3 citations · 3 across the 12 of their papers we have counts for
13 papers
WALDO: One-Shot Exemplar-Conditioned Object Detection in Cluttered Scenes
Kishor Datta Gupta, Ahmed Rafi Hasan, Md. Mahfuzur Rahman +2
Locating a specific object instance in a cluttered scene using a single reference image and a short description, and reporting when that instance is absent, large vision-language m…
TriCLE: Tri-Modal Vision-Language Reasoning for Edge-Deployed Fine-Grained Clustering
Kishor Datta Gupta, Md. Mahfuzur Rahman, Fahad Rahman +4
Edge platforms used for aerial observation must interpret aircraft imagery under limited memory, limited compute, and intermittent connectivity. This setting is difficult for stand…
GPF-LiveNews: A Streaming Evaluation Protocol for Group-Conditioned Framing in Large Language Models
Mohd Ariful Haque, Fahad Rahman, Kishor Datta Gupta +1
Deployed language models are evaluated in a non-stationary environment: model versions, retrieval layers, safety systems, and real-world inputs all change over time. Static bias be…
Verbatim Data Transcription Failures in LLM Code Generation: A State-Tracking Stress Test
Mohd Ariful Haque, Kishor Datta Gupta, Mohammad Ashiqur Rahman +1
Many real-world software tasks require exact transcription of provided data into code, such as cryptographic constants, protocol test vectors, allowlists, and calibration tables. T…
TinyLLM: Evaluation and Optimization of Small Language Models for Agentic Tasks on Edge Devices
Mohd Ariful Haque, Fahad Rahman, Kishor Datta Gupta +2
This paper investigates the effectiveness of small language models (SLMs) for agentic tasks (function/tool/API calling) with a focus on running agents on edge devices without relia…
Physics-Based Benchmarking Metrics for Multimodal Synthetic Images
Kishor Datta Gupta, Marufa Kamal, Md. Mahfuzur Rahman +3
Current state of the art measures like BLEU, CIDEr, VQA score, SigLIP-2 and CLIPScore are often unable to capture semantic or structural accuracy, especially for domain-specific or…
Beyond Visual Similarity: Rule-Guided Multimodal Clustering with explicit domain rules
Kishor Datta Gupta, Mohd Ariful Haque, Marufa Kamal +3
Traditional clustering techniques often rely solely on similarity in the input data, limiting their ability to capture structural or semantic constraints that are critical in many…
Continuous Monitoring of Large-Scale Generative AI via Deterministic Knowledge Graph Structures
Kishor Datta Gupta, Mohd Ariful Haque, Hasmot Ali +3
Generative AI (GEN AI) models have revolutionized diverse application domains but present substantial challenges due to reliability concerns, including hallucinations, semantic dri…
VLCE: A Knowledge-Enhanced Framework for Image Description in Disaster Assessment
Md. Mahfuzur Rahman, Kishor Datta Gupta, Marufa Kamal +5
General-purpose vision-language models (VLMs) such as LLaVA and QwenVL produce descriptions of disaster imagery that lack domain-specific vocabulary and actionable detail. We propo…
UrbanInsight: A Distributed Edge Computing Framework with LLM-Powered Data Filtering for Smart City Digital Twins
Kishor Datta Gupta, Md Manjurul Ahsan, Mohd Ariful Haque +2
Cities today generate enormous streams of data from sensors, cameras, and connected infrastructure. While this information offers unprecedented opportunities to improve urban life,…
Advanced Tool Learning and Selection System (ATLASS): A Closed-Loop Framework Using LLM
Mohd Ariful Haque, Justin Williams, Sunzida Siddique +4
The combination of LLM agents with external tools enables models to solve complex tasks beyond their knowledge base. Human-designed tools are inflexible and restricted to solutions…
SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deployment
Ariful Haque, Sunzida Siddique, Md. Mahfuzur Rahman +5
The integration of Large Language Models (LLMs) such as GitHub Copilot, ChatGPT, Cursor AI, and Codeium AI into software development has revolutionized the coding landscape, offeri…
Physical Rule-Guided Convolutional Neural Network
Kishor Datta Gupta, Marufa Kamal, Rakib Hossain Rifat +2
The black-box nature of Convolutional Neural Networks (CNNs) and their reliance on large datasets limit their use in complex domains with limited labeled data. Physics-Guided Neura…