignment is of…
Can We Predict Your Next Move Without Breaking Your Privacy?
Arpita Soni, Sahil Tripathi, Gautam Siddharth Kashyap +5
We propose FLLL3M--Federated Learning with Large Language Models for Mobility Modeling--a privacy-preserving framework for Next-Location Prediction (NxLP). By retaining user data l…
Truth, Trust, and Trouble: Medical AI on the Edge
Mohammad Anas Azeez, Rafiq Ali, Ebad Shabbir +4
Large Language Models (LLMs) hold significant promise for transforming digital health by enabling automated medical question answering. However, ensuring these models meet critical…
Can Argus Judge Them All? Comparing VLMs Across Domains
Harsh Joshi, Gautam Siddharth Kashyap, Rafiq Ali +5
Vision-Language Models (VLMs) are increasingly used in industry VLM applications such as retrieval systems, content generation platforms, and decision-support workflows, where mode…
Can We Predict the Unpredictable? Leveraging DisasterNet-LLM for Multimodal Disaster Classification
Manaswi Kulahara, Gautam Siddharth Kashyap, Nipun Joshi +1
Effective disaster management requires timely and accurate insights, yet traditional methods struggle to integrate multimodal data such as images, weather records, and textual repo…
How Can Multimodal Remote Sensing Datasets Transform Classification via SpatialNet-ViT?
Gautam Siddharth Kashyap, Manaswi Kulahara, Nipun Joshi +1
Remote sensing datasets offer significant promise for tackling key classification tasks such as land-use categorization, object presence detection, and rural/urban classification.…
A Study of Hybrid and Evolutionary Metaheuristics for Single Hidden Layer Feedforward Neural Network Architecture
Gautam Siddharth Kashyap, Md Tabrez Nafis, Samar Wazir
Training Artificial Neural Networks (ANNs) with Stochastic Gradient Descent (SGD) frequently encounters difficulties, including substantial computing expense and the risk of conver…
ChildGuard: A Specialized Dataset for Combatting Child-Targeted Hate Speech
Gautam Siddharth Kashyap, Mohammad Anas Azeez, Rafiq Ali +3
Mental health industry faces growing concerns regarding hate speech directed at children's on social media, as exposure to such content can contribute to adverse psychological outc…
LLMs on a Budget? Say HOLA
Zohaib Hasan Siddiqui, Jiechao Gao, Ebad Shabbir +4
Running Large Language Models (LLMs) on edge devices is constrained by high compute and memory demands posing a barrier for real-time applications in sectors like healthcare, educa…
Heterogeneity over Homogeneity: Investigating Multilingual Speech Pre-Trained Models for Detecting Audio Deepfake
Orchid Chetia Phukan, Gautam Siddharth Kashyap, Arun Balaji Buduru +1
In this work, we investigate multilingual speech Pre-Trained models (PTMs) for Audio deepfake detection (ADD). We hypothesize that multilingual PTMs trained on large-scale diverse…
From Text to Transformation: A Comprehensive Review of Large Language Models' Versatility
Pravneet Kaur, Gautam Siddharth Kashyap, Ankit Kumar +3
This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Tran…
Are Paralinguistic Representations all that is needed for Speech Emotion Recognition?
Orchid Chetia Phukan, Gautam Siddharth Kashyap, Arun Balaji Buduru +1
Availability of representations from pre-trained models (PTMs) have facilitated substantial progress in speech emotion recognition (SER). Particularly, representations from PTM tra…
Detection of a facemask in real-time using deep learning methods: Prevention of Covid 19
Gautam Siddharth Kashyap, Jatin Sohlot, Ayesha Siddiqui +4
A health crisis is raging all over the world with the rapid transmission of the novel-coronavirus disease (Covid-19). Out of the guidelines issued by the World Health Organisation…