Yihong Liu

Removing an architectural prior abruptly tanks Transformer recall from 77% to 9%, but smoothly annealing it away allows the model to permanently consolidate the underlying circuit.

Machine translation benchmarks have functionally saturated, but pairing human-authored failure cases with deterministic verification rules reveals critical multimodal blind spots that automated metrics consistently miss.