14 papers
Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning
Shilin Shan, Chuhao Zhou, Ruize Wang +30
Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical…
YARD: Y-Architecture Register Decoding for Efficient Hallucination Mitigation in Large Vision-Language Models
Ting Chen, Geng Li, Guohao Chen +5
Contrastive decoding (CD) seeks to mitigate hallucinations in Large Vision-Language Models (LVLMs) by contrasting the output distributions of a standard model and a visually degrad…
OccamToken: Efficient VLM Inference with Training-Free and Budget-Adaptive Token Pruning
Geng Li, Guohao Chen, Ting Chen +6
Vision-language models (VLMs) rely on long visual token sequences for visual understanding, making the prefill stage expensive in both computation and memory. Most existing pruning…
Guided Trajectory Optimization with Sparse Scaling for Test-Time Diffusion
Gang Dai, Yining Huang, Yiming Xia +2
The efficient Test-Time Scaling (TTS) paradigm offers a promising perspective for enhancing the generation performance of diffusion models. However, current solutions are limited t…
ZeroSiam: An Efficient Asymmetry for Test-Time Entropy Optimization without Collapse
Guohao Chen, Shuaicheng Niu, Deyu Chen +5
Test-time entropy minimization helps adapt a model to novel environments and incentivize its reasoning capability, unleashing the model's potential during inference by allowing it…
EVA-0: Test-Time Model Evolution with Only Two Forward Passes per Sample
Guohao Chen, Shuaicheng Niu, Geng Li +4
Test-time model evolution offers a promising way for deployed models to improve from unlabeled test-time experience, yet most existing methods depend on backpropagation (BP), which…