2 citations · 2 across the 7 of their papers we have counts for
7 papers
Conformal Privacy Auditing: Calibrated Re-identification Attacks with Statistical Guarantees
Shuo Huang, Gholamreza Haffari, Xingliang Yuan +2
Empirical identity leakage from released text is increasingly driven by attackers that combine large language models (LLMs) with auxiliary knowledge to link documents to individual…
TAB-AUDIT: Detecting AI-Fabricated Scientific Tables via Multi-View Likelihood Mismatch
Shuo Huang, Yan Pen, Lizhen Qu
AI-generated fabricated scientific manuscripts raise growing concerns with large-scale breaches of academic integrity. In this work, we present the first systematic study on detect…
Zero-Shot Privacy-Aware Text Rewriting via Iterative Tree Search
Shuo Huang, Xingliang Yuan, Gholamreza Haffari +1
The increasing adoption of large language models (LLMs) in cloud-based services has raised significant privacy concerns, as user inputs may inadvertently expose sensitive informati…
Causal Discovery Inspired Unsupervised Domain Adaptation for Emotion-Cause Pair Extraction
Yuncheng Hua, Yujin Huang, Shuo Huang +5
This paper tackles the task of emotion-cause pair extraction in the unsupervised domain adaptation setting. The problem is challenging as the distributions of the events causing em…
NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human
Shuo Huang, William MacLean, Xiaoxi Kang +5
The widespread use of cloud-based Large Language Models (LLMs) has heightened concerns over user privacy, as sensitive information may be inadvertently exposed during interactions…
On Robustness of Neural Semantic Parsers
Shuo Huang, Zhuang Li, Lizhen Qu +1
Semantic parsing maps natural language (NL) utterances into logical forms (LFs), which underpins many advanced NLP problems. Semantic parsers gain performance boosts with deep neur…
Few-Shot Semantic Parsing for New Predicates
Zhuang Li, Lizhen Qu, Shuo Huang +1
In this work, we investigate the problems of semantic parsing in a few-shot learning setting. In this setting, we are provided with utterance-logical form pairs per new predicate.…