collaborators

5 papers

cs.SE2026

ConcoLixir: Reactive LLM Discovery Oracles for Python Concolic Testing

Dong Chen, Chih-Duo Hong, Fang Yu

Concolic testing combines concrete execution with symbolic constraint solving, but Python programs expose recurring limits. Library calls can cause symbolic variables to downgrade…

cs.LG2026

Signature filtering: a lightweight enhancement for statistical watermark detection in large language models

Chih-Duo Hong, Yen-Pang Chen, Fang Yu

Statistical watermarks help organizations attribute large language model (LLM) outputs, yet existing detectors often struggle when watermark signals are weak, texts are repetitive,…

cs.CR2026

OTTER: A Red-Teaming System for Toxicity-Evading Jailbreak Prompt Optimization

Jerry Wang, Hsin-Ling Hsu, Yi-Cheng Lai +2

Production LLMs increasingly rely on toxicity-based moderation filters as a primary defense, assuming that harmful intent correlates with toxic surface wording. We show this assump…

cs.LG2026

WARP: Guaranteed Inner-Layer Repair of NLP Transformers

Hsin-Ling Hsu, Min-Yu Chen, Nai-Chia Chen +3

Transformer-based NLP models remain vulnerable to adversarial perturbations, yet existing repair methods face a fundamental trade-off: gradient-based approaches offer flexibility b…

cs.LG2025

Concolic Testing on Individual Fairness of Neural Network Models

Ming-I Huang, Chih-Duo Hong, Fang Yu

This paper introduces PyFair, a formal framework for evaluating and verifying individual fairness of Deep Neural Networks (DNNs). By adapting the concolic testing tool PyCT, we gen…