arXiv Machine Learning
Jul 10
Holographic Neural PCFG for Unsupervised Parsing
arXiv:2607. 08063v1 Announce Type: cross Abstract: Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone.
Holographic Neural PCFG for Unsupervised Parsing
Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone. Recent neural parameterizations of PCFGs achieve strong performance in both supervised and unsupervised parsing, yet rely on high-capacity black-box networks for rule scoring -- as exemplified by the Neural PCFG family -- leaving rule probabilities without an interpretable mathematical form.
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arXiv Machine Learning
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arXiv Machine Learning
Aug 4
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arXiv AI
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Hugging Face Trending Papers
Jul 22
Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning
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arXiv Machine Learning
Jun 16
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arXiv AI
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From Dependency to Compositionality: A Neurosymbolic Lifting of LLM Outputs via Combinatory Categorial Grammar
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TokEval: A Tokenizer Evaluation Suite
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