6 papers
Calibrating Post-Training Feature Shifts for LLM Data Contamination Detection
Zhen Yang, Mengqi Wang, Gengda Zhao +3
Large language models (LLMs) are trained on massive and largely undisclosed corpora that may contain copyrighted or privacy-sensitive content. Data contamination detection (DCD) th…
Interpretable Column Annotation with LLM-Symbolized Decision Process Materialization
Mengqi Wang, Jianwei Wang, Qing Liu +5
Column annotation (CA), including column type annotation (CTA) and column property annotation (CPA), aims to identify the meanings of table columns and the semantic relationships a…
Audio-Conditioned Diffusion LLMs for ASR and Deliberation Processing
Mengqi Wang, Zhan Liu, Zengrui Jin +3
Diffusion-based large language models (DLLMs) have recently attracted growing interest as an alternative to autoregressive decoders. In this work, we present an empirical study on…
Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection
Mengqi Wang, Jianwei Wang, Qing Liu +5
Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent state-of-the-art ED methods lever…
How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models?
Mengqi Wang, Tiantian Feng, Shrikanth Narayanan
Large language models (LLMs) have enabled a wide variety of real-world applications in various domains. However, creating a high-performing application with high accuracy remains c…
LLM-based HSE Compliance Assessment: Benchmark, Performance, and Advancements
Jianwei Wang, Mengqi Wang, Yinsi Zhou +5
Health, Safety, and Environment (HSE) compliance assessment demands dynamic real-time decision-making under complicated regulations and complex human-machine-environment interactio…