11 citations · 11 across the 11 of their papers we have counts for
11 papers
ARIAL: An Agentic Framework for Document VQA with Precise Answer Localization
Ahmad Mohammadshirazi, Pinaki Prasad Guha Neogi, Dheeraj Kulshrestha +1
Document Visual Question Answering (VQA) requires models to not only extract accurate textual answers but also precisely localize them within document images, a capability critical…
Exploiting the Experts: Unauthorized Compression in MoE-LLMs
Pinaki Prasad Guha Neogi, Ahmad Mohammadshirazi, Dheeraj Kulshrestha +1
Mixture-of-Experts (MoE) architectures are increasingly adopted in large language models (LLMs) for their scalability and efficiency. However, their modular structure introduces a…
MGA-VQA: Secure and Interpretable Graph-Augmented Visual Question Answering with Memory-Guided Protection Against Unauthorized Knowledge Use
Ahmad Mohammadshirazi, Pinaki Prasad Guha Neogi, Dheeraj Kulshrestha +1
Document Visual Question Answering (DocVQA) requires models to jointly understand textual semantics, spatial layout, and visual features. Current methods struggle with explicit spa…
DocVAL: Validated Chain-of-Thought Distillation for Grounded Document VQA
Pinaki Prasad Guha Neogi, Ahmad Mohammadshirazi, Ser-Nam Lim +1
Document visual question answering requires models not only to answer questions correctly, but also to precisely localize answers within complex document layouts. While large visio…
InsightBuild: LLM-Powered Causal Reasoning in Smart Building Systems
Pinaki Prasad Guha Neogi, Ahmad Mohammadshirazi, Rajiv Ramnath
Smart buildings generate vast streams of sensor and control data, but facility managers often lack clear explanations for anomalous energy usage. We propose InsightBuild, a two-sta…
ALCo-FM: Adaptive Long-Context Foundation Model for Accident Prediction
Pinaki Prasad Guha Neogi, Ahmad Mohammadshirazi, Rajiv Ramnath
Traffic accidents are rare, yet high-impact events that require long-context multimodal reasoning for accurate risk forecasting. In this paper, we introduce ALCo-FM, a unified adap…
PIAD-SRNN: Physics-Informed Adaptive Decomposition in State-Space RNN
Ahmad Mohammadshirazi, Pinaki Prasad Guha Neogi, Rajiv Ramnath
Time series forecasting often demands a trade-off between accuracy and efficiency. While recent Transformer models have improved forecasting capabilities, they come with high compu…
DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and Trustworthiness
Ahmad Mohammadshirazi, Pinaki Prasad Guha Neogi, Ser-Nam Lim +1
Document Visual Question Answering (VQA) demands robust integration of text detection, recognition, and spatial reasoning to interpret complex document layouts. In this work, we in…
DocParseNet: Advanced Semantic Segmentation and OCR Embeddings for Efficient Scanned Document Annotation
Ahmad Mohammadshirazi, Ali Nosrati Firoozsalari, Mengxi Zhou +2
Automating the annotation of scanned documents is challenging, requiring a balance between computational efficiency and accuracy. DocParseNet addresses this by combining deep learn…
CrashFormer: A Multimodal Architecture to Predict the Risk of Crash
Amin Karimi Monsefi, Pouya Shiri, Ahmad Mohammadshirazi +4
Reducing traffic accidents is a crucial global public safety concern. Accident prediction is key to improving traffic safety, enabling proactive measures to be taken before a crash…
Novel Physics-Based Machine-Learning Models for Indoor Air Quality Approximations
Ahmad Mohammadshirazi, Aida Nadafian, Amin Karimi Monsefi +2
Cost-effective sensors are capable of real-time capturing a variety of air quality-related modalities from different pollutant concentrations to indoor/outdoor humidity and tempera…