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State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China
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LLM-generated test suites are shockingly bad at catching even simple code mutations, with even the best models failing to detect over 60% of them.
Attention Sink, where Transformers fixate on seemingly irrelevant tokens, is more than just a quirk – it's a fundamental challenge impacting training, inference, and even causing hallucinations, demanding a systematic approach to understanding and mitigating its effects.
