Releases a large real-world dataset of dirty postal addresses with ground truth for benchmarking data cleaning algorithms.
Detecting Personal Information in Training Corpora: an Analysis
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
representative citing papers
The paper constructs an SCPI dataset via LLM-based annotation and trains classifiers to detect sensitive personal information in Japanese pre-training corpora, claiming this is the first such exploration.
LLMs outperform humans in expressing illocutionary intents and sycophancy in successful persuasive counter-arguments from ChangeMyView, with crowd workers preferring LLM versions.
A survey that compiles and taxonomizes more than 32 existing hallucination mitigation techniques for LLMs while analyzing their challenges and limitations.
citing papers explorer
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A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models
A survey that compiles and taxonomizes more than 32 existing hallucination mitigation techniques for LLMs while analyzing their challenges and limitations.