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cs.RO2025
The Better You Learn, The Smarter You Prune: Towards Efficient Vision-language-action Models via Differentiable Token Pruning
Titong Jiang, Xuefeng Jiang, Yuan Ma +7
We present LightVLA, a simple yet effective differentiable token pruning framework for vision-language-action (VLA) models. While VLA models have shown impressive capability in exe…
cs.LG2025
SeqPE: Transformer with Sequential Position Encoding
Huayang Li, Yahui Liu, Hongyu Sun +5
Since self-attention layers in Transformers are permutation invariant by design, positional encodings must be explicitly incorporated to enable spatial understanding. However, fixe…
cs.CV2025★ 1 cited
SEGT: A General Spatial Expansion Group Transformer for nuScenes Lidar-based Object Detection Task
Cheng Mei, Hao He, Yahui Liu +1
In the technical report, we present a novel transformer-based framework for nuScenes lidar-based object detection task, termed Spatial Expansion Group Transformer (SEGT). To effici…