Robust Detection of Machine-Generated Text Across Diverse Generators and Domains
Existing methods for detecting machine-generated text face severe limitations in generalizing to diverse generators and domains in real-world scenarios. This work introduces T5LLMCipher, a novel system that leverages the embeddings from LLM encoders to robustly detect and attribute machine-generated text, outperforming state-of-the-art approaches.
Investigating Text Shortening Strategy in BERT: Truncation vs Summarization
Summarization outperforms truncation in text classification tasks, with the best strategy being taking the head of the document.
Analyzing Claim Decomposition Methods for Textual Support Evaluation
Claim decomposition methods significantly impact the evaluation of textual support metrics.
Improving Authorship Verification with Synthetic Examples
Augmenting training sets with synthetic examples for authorship verification may not consistently improve classifier performance.
Arabic Text Sentiment Analysis: Challenges and Solutions Explored
This study delves into the challenges and solutions of Arabic sentiment analysis, highlighting the need for improved tools and resources in this field.
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