NLPExplorer

CoNLL - 2023

Total Papers:- 74

Total Papers accross all years:- 1554

Total Citations :- 0

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Pre-training LLMs using human-like development data corpus

Khushi Bhardwaj | Raj Sanjay Shah | Sashank Varma |

Future Lens: Anticipating Subsequent Tokens from a Single Hidden State

A Comparative Study on Textual Saliency of Styles from Eye Tracking, Annotations, and Language Models

Karin de Langis | Dongyeop Kang |

Strategies to Improve Low-Resource Agglutinative Languages Morphological Inflection

Optimizing GPT-2 Pretraining on BabyLM Corpus with Difficulty-based Sentence Reordering

Nasim Borazjanizadeh |

Exploring Transformers as Compact, Data-efficient Language Models

Clayton Fields | Casey Kennington |

On the Effects of Structural Modeling for Neural Semantic Parsing

Xiang Zhang | Shizhu He | Kang Liu | Jun Zhao |

A Block Metropolis-Hastings Sampler for Controllable Energy-based Text Generation

Jarad Forristal | Fatemehsadat Mireshghallah | Greg Durrett | Taylor Berg-Kirkpatrick |

Syntactic Inductive Bias in Transformer Language Models: Especially Helpful for Low-Resource Languages?

Luke Gessler | Nathan Schneider |

Humans and language models diverge when predicting repeating text

Aditya Vaidya | Javier Turek | Alexander Huth |

JaSPICE: Automatic Evaluation Metric Using Predicate-Argument Structures for Image Captioning Models

Yuiga Wada | Kanta Kaneda | Komei Sugiura |

How Fragile is Relation Extraction under Entity Replacements?

Grammar induction pretraining for language modeling in low resource contexts

Xuanda Chen | Eva Portelance |

Challenging the “One Single Vector per Token” Assumption

Mathieu Dehouck |

Tiny Language Models Enriched with Multimodal Knowledge from Multiplex Networks