Shengzhuo Yang and coauthors · Paper · Published 2026-07-10 · Source accessed 2026-09-28
Factual summary and attribution only; no upstream prose, images, weights, or dataset redistributed.
Referenced by 3 records: LIBERO · CALVIN · TS-Mask VLA
TS-Mask VLA is a manipulation research framework that models temporal and spatial structure in discrete action sequences.
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
The paper combines a discrete diffusion action expert with bridge attention and a masking strategy across time and action dimensions. This distinguishes its action decoder from purely autoregressive token generation.
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
The authors report both simulation benchmarks and physical tasks. This registry links LIBERO and CALVIN without importing abstract-level aggregate numbers that lack a fully captured evaluation protocol.
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
Author-reported paper results are not independent reproductions; release licensing remains unverified.
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
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Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
Connection reviewed 2026-09-28
Shengzhuo Yang and coauthors · Published 2026-07-10 · Source accessed 2026-09-28
Connection reviewed 2026-09-28
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Shengzhuo Yang and coauthors · Paper · Published 2026-07-10 · Source accessed 2026-09-28
Factual summary and attribution only; no upstream prose, images, weights, or dataset redistributed.
Referenced by 3 records: LIBERO · CALVIN · TS-Mask VLA