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ml:graphical_models

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ml:graphical_models [2023/08/31 22:41] – [Recent NLP Papers that Use PGMs] jmflanigml:graphical_models [2025/05/03 01:43] (current) – [Interesting NLP Deep Learning + PGM Papers] jmflanig
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   * [[https://arxiv.org/pdf/2106.02736.pdf|Goyal et al 2021 - Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis–Hastings]]   * [[https://arxiv.org/pdf/2106.02736.pdf|Goyal et al 2021 - Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis–Hastings]]
   * [[https://arxiv.org/pdf/2105.15021.pdf|Yang et al 2021 - Neural Bi-Lexicalized PCFG Induction]] Uses a Bayesian network to describe their model   * [[https://arxiv.org/pdf/2105.15021.pdf|Yang et al 2021 - Neural Bi-Lexicalized PCFG Induction]] Uses a Bayesian network to describe their model
 +  * [[https://arxiv.org/pdf/2406.06950|Hou et al 2024 - A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation]]
  
 ===== Recent NLP Papers that Use PGMs ==== ===== Recent NLP Papers that Use PGMs ====
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   * Sometimes PGMS are covered in the UCSC course [[https://courses.soe.ucsc.edu/courses/cse290c|CSE 290C]] (when [[https://courses.soe.ucsc.edu/courses/cmps290c/Fall15/01|Lisa Geetoor teaches it]])   * Sometimes PGMS are covered in the UCSC course [[https://courses.soe.ucsc.edu/courses/cse290c|CSE 290C]] (when [[https://courses.soe.ucsc.edu/courses/cmps290c/Fall15/01|Lisa Geetoor teaches it]])
   * **Course at CMU**: Probabilistic Graphical Models [[https://www.cs.cmu.edu/~epxing/Class/10708-20/index.html|Spring 2020]] [[https://www.cs.cmu.edu/~epxing/Class/10708-20/lectures.html|Lectures with videos]] [[https://www.cs.cmu.edu/~epxing/Class/10708/|2014 (with videos and scribe notes)]]   * **Course at CMU**: Probabilistic Graphical Models [[https://www.cs.cmu.edu/~epxing/Class/10708-20/index.html|Spring 2020]] [[https://www.cs.cmu.edu/~epxing/Class/10708-20/lectures.html|Lectures with videos]] [[https://www.cs.cmu.edu/~epxing/Class/10708/|2014 (with videos and scribe notes)]]
 +  * Stanford course: [[https://ermongroup.github.io/cs228/|CS 228 - Probabilistic Graphical Models]]
   * **Matt Gormley's course at CMU**: [[https://www.cs.cmu.edu/~mgormley/courses/10418/|10418]] (with videos)   * **Matt Gormley's course at CMU**: [[https://www.cs.cmu.edu/~mgormley/courses/10418/|10418]] (with videos)
   * **Best overview tutorial:** [[https://kuleshov.github.io/cs228-notes/|CS228 Lecture Notes]]   * **Best overview tutorial:** [[https://kuleshov.github.io/cs228-notes/|CS228 Lecture Notes]]
ml/graphical_models.1693521668.txt.gz · Last modified: 2023/08/31 22:41 by jmflanig
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