5 citations · 5 across the 5 of their papers we have counts for
7 papers
Evaluating the Ability of Explanations to Disambiguate Models in a Rashomon Set
Kaivalya Rawal, Eoin Delaney, Zihao Fu +2
Explainable artificial intelligence (XAI) is concerned with producing explanations indicating the inner workings of models. For a Rashomon set of similarly performing models, expla…
SCALPEL: Selective Capability Ablation via Low-rank Parameter Editing for Large Language Model Interpretability Analysis
Zihao Fu, Xufeng Duan, Zhenguang G. Cai
Large language models excel across diverse domains, yet their deployment in healthcare, legal systems, and autonomous decision-making remains limited by incomplete understanding of…
OxEnsemble: Fair Ensembles for Low-Data Classification
Jonathan Rystrøm, Zihao Fu, Chris Russell
We address the problem of fair classification in settings where data is scarce and unbalanced across demographic groups. Such low-data regimes are common in domains like medical im…
FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models
Zihao Fu, Ryan Brown, Shun Shao +3
Text-to-image diffusion models, such as Stable Diffusion, have demonstrated remarkable capabilities in generating high-quality and diverse images from natural language prompts. How…
CAST: Compositional Analysis via Spectral Tracking for Understanding Transformer Layer Functions
Zihao Fu, Ming Liao, Chris Russell +1
Large language models have achieved remarkable success but remain largely black boxes with poorly understood internal mechanisms. To address this limitation, many researchers have…
Multi-use LLM Watermarking and the False Detection Problem
Zihao Fu, Chris Russell
Digital watermarking is a promising solution for mitigating some of the risks arising from the misuse of automatically generated text. These approaches either embed non-specific wa…