Getting from Generative AI to Trustworthy AI: What LLMs might learn from Cyc

Autor: Lenat, Doug, Marcus, Gary

Generative AI, the most popular current approach to AI, consists of large language models (LLMs) that are trained to produce outputs that are plausible, but not necessarily correct. Although their abilities are often uncanny, they are lacking in aspe

Externí odkaz: http://arxiv.org/abs/2308.04445

Learning profile-based recommendations for medical search auto-complete

Autor: Boomgaard, Guusje, Santamaría, Selene Báez, Tiddi, Ilaria, Sips, Robert Jan, Szlávik, Zoltán, Martin, Andreas, Hinkelmann, Knut, Fill, Hans-Georg, Gerber, Aurona, Lenat, Doug, Stolle, Reinhard, van Harmelen, Frank

Publikováno v: AAAI-MAKE 2021 Combining Machine Learning and Knowledge Engineering: Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021) Stanford University, Palo Alto, California, USA, March 22-24, 2021, 1-13
STARTPAGE=1;ENDPAGE=13;TITLE=AAAI-MAKE 2021 Combining Machine Learning and Knowledge Engineering

Query popularity is a main feature in web-search auto-completion. Several personalization features have been proposed to support specific users' searches, but often do not meet the privacy requirements of a medical environment (e.g. clinical trial se

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::1e241b62b01ae9f58c8b61edafa8b081
https://research.vu.nl/en/publications/44fdca3c-d96e-4591-8297-8f6588800b83

Mitigating bias in deep nets with knowledge bases: The case of natural language understanding for robots

Autor: Mensio, Martino, Bastianelli, Emanuele, Tiddi, Ilaria, Rizzo, Giuseppe, Martin, Andreas, Hinkelmann, Knut, Fill, Hans-Georg, Gerber, Aurona, Lenat, Doug, Stolle, Reinhard, van Harmelen, Frank

Publikováno v: AAAI-MAKE 2020 Combining Machine Learning and Knowledge Engineering in Practice-Volume I: Spring Symposium: Proceedings of the AAAI 2020 Spring Symposium on Combining Machine Learning and Knowledge Engineering in Practice (AAAI-MAKE 2020)-Volume I Stanford University, Palo Alto, California, USA, March 23-25, 2020, 1, 1-9

In this paper, we tackle the problem of lack of understandability of deep learning systems by integrating heterogeneous knowledge sources, and in the specific we present how we used FrameNet to guarantee the correct learning for an LSTM-based semanti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::7e4fd3c72c45a8c3fe6e50547ac32a37
https://research.vu.nl/en/publications/28a90763-af67-43e0-b564-e5b65ac84de5

Preface:Combining machine learning with knowledge engineering (AAAI-Make 2019)

Autor: Martin, Andreas, Hinkelmann, Knut, Gerber, Aurona, Lenat, Doug, van Harmelen, Frank, Clark, Peter

Publikováno v: Martin, A, Hinkelmann, K, Gerber, A, Lenat, D, van Harmelen, F & Clark, P 2019, Preface : Combining machine learning with knowledge engineering (AAAI-Make 2019) . in A Martin (ed.), AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering : Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019). Stanford University, Palo Alto, California, USA, March 25-27, 2019 . CEUR Workshop Proceedings, vol. 2350, CEUR-WS, 2019 AAAI Spring Symposium on Combining Machine Learning with Knowledge Engineering, AAAI-MAKE 2019, Palo Alto, United States, 25/03/19 . < http://ceur-ws.org/Vol-2350/xpreface.pdf >

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______4612::e31b5d228fb98d5dd33b13acaeb39cad
https://hdl.handle.net/1871.1/0a31abcf-fd8e-4ab2-a6b8-f6e42ecb9002

Large-scale Knowledge Representation Resources for Cognitive Science Research

Autor: Miller, George A., Fillmore, Charles J., Palmer, Martha S., Lenat, Doug, Hayes, Pat

Publikováno v: Miller, George A.; Fillmore, Charles J.; Palmer, Martha S.; Lenat, Doug; & Hayes, Pat. (2004). Large-scale Knowledge Representation Resources for Cognitive Science Research. Proceedings of the Cognitive Science Society, 26(26). Retrieved from: http://www.escholarship.org/uc/item/1px3c3tj

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______325::dab9ec8d43f30ff22aff48e952c80efc
http://www.escholarship.org/uc/item/1px3c3tj