6 papers
VLN-Cache: Enabling Token Caching for VLN Models with Visual/Semantic Dynamics Awareness
Zihao Zheng, Zhihao Mao, Xingyue Zhou +9
Vision-and-Language Navigation (VLN) increasingly relies on large vision-language models, but their inference cost conflicts with real-time deployment. Token caching is a promising…
FreqCache: Accelerating Embodied VLN Models with Adaptive Frequency-Guided Token Caching
Zihao Zheng, Xingyue Zhou, Zhihao Mao +7
Vision-Language-Navigation (VLN) models exhibit excellent navigation accuracy but incur high computational overhead. Token caching has emerged as a promising training-free strategy…
HeiSD: Hybrid Speculative Decoding for Embodied Vision-Language-Action Models with Kinematic Awareness
Zihao Zheng, Zhihao Mao, Sicheng Tian +8
Vision-Language-Action (VLA) Models have become the mainstream solution for robot control, but suffer from slow inference speeds. Speculative Decoding (SD) is a promising accelerat…
KERV: Kinematic-Rectified Speculative Decoding for Embodied VLA Models
Zihao Zheng, Zhihao Mao, Maoliang Li +6
Vision-Language-Action (VLA) models build a token-domain robot control paradigm, yet suffer from low speed. Speculative Decoding (SD) is an optimization strategy that can boost inf…
2D or 3D: Who Governs Salience in VLA Models? -- Tri-Stage Token Pruning Framework with Modality Salience Awareness
Zihao Zheng, Sicheng Tian, Zhihao Mao +8
Vision-Language-Action (VLA) models have emerged as the mainstream of embodied intelligence. Recent VLA models have expanded their input modalities from 2D-only to 2D+3D paradigms,…
MARS: Harmonizing Multimodal Convergence via Adaptive Rank Search
Minkyoung Cho, Insu Jang, Shuowei Jin +5
Fine-tuning Multimodal Large Language Models (MLLMs) with parameter-efficient methods like Low-Rank Adaptation (LoRA) is crucial for task adaptation. However, imbalanced training d…