CKT-WAM transfers teacher WAM knowledge to students via compressed text-embedding contexts using LQCA and adapters, reaching 86.1% success on LIBERO-Plus with 1.17% trainable parameters and 83.3% in real-world tasks.
Proceedings of the 41st International Conference on Machine Learning , pages =
2 Pith papers cite this work. Polarity classification is still indexing.
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