8 citations · 11 across the 16 of their papers we have counts for
8 papers · 1 filter
MobiAgent: Dual-Loop Recursive Policy Self-Improvement for Long-Horizon Mobile Manipulation
Chenzhi Liu, Yue Zhang, Jiehong Lin +4
Long-horizon mobile manipulation presents significant challenges due to compounding execution errors and capacity interference between locomotion and arm control. While recent Visi…
AnyStep-WAM: Budget-Aligned Distillation and Adaptive Inference for World Action Models
Rui Wang, Xiangyu Wang, Donglin Yang +4
World-action models (WAMs) couple predictive visual modeling with action generation, typically relying on iterative denoising with a fixed denoising steps. However, manipulation ta…
LiFR v2: Completion-Augmented Event Propagation for High-Rate Dense Prediction
Tao Wan, Xiaoshan Wu, Yifei Yu +6
High-rate dense perception in dynamic environments is limited by the low update rate of RGB cameras, as rapid scene changes can occur between frames. Event cameras offer temporally…
RRAM-DP: Device-Calibrated Differential Privacy for In-Memory Edge Learning
Kwunhang Wong, Jichang Yang, Karl M. H. Lai +7
Edge Artificial Intelligence of Things (AIoT) systems often collect sensitive data in situ, raising serious privacy concerns. Resistive-switching random-access memory (RRAM) is an…
PhysEditBench: A Protocol-Conditioned Benchmark for Dense Physical-Map Prediction with Image Editors
Jiaxin Yang, Yu Hou, Muxin Liu +5
Can general-purpose image editors predict physical maps from a single RGB image? General-purpose image editors differ from standard task-specific dense-prediction models: they do n…
CoRe-Gen: Robust Spectrum-to-Structure Generation under Imperfect Fingerprint Conditions
Tianbo Liu, Chixiang Lu, Jing Hao +4
Molecular structure elucidation from tandem mass spectra (MS/MS) remains challenging, particularly for de novo generation beyond database coverage. A common approach decomposes the…
When to Trust Imagination: Adaptive Action Execution for World Action Models
Rui Wang, Yue Zhang, Jiehong Lin +5
World Action Models (WAMs) jointly predict future visual observations and actions, but typically execute a fixed number of actions before replanning, regardless of whether the imag…
Parameter Efficient Machine Unlearning on Hybrid Resistive Memory based Compute-in-Memory Accelerators
Ning Lin, Jichang Yang, Yangu He +17
Resistive memory compute-in-memory accelerators provide energy efficient analogue matrix vector multiplication for neural network inference, but frequent reprogramming of analogue…