27cc3576a6f149e95cf68afc3e25cd6c.zip Online

Reviewers generally agreed that the method offers superior accuracy and efficiency across multiple tasks, supported by thorough ablation studies on design choices.

One reviewer pointed out that the methods ZIP was compared against (like BLACKVIP and BPTVLM) were from 2023, and suggested that more recent 2024 benchmarks should have been included for a fairer comparison.

Reviewers from the research community have shared their direct impressions of the work: 27cc3576a6f149e95cf68afc3e25cd6c.zip

Reviewers pointed out that the soft prompt reparameterization design choices were thoroughly tested, including detailed ablation studies.

It addresses the high query requirements of existing methods by reducing problem dimensionality and using "intrinsic-dimensional gradient clipping." Reviewers generally agreed that the method offers superior

Because black-box prompt tuning is a niche field, some reviewers found it difficult to judge exactly how "new" the method was compared to the very latest unpublished research. Community Feedback

Evaluators noted superior accuracy across 13+ different tasks and strong performance in "few-shot" settings (learning from very little data). It addresses the high query requirements of existing

The community recognized the extensive evaluations showcasing superior accuracy and query efficiency over 13+ tasks.