1 citations · 1 across the 15 of their papers we have counts for
17 papers
SIFT: Robust Meta-Faithfulness Verification of Chain-of-Thought Reasoning Under Distribution Shift
Noor Islam S. Mohammad, Md. Basim Al Zabir Shammo, Hasan Siddiki +3
Chain-of-Thought (CoT) faithfulness detectors are widely used to audit reasoning models, yet a detector is itself a predictor whose verdicts are treated as stable properties. We as…
Interference Meets Inference: Bayesian Time-Series Modeling of Radio-Frequency Interference
Jade M. Ducharme, Andrei Li, Michael J. Wilensky +1
Radio-frequency interference (RFI) remains a major challenge for modern radio astronomy experiments. In this work, we cast RFI detection as a one-dimensional time-series anomaly-de…
Harmfulness Propagation Dynamics: Layer-wise Trajectories of Adversarial Intent in Large Language Models
Noor Islam S. Mohammad, Uluğ Bayazıt
We identify \textbf{Harmfulness Propagation Dynamics (HPD)}: for harmful prompts, the projection of the last-token hidden state onto a learned harm direction rises monotonically wi…
Salient Knowledge Pathways: Sparse Cross-Modal Routing for Efficient Knowledge-Intensive Multimodal Question Answering
Noor Islam S. Mohammad, Uluğ Bayazıt
Knowledge-intensive multimodal question answering (KI-MMQA) sits at the intersection of three expensive primitives: long visual token sequences, dense retrieval over large external…
SURGELLM: Rethinking Multi-Task Evaluation through Task-Aware Feature Gating with Class-Balanced Normalization
Noor Islam S. Mohammad, Ulug Bayazit
Fine-tuned encoders deployed across heterogeneous NLP tasks face three compounding problems: mismatched inductive biases, class-imbalance corruption of feature statistics, and no m…
Coherence Under Commitment: Probing Generalization and Vacuous Memorization in LLM Logical Reasoning
Noor Islam S. Mohammad, Mahmudul Hasan
Large language models (LLMs) deployed for logical reasoning in knowledge-intensive domains exhibit a subtle but critical failure: coherence can be vacuously achieved through system…
MIRAGE: Auditing Anti-Muslim Bias in Frontier LLMs Across Reasoning, Agentic, and Time-Coupled Conditions
Noor Islam S. Mohammad, Tamim Sheikh
Five years after the discovery of persistent anti-Muslim bias in large language models, most evaluations remain confined to single-turn prompt completion, a setting that no longer…
The Faithfulness Gap: Certifying Semantic Equivalence Between Natural-Language and Formal Mathematical Statements
Noor Islam S. Mohammad, Tamim Sheikh
Autoformalization, translating natural-language mathematics into formal proof assistants, is bottlenecked not by translation fluency but by \emph{faithfulness}: a formal statement…
Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning
Md Muntaqim Meherab, Noor Islam S. Mohammad, Faiza Feroz
Sparse autoencoders can localize where concepts live in language models, but not how they interact during multi-step reasoning. We propose Causal Concept Graphs (CCG): a directed a…
SafeLM: Unified Privacy-Aware Optimization for Trustworthy Federated Large Language Models
Noor Islam S. Mohammad, Uluğ Bayazıt
Large language models (LLMs) are increasingly deployed in high-stakes domains, yet a unified treatment of their overlapping safety challenges remains lacking. We present SafeLM, a…
EdgeDetect: Importance-Aware Gradient Compression with Homomorphic Aggregation for Federated Intrusion Detection
Noor Islam S. Mohammad
Federated learning (FL) enables collaborative intrusion detection without raw data exchange, but conventional FL incurs high communication overhead from full-precision gradient tra…
Regularized Meta-Learning for Improved Generalization
Noor Islam S. Mohammad, Md Muntaqim Meherab
Deep ensemble methods often improve predictive performance, yet they suffer from three practical limitations: redundancy among base models that inflates computational cost and degr…
Breaking the Temporal Complexity Barrier: Bucket Calculus for Parallel Machine Scheduling
Noor Islam S. Mohammad
This paper introduces bucket calculus, a novel mathematical framework that fundamentally transforms the computational complexity landscape of parallel machine scheduling optimizati…
Hierarchical Spatial Algorithms for High-Resolution Image Quantization and Feature Extraction
Noor Islam S. Mohammad
This study introduces a modular framework for spatial image processing, integrating grayscale quantization, color and brightness enhancement, image sharpening, bidirectional transf…
CoGate-LSTM: Prototype-Guided Feature-Space Gating for Mitigating Gradient Dilution in Imbalanced Toxic Comment Classification
Noor Islam S. Mohammad
Toxic text classification for online moderation remains challenging under extreme class imbalance, where rare but high-risk labels such as threat and severe_toxic are consistently…
Attribution Graphs and Causal Probing for Mechanistic Discovery and Bias Repair in Multimodal Generative Learning
Noor Islam S. Mohammad, Uluğ Bayazıt
We treat the internals of generative models as mechanistic objects rather than black boxes. We introduce \textbf{Attribution Graphs} (AGs), which extend GradCAM++ to circuit-level…
Data Scheduling Algorithm for Scalable and Efficient IoT Sensing in Cloud Computing
Noor Islam S. Mohammad
The rapid growth of Internet of Things (IoT) devices produces massive, heterogeneous data streams, demanding scalable and efficient scheduling in cloud environments to meet latency…