9 papers
SafeCommit: Certifying When Memory-Grounded Agents May Safely Act
Mayur Akewar, Ravi Ranjan
Long-horizon agents increasingly use persistent memory and tools to take actions with external side effects. A central failure mode is premature commitment: an agent acts before re…
Listening with Attention: Entropy-Guided Explainability for Transformer-Based Audio Models
Ravi Ranjan, Utkarsh Grover, Xiaomin Lin +1
Transformer-based automatic speech recognition (ASR) models such as Whisper are highly accurate, but their predictions remain difficult to interpret. Existing explainable AI (XAI)…
PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs
Ravi Ranjan, Utkarsh Grover, Xiaomin Lin +1
Large language models (LLMs) can provide automated feedback in educational settings, but aligning an LLMs style with a specific instructors tone while maintaining diagnostic correc…
VLA-Forget: Vision-Language-Action Unlearning for Embodied Foundation Models
Ravi Ranjan, Agoritsa Polyzou
Vision-language-action (VLA) models are emerging as embodied foundation models for robotic manipulation, but their deployment introduces a new unlearning challenge: removing unsafe…
G-Drift MIA: Membership Inference via Gradient-Induced Feature Drift in LLMs
Ravi Ranjan, Utkarsh Grover, Xiaomin Lin +1
Large language models (LLMs) are trained on massive web-scale corpora, raising growing concerns about privacy and copyright. Membership inference attacks (MIAs) aim to determine wh…
CatRAG: Functor-Guided Structural Debiasing with Retrieval Augmentation for Fair LLMs
Ravi Ranjan, Utkarsh Grover, Mayur Akewar +2
Large Language Models (LLMs) are deployed in high-stakes settings but can show demographic, gender, and geographic biases that undermine fairness and trust. Prior debiasing methods…