1 citations · 1 across the 4 of their papers we have counts for
5 papers
Slow-Fast Multi-Teacher On-Policy Distillation for Capability Preservation
Xiaofei Yin, Tong Chu, Jiyuan Fu +3
Foundation multimodal large language models are designed to support a broad spectrum of capabilities across diverse domains. Multi-teacher on-policy distillation (MOPD) provides an…
UniDFKD: A Unified Semantic Prior Framework for Architecture-Agnostic Data-Free Knowledge Distillation
Xuewan He, Tong Chu, Zihan Cheng +5
Data-Free Knowledge Distillation (DFKD) transfers knowledge from a pretrained teacher model to a compact student model by synthesizing semantically informative data, eliminating th…
The Next Screenshot Knows: Gated Hindsight Distillation for Mobile GUI Agents
Weiwei Li, Junzhuo Liu, Tong Chu +2
GUI agents are commonly trained offline from successful interaction trajectories. Standard training decomposes each trajectory into prefix-action pairs: the agent predicts an actio…
Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted Attacks
Anqi Zhao, Tong Chu, Yahao Liu +3
In this work, we study the black-box targeted attack problem from the model discrepancy perspective. On the theoretical side, we present a generalization error bound for black-box…
Undoing the Damage of Label Shift for Cross-domain Semantic Segmentation
Yahao Liu, Jinhong Deng, Jiale Tao +3
Existing works typically treat cross-domain semantic segmentation (CDSS) as a data distribution mismatch problem and focus on aligning the marginal distribution or conditional dist…