12 citations · 26 across the 4 of their papers we have counts for
4 papers
Learning to Grasp Anything by Playing with Random Toys
Dantong Niu, Yuvan Sharma, Baifeng Shi +11
Robotic manipulation policies often struggle to generalize to novel objects, limiting their real-world utility. In contrast, cognitive science suggests that children develop genera…
A Simple and Effective Positional Encoding for Transformers
Pu-Chin Chen, Henry Tsai, Srinadh Bhojanapalli +3
Transformer models are permutation equivariant. To supply the order and type information of the input tokens, position and segment embeddings are usually added to the input. Recent…
Rethinking embedding coupling in pre-trained language models
Hyung Won Chung, Thibault Févry, Henry Tsai +2
We re-evaluate the standard practice of sharing weights between input and output embeddings in state-of-the-art pre-trained language models. We show that decoupled embeddings provi…
Finding Fast Transformers: One-Shot Neural Architecture Search by Component Composition
Henry Tsai, Jayden Ooi, Chun-Sung Ferng +2
Transformer-based models have achieved stateof-the-art results in many tasks in natural language processing. However, such models are usually slow at inference time, making deploym…