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M-agents harbor 158 unique implementation bugs that could lead to critical failures in real-world applications, and a new tool can identify over 60% of these issues automatically.
Distinguishing negative samples can boost LLM reasoning performance on ARC-like tasks by providing critical near-miss alternatives.
