Shuai Ma

Learnable observation front ends can dramatically improve low-rate speech reconstruction by capturing richer semantic information than traditional sampling methods.

By explicitly modeling literal polarity in SAT formulas, GNNs can more accurately predict unsatisfiable cores.

Direct generative decoding from semantics to images reduces hallucinations and accelerates inference speed by over eight times.