From Large Language Models to Small Logic Programs: Building Global Explanations from Disagreeing Local Post-hoc Explainers
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articleno = 32,
author = {Agiollo, Andrea and Siebert, Luciano Cavalcante and Murukannaiah, Pradeep Kumar and Omicini, Andrea},
dblp = {journals/aamas/AgiolloSMO24},
doi = {10.1007/s10458-024-09663-8},
iris = {11585/973894},
journal = {Autonomous Agents and Multi-Agent Systems},
keywords = {Natural language processing, post-hoc explanations, symbolic knowledge extraction, eXplainable AI, resource-friendly AI},
month = jul,
note = {Special Issue on Multi-Agent Systems and Explainable AI},
numpages = 33,
pages = {1--33},
publisher = {Springer},
scholar = {13114388339509722903},
scopus = {2-s2.0-85197706028},
title = {From Large Language Models to Small Logic Programs: Building Global Explanations from Disagreeing Local Post-hoc Explainers},
url = {http://link.springer.com/10.1007/s10458-024-09663-8},
urlopenaccess = {https://link.springer.com/content/pdf/10.1007/s10458-024-09663-8.pdf},
urlpdf = {https://link.springer.com/content/pdf/10.1007/s10458-024-09663-8.pdf},
volume = 38,
wos = {WOS:001264787900001},
year = 2024
}