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cs.LG2026
Learning to Compute Is Not Learning to Retain or Reuse in Looped Transformers
Peilong Zhou, Hongtao Zhang, Yulong Huang +3
Looped transformers compute by applying one block repeatedly, so they can run for more loops than they were trained with. Recurrent reasoners are known to overthink: iterating past…
cs.LG2026
Alpha-RTL: Test-Time Training for RTL Hardware Optimization
Peilong Zhou, Zhirong Chen, Cangyuan Li +4
Large language models (LLMs) have shown increasing promise in generating functionally correct register-transfer-level (RTL) hardware designs. Recent systems improve further through…