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cs.LG2026
CRoPE: Efficient Parametrization of Rotary Positional Embedding
Beicheng Lou, Zifei Xu, Vivian W. H. Wong
Rotary positional embedding has become the state-of-the-art approach to encode position information in transformer-based models. While it is often succinctly expressed in complex l…
cs.LG2020
Compressed imitation learning
Nathan Zhao, Beicheng Lou
In analogy to compressed sensing, which allows sample-efficient signal reconstruction given prior knowledge of its sparsity in frequency domain, we propose to utilize policy simpli…