Výsledky vyhledávání - "Iulian Vlad Serban"

Periodical

IULIAN VLAD SERBAN PRÉSENTE SA PLATEFORME D’APPRENTISSAGE KORBIT AI. (French)

Autor: Morriet, Oriane

Publikováno v: Convergence Magazine; jul2021, Issue 175, p62-63, 2p, 1 Color Photograph

Few-Shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems

Autor: Devang Kulshreshtha, Muhammad Shayan, Robert Belfer, Siva Reddy, Iulian Vlad Serban, Ekaterina Kochmar

Existing work on generating hints in Intelligent Tutoring Systems (ITS) focuses mostly on manual and non-personalized feedback. In this work, we explore automatically generated questions as personalized feedback in an ITS. Our personalized feedback c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::81c11c4b499b52e0a77230a65fa4ac64
https://doi.org/10.3233/faia220062

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Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems

Autor: Dung Do Vu, Iulian Vlad Serban, Ekaterina Kochmar, Robert Belfer, Varun Gupta, Joelle Pineau

Publikováno v: Kochmar, E, Vu, D D, Belfer, R, Gupta, V, Serban, I V & Pineau, J 2021, ' Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems ', International Journal of Artificial Intelligence in Education . https://doi.org/10.1007/s40593-021-00267-x

Intelligent tutoring systems (ITS) have been shown to be highly effective at promoting learning as compared to other computer-based instructional approaches. However, many ITS rely heavily on expert design and hand-crafted rules. This makes them diff

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c32c8305f3b45de1f5333a7e4fabb53d
https://purehost.bath.ac.uk/ws/files/221784481/AIED_journal_final.pdf

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A Comparative Study of Learning Outcomes for Online Learning Platforms

Autor: Ekaterina Kochmar, Laurent Charlin, Ansona Onyi Ching, Ariella Smofsky, Farid Faraji, Adela Matajova, Iulian Vlad Serban, Anush Stepanyan, Robert Belfer, Yoshua Bengio, Sabina Elkins, Muhammad Shayan, Vincent Pavero, Nathan Burns, Dung Do Vu, François St-Hilaire, Antoine Frau, Neroli Ko, Joseph Potochny

Publikováno v: St-Hilaire, F, Burns, N, Belfer, R, Shayan, M, Smofsky, A, Vu, D D, Frau, A, Potochny, J, Faraji, F, Pavero, V, Ko, N, Ching, A O, Elkins, S, Stepanyan, A, Matajova, A, Charlin, L, Bengio, Y, Serban, I V & Kochmar, E 2021, ' A Comparative Study of Learning Outcomes for Online Learning Platforms ', Paper presented at The 2021 conference on Artificial Intelligence in Education, Utrecht, Netherlands, 14/06/21-18/06/21 .
Lecture Notes in Computer Science ISBN: 9783030782696
AIED (2)

Personalization and active learning help educational systems to close the gap between students with varying abilities. We run a comparative head-to-head study of learning outcomes for two popular online platforms: Platform A, which delivers content o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d221bedce6209909921af1851e63899c
https://purehost.bath.ac.uk/ws/files/219767691/paper_195.pdf

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A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM

Autor: Iulian Vlad Serban, Aaron Courville, Dung Do Vu, Robert Belfer, Joelle Pineau, Ekaterina Kochmar, Laurent Charlin, Varun Gupta, Yoshua Bengio

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030522391
AIED (2)
Artificial Intelligence in Education

We present Korbit, a large-scale, open-domain, mixed-interface, dialogue-based intelligent tutoring system (ITS). Korbit uses machine learning, natural language processing and reinforcement learning to provide interactive, personalized learning onlin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62024e826ae4b12a22850012753fc19e

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Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System

Autor: Joelle Pineau, Dung Do Vu, Varun Gupta, Iulian Vlad Serban, Robert Belfer, Ekaterina Kochmar

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030522391
AIED (2)

We investigate how automated, data-driven, personalized feedback in a large-scale intelligent tutoring system (ITS) improves student learning outcomes. We propose a machine learning approach to generate personalized feedback, which takes individual n

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2ea996cdb60f26e5685628245a0fd4ba
https://doi.org/10.1007/978-3-030-52240-7_26

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A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version

Autor: Peter Henderson, Joelle Pineau, Laurent Charlin, Iulian Vlad Serban, Ryan Lowe

Publikováno v: Dialogue & Discourse. 9:1-49

During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical systems are still b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ba81a28ea6570240560426eae3c2c746
https://doi.org/10.5087/dad.2018.101

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Training End-to-End Dialogue Systems with the Ubuntu Dialogue Corpus

Autor: Ryan Lowe, Laurent Charlin, Iulian Vlad Serban, Chia-Wei Liu, Nissan Pow, Joelle Pineau

Publikováno v: Dialogue & Discourse. 8:31-65

In this paper, we construct and train end-to-end neural network-based dialogue systems usingan updated version of the recent Ubuntu Dialogue Corpus, a dataset containing almost 1 million multi-turn dialogues, with a total of over 7 million utterances

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::81e9b318bf0af35d2b779d18ad32e2e6
https://doi.org/10.5087/dad.2017.102

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The Second Conversational Intelligence Challenge (ConvAI2)

Autor: Shrimai Prabhumoye, Ryan Lowe, Kurt Shuster, Joelle Pineau, Alexander H. Miller, Emily Dinan, Douwe Kiela, Jack Urbanek, Iulian Vlad Serban, Valentin Malykh, Arthur Szlam, Alexander I. Rudnicky, Varvara Logacheva, Mikhail S. Burtsev, Jason D. Williams, Jason Weston, Alan W. Black

Publikováno v: The NeurIPS '18 Competition ISBN: 9783030291341

We describe the setting and results of the ConvAI2 NeurIPS competition that aims to further the state-of-the-art in open-domain chatbots. Some key takeaways from the competition are: (1) pretrained Transformer variants are currently the best performi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::baea3ac4d285aa0d6565323f702a3437
https://doi.org/10.1007/978-3-030-29135-8_7

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