9 citations · 42 across the 36 of their papers we have counts for
7 papers · 1 filter
Exploring Concept Subspace for Self-explainable Text-Attributed Graph Learning
Xiaoxue Han, Libo Zhang, Zining Zhu +1
We introduce Graph Concept Bottleneck (GCB) as a new paradigm for self-explainable text-attributed graph learning. GCB maps graphs into a subspace, concept bottleneck, where each c…
The Illusion of Specialization: Unveiling the Domain-Invariant "Standing Committee" in Mixture-of-Experts Models
Yan Wang, Yitao Xu, Nanhan Shen +3
Mixture of Experts models are widely assumed to achieve domain specialization through sparse routing. In this work, we question this assumption by introducing COMMITTEEAUDIT, a pos…
Feature-Guided SAE Steering for Refusal-Rate Control using Contrasting Prompts
Samaksh Bhargav, Zining Zhu
Large Language Model (LLM) deployment requires guiding the LLM to recognize and not answer unsafe prompts while complying with safe prompts. Previous methods for achieving this req…
KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning
Zhendong Mi, Qitao Tan, Xiaodong Yu +3
Large language models (LLMs) have demonstrated impressive capabilities across numerous NLP tasks. Nevertheless, conventional first-order fine-tuning techniques impose heavy memory…
OOD-Probe: A Neural Interpretation of Out-of-Domain Generalization
Zining Zhu, Soroosh Shahtalebi, Frank Rudzicz
The ability to generalize out-of-domain (OOD) is an important goal for deep neural network development, and researchers have proposed many high-performing OOD generalization method…
Robustness against the channel effect in pathological voice detection
Yi-Te Hsu, Zining Zhu, Chi-Te Wang +3
Many people are suffering from voice disorders, which can adversely affect the quality of their lives. In response, some researchers have proposed algorithms for automatic assessme…
Semi-supervised classification by reaching consensus among modalities
Zining Zhu, Jekaterina Novikova, Frank Rudzicz
Deep learning has demonstrated abilities to learn complex structures, but they can be restricted by available data. Recently, Consensus Networks (CNs) were proposed to alleviate da…