8 citations · 18 across the 20 of their papers we have counts for
5 papers · 1 filter
Minerva: Reinforcement Learning with Verifiable Rewards for Cyber Threat Intelligence LLMs
Md Tanvirul Alam, Aritran Piplai, Ionut Cardei +2
Cyber threat intelligence (CTI) analysts routinely convert noisy, unstructured security artifacts into standardized, automation-ready representations. Although large language model…
Limits of Generalization in RLVR: Two Case Studies in Mathematical Reasoning
Md Tanvirul Alam, Nidhi Rastogi
Mathematical reasoning is a central challenge for large language models (LLMs), requiring not only correct answers but also faithful reasoning processes. Reinforcement Learning wit…
Towards Understanding Self-play for LLM Reasoning
Justin Yang Chae, Md Tanvirul Alam, Nidhi Rastogi
Recent advances in large language model (LLM) reasoning, led by reinforcement learning with verifiable rewards (RLVR), have inspired self-play post-training, where models improve b…
ADAPT: A Pseudo-labeling Approach to Combat Concept Drift in Malware Detection
Md Tanvirul Alam, Aritran Piplai, Nidhi Rastogi
Machine learning models are commonly used for malware classification; however, they suffer from performance degradation over time due to concept drift. Adapting these models to cha…
MORPH: Towards Automated Concept Drift Adaptation for Malware Detection
Md Tanvirul Alam, Romy Fieblinger, Ashim Mahara +1
Concept drift is a significant challenge for malware detection, as the performance of trained machine learning models degrades over time, rendering them impractical. While prior re…