systems and reinforcement
Reforcemind explores the fundamental post-training bottlenecks of Vision-Language-Action models.
systems and reinforcement
Reforcemind explores the fundamental post-training bottlenecks of Vision-Language-Action models.
Multi-Agent Reinforcement Learning (MARL) cybersecurity simulator
Python 2
A hpc LLVM Pass extracting semantic Control-Data Flow Graphs (CDFG) from Intermediate Representation for Graph Neural Networks. Enables cross-language code retrieval and clone detection beyond toke…
Python 1
A framework for end-to-end AI inference optimization: from model parsing and graph IR, through graph and kernel optimizations, to hardware profiling, auto-tuning, and visualization.
Python
Event-Driven Continuous-Time Graph MARL for Asynchronous Cyber Defense in NetForge_RL. A framework for training autonomous cyber defenders in a continuous-time POSMDP environment. Features Neural ODE temporal dynamics, GAT spatial reasoning, and a Sim2Real evaluation bridge against live CVE payloads.
Implementation of Epistemic Time-Dilation MAPPO (ETD-MAPPO). A compute-aware MARL framework where agents autonomously modulate their execution frequency based on uncertainty to reduce inference overhead.
A hpc LLVM Pass extracting semantic Control-Data Flow Graphs (CDFG) from Intermediate Representation for Graph Neural Networks. Enables cross-language code retrieval and clone detection beyond token-based approaches.
A framework for end-to-end AI inference optimization: from model parsing and graph IR, through graph and kernel optimizations, to hardware profiling, auto-tuning, and visualization.
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