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D DianShi-RxnDB is presented, a large-scale, fine-grained organic reaction data platform built via a fully automated extraction and normalization pipeline integrating patent text, images, and reaction schemes integrating patent text, images, and reaction schemes.
Achieving up to 2.7x speedup in AI accelerator simulations by compressing multiple RTL nodes into a single instruction sequence could revolutionize chip design efficiency.
Achieving a 100% detection rate for transient faults in CKKS computation with minimal overhead could revolutionize the reliability of encrypted data processing on standard CPUs.
Automating fault tolerance at the RTL level is now possible: FT-Pilot uses LLMs to rewrite hardware designs, slashing error rates without manual intervention.
LLMs can now write better hardware verification code: CoverAssert boosts functional coverage by up to 15% by iteratively guiding LLMs with coverage feedback.
Emotional support chatbots get a boost by learning directly from simulated user reactions, generating natural language critiques that drive better conversations.
