Feb. 20, 2024, 5:52 a.m. | Alexis Chevalier, Jiayi Geng, Alexander Wettig, Howard Chen, Sebastian Mizera, Toni Annala, Max Jameson Aragon, Arturo Rodr\'iguez Fanlo, Simon Friede

cs.CL updates on arXiv.org arxiv.org

arXiv:2402.11111v1 Announce Type: cross
Abstract: NLP has recently made exciting progress toward training language models (LMs) with strong scientific problem-solving skills. However, model development has not focused on real-life use-cases of LMs for science, including applications in education that require processing long scientific documents. To address this, we introduce TutorEval and TutorChat. TutorEval is a diverse question-answering benchmark consisting of questions about long chapters from STEM textbooks, written by experts. TutorEval helps measure real-life usability of LMs as scientific assistants, …

abstract applications arxiv cases cs.ai cs.cl development documents education language language models life lms model development nlp problem-solving processing progress science skills training type

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