Hugging Face Trending Papers July 22, 2026

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning

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This paper introduces Sentence Splitter, a self-supervised framework built upon a T5-based encoder--decoder architecture for uncovering the latent factual structure of natural language sentences. The proposed method identifies the semantic boundary between a descriptive prefix (head) and its factual completion (tail) by formulating sentence splitting as a discrete segmentation problem, where a sentence of length $N$ admits $N$ possible split points but only one recovers the intended head--tail structure.

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Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning

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