{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:38:36Z","timestamp":1761176316207,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Current deep learning-based activity recognition and anticipation approaches struggle with unlabeled datasets and the lack of commonsense knowledge about previously unseen objects, i.e., unknown objects. This paper proposes a neurosymbolic framework that combines context recognition, incremental learning, and commonsense reasoning to anticipate activities from egocentric vision, while accounting for perceptual uncertainty and the incompleteness of real-world commonsense knowledge. The incremental learning component leverages language models, while Bayesian reasoning enables continuous updates to an ontological knowledge graph with class and affordance descriptions of these unknown objects. These descriptions are derived from visual feature embeddings extracted using a transformer and enriched with knowledge from various multi-modal large language models (MLLMs). Event calculus and answer set programming are used to formalize domain knowledge, enabling probabilistic symbolic reasoning over contextual events to support the prediction of user intentions and the anticipation of both simple and complex activities. A prototype has been tested in a domestic environment using images captured from a head-mounted camera and real-time object and context event detection.<\/jats:p>","DOI":"10.3233\/faia251451","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:03:26Z","timestamp":1761127406000},"source":"Crossref","is-referenced-by-count":0,"title":["Neuro-Symbolic Framework Integrating Incremental Learning with LLM and Symbolic Reasoning on Unknown Objects"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2525-1597","authenticated-orcid":false,"given":"Imad Eddine","family":"Kenai","sequence":"first","affiliation":[{"name":"LISSI Lab, University of Paris-Est Cr\u00e9teil, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7122-1271","authenticated-orcid":false,"given":"Abdelghani","family":"Chibani","sequence":"additional","affiliation":[{"name":"LISSI Lab, University of Paris-Est Cr\u00e9teil, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1668-7620","authenticated-orcid":false,"given":"Ferhat","family":"Attal","sequence":"additional","affiliation":[{"name":"LISSI Lab, University of Paris-Est Cr\u00e9teil, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5760-8556","authenticated-orcid":false,"given":"Ilies","family":"Chibane","sequence":"additional","affiliation":[{"name":"LISSI Lab, University of Paris-Est Cr\u00e9teil, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3238-0517","authenticated-orcid":false,"given":"Yacine","family":"Amirat","sequence":"additional","affiliation":[{"name":"LISSI Lab, University of Paris-Est Cr\u00e9teil, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251451","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:03:26Z","timestamp":1761127406000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251451"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251451","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}