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Cho-Yu Jason Chiang

3 accepted papers

2026

AdvBDGen: A Robust Framework for Generating Adaptive and Stealthy Backdoors in LLM Alignment

AAAI 2026technical

With the increasing adoption of reinforcement learning with human feedback (RLHF) to align large language models (LLMs), the risk of backdoor installation during the alignment process has grown, potentially leading to unintended and harmful behaviors. Existing backdoor attacks mostly focus on simple

Cited by 0SourcePDFScholar
2025

Reflective Agreement: Combining Self-Mixture of Agents with a Sequence Tagger for Robust Event Extraction

EMNLP 2025

Event Extraction (EE) involves automatically identifying and extracting structured information about events from unstructured text, including triggers, event types, and arguments. Traditional discriminative models demonstrate high precision but often exhibit limited recall, particularly for nuanced

Cited by 0SourcePDFScholar
2021

Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions

ICML 2021spotlight

Generative adversarial networks (GANs) are often billed as "universal distribution learners", but precisely what distributions they can represent and learn is still an open question. Heavy-tailed distributions are prevalent in many different domains such as financial risk-assessment, physics, and ep…