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The Pennsylvania State University
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Memory-augmented LLMs get a strategic upgrade: MemMA uses multi-agent reasoning to proactively guide memory construction and repair, leading to significant performance gains.
LLMs analyzing binaries aren't just spitting out tokens – they're exhibiting surprisingly structured reasoning patterns like "early pruning" and "targeted backtracking" that could revolutionize how we understand and control these systems.
