NLPExplorer

BEA - 2024

Total Papers:- 59

Total Papers accross all years:- 437

Total Citations :- 0

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Item Difficulty and Response Time Prediction with Large Language Models: An Empirical Analysis of USMLE Items

Okan Bulut | Guher Gorgun | Bin Tan |

Using Machine Learning to Predict Item Difficulty and Response Time in Medical Tests

Mehrdad Yousefpoori-Naeim | Shayan Zargari | Zahra Hatami |

ANU at MLSP-2024: Prompt-based Lexical Simplification for English and Sinhala

Sandaru Seneviratne | Hanna Suominen |

UPN-ICC at BEA 2024 Shared Task: Leveraging LLMs for Multiple-Choice Questions Difficulty Prediction

George Duenas | Sergio Jimenez | Geral Mateus Ferro |

Explainable AI in Language Learning: Linking Empirical Evidence and Theoretical Concepts in Proficiency and Readability Modeling of Portuguese

Luisa Ribeiro-Flucht | Xiaobin Chen | Detmar Meurers |

Can GPT-4 do L2 analytic assessment?

Stefano Banno | Hari Krishna Vydana | Kate Knill | Mark Gales |

Automatic Crossword Clues Extraction for Language Learning

Identifying Fairness Issues in Automatically Generated Testing Content

Kevin Stowe |

Evaluating Vocabulary Usage in LLMs

Matthew Durward | Christopher Thomson |

Findings from the First Shared Task on Automated Prediction of Difficulty and Response Time for Multiple-Choice Questions

Using Adaptive Empathetic Responses for Teaching English

Li Siyan | Teresa Shao | Julia Hirschberg | Zhou Yu |

The BEA 2024 Shared Task on the Multilingual Lexical Simplification Pipeline

Automated Essay Scoring Using Grammatical Variety and Errors with Multi-Task Learning and Item Response Theory

Kosuke Doi | Katsuhito Sudoh | Satoshi Nakamura |

TMU-HIT at MLSP 2024: How Well Can GPT-4 Tackle Multilingual Lexical Simplification?