Jun Yin — Papers on Cortexa

arxivcs.ARcs.AI2026-07-30

ARES: Adaptive Reasoning-Effort Steering for PPA- and Cost-Aware RTL Optimization with LLM Agents

Stef Cuyckens, Mihaela Jivanescu, Jun Yin, Chao Fang, Marian Verhelst

Large language model (LLM) agents optimize the power, performance, and area (PPA) of register-transfer-level (RTL) designs by iterating over edits, synthesis, and PPA analysis, paying a dollar cost for every LLM call. Prior agents report the quality reached without its normalized…

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arxivcs.ARcs.AIcs.LG2026-07-24

HiKV: Hierarchical Importance-Aware KV Cache with Hardware Acceleration for LLM Decoding

Chao Fang, Jun Yin, Man Shi, Marian Verhelst

With the rapid adoption of long-context large language models (LLMs), the continuously growing KV cache during decoding has become the critical memory bottleneck. To tackle this challenge, we propose HiKV, a novel algorithm-hardware co-design that exploits KV cache redundancy thr…

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