4 citations · 5 across the 12 of their papers we have counts for
13 papers
QAPruner: Quantization-Aware Vision Token Pruning for Multimodal Large Language Models
Xinhao Wang, Zhonyu Xia, Zhiwei Lin +2
Multimodal Large Language Models (MLLMs) have shown strong reasoning ability, but their high computational and memory costs hinder deployment in resource-constrained settings. Whil…
ELITE: Experiential Learning and Intent-Aware Transfer for Self-improving Embodied Agents
Bingqing Wei, Zhongyu Xia, Dingai Liu +3
Vision-language models (VLMs) have shown remarkable general capabilities, yet embodied agents built on them fail at complex tasks, often skipping critical steps, proposing invalid…
Multi-Representation Adapter with Neural Architecture Search for Efficient Range-Doppler Radar Object Detection
Zhiwei Lin, Weicheng Zheng, Yongtao Wang
Detecting objects efficiently from radar sensors has recently become a popular trend due to their robustness against adverse lighting and weather conditions compared with cameras.…
SAR-NAS: Lightweight SAR Object Detection with Neural Architecture Search
Xinyi Yu, Zhiwei Lin, Yongtao Wang
Synthetic Aperture Radar (SAR) object detection faces significant challenges from speckle noise, small target ambiguities, and on-board computational constraints. While existing ap…
PTQAT: A Hybrid Parameter-Efficient Quantization Algorithm for 3D Perception Tasks
Xinhao Wang, Zhiwei Lin, Zhongyu Xia +1
Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) represent two mainstream model quantization approaches. However, PTQ often leads to unacceptable performance…
RFTF: Reinforcement Fine-tuning for Embodied Agents with Temporal Feedback
Junyang Shu, Zhiwei Lin, Yongtao Wang
Vision-Language-Action (VLA) models have demonstrated significant potential in the field of embodied intelligence, enabling agents to follow human instructions to complete complex…