11 citations · 13 across the 33 of their papers we have counts for
8 papers · 1 filter
Spectral Gating Networks
Jusheng Zhang, Yijia Fan, Kaitong Cai +5
Gating mechanisms are ubiquitous, yet a complementary question in feed-forward networks remains under-explored: how to introduce frequency-rich expressivity without sacrificing sta…
Rational ANOVA Networks
Jusheng Zhang, Ningyuan Liu, Qinhan Lyu +2
Deep neural networks typically treat nonlinearities as fixed primitives (e.g., ReLU), limiting both interpretability and the granularity of control over the induced function class.…
Causal Invariance and Counterfactual Learning Driven Cooperative Game for Multi-Label Classification
Yijia Fan, Jusheng Zhang, Kaitong Cai +2
Multi-label classification (MLC) remains vulnerable to label imbalance, spurious correlations, and distribution shifts, challenges that are particularly detrimental to rare label p…
Understanding Hardness of Vision-Language Compositionality from A Token-level Causal Lens
Ziliang Chen, Tianang Xiao, Jusheng Zhang +2
Contrastive Language-Image Pre-training (CLIP) delivers strong cross modal generalization by aligning images and texts in a shared embedding space, yet it persistently fails at com…
Guardian: Decoupling Exploration from Safety in Reinforcement Learning
Kaitong Cai, Jusheng Zhang, Jing Yang +1
Hybrid offline--online reinforcement learning (O2O RL) promises both sample efficiency and robust exploration, but suffers from instability due to distribution shift between offlin…
Learning Dynamics of VLM Finetuning
Jusheng Zhang, Kaitong Cai, Jing Yang +1
Preference-based finetuning of vision--language models (VLMs) is brittle: trivially wrong negatives inject uninformative gradients that destabilize training. We recast alignment as…
CF-VLM:CounterFactual Vision-Language Fine-tuning
Jusheng Zhang, Kaitong Cai, Yijia Fan +2
Recent advances in vision-language models (VLMs) have greatly improved cross-modal semantic understanding, yet significant limitations remain in fine-grained discrimination and dee…
Kolmogorov-Arnold Fourier Networks
Jusheng Zhang, Yijia Fan, Kaitong Cai +2
Although Kolmogorov-Arnold-based interpretable networks (KANs) possess strong theoretical expressiveness, they suffer from severe parameter explosion and limited ability to capture…