5 papers
Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning
Yuqi Li, Yuedong Tan, Huiran Duan +7
Unified multimodal object tracking has achieved remarkable robustness by leveraging complementary sensor data (e.g., RGB, Thermal, Depth), yet the heavy computational burden of sta…
Federated Knowledge Distillation for Multi-Model Architectures Lithography Hotspot Detection
Yuqi Li, Xingyou Lin, Yanli Li +6
As a special type of multimedia data, Lithography Hotspot Detection (LHD) training often requires stronger privacy protection than conventional multimedia data, and federated learn…
Hit-RAG: Learning to Reason with Long Contexts via Preference Alignment
Junming Liu, Yuqi Li, Shiping Wen +2
Despite the promise of Retrieval-Augmented Generation in grounding Multimodal Large Language Models with external knowledge, the transition to extensive contexts often leads to sig…
MMT-ARD: Multimodal Multi-Teacher Adversarial Distillation for Robust Vision-Language Models
Yuqi Li, Junhao Dong, Chuanguang Yang +5
Vision-Language Models (VLMs) are increasingly deployed in safety-critical applications, making their adversarial robustness a crucial concern. While adversarial knowledge distilla…
MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation
Weilun Feng, Chuanguang Yang, Haotong Qin +10
Diffusion models have demonstrated remarkable performance on vision generation tasks. However, the high computational complexity hinders its wide application on edge devices. Quant…