3 citations · 5 across the 8 of their papers we have counts for
4 papers · 1 filter
A One-Layer Decoder-Only Transformer is a Two-Layer RNN: With an Application to Certified Robustness
Yuhao Zhang, Aws Albarghouthi, Loris D'Antoni
This paper reveals a key insight that a one-layer decoder-only Transformer is equivalent to a two-layer Recurrent Neural Network (RNN). Building on this insight, we propose ARC-Tra…
CodeFort: Robust Training for Code Generation Models
Yuhao Zhang, Shiqi Wang, Haifeng Qian +8
Code generation models are not robust to small perturbations, which often lead to incorrect generations and significantly degrade the performance of these models. Although improvin…
Ensuring Safe and High-Quality Outputs: A Guideline Library Approach for Language Models
Yi Luo, Zhenghao Lin, Yuhao Zhang +7
Large Language Models (LLMs) exhibit impressive capabilities but also present risks such as biased content generation and privacy issues. One of the current alignment techniques in…
Verified Training for Counterfactual Explanation Robustness under Data Shift
Anna P. Meyer, Yuhao Zhang, Aws Albarghouthi +1
Counterfactual explanations (CEs) enhance the interpretability of machine learning models by describing what changes to an input are necessary to change its prediction to a desired…