Feng Xia
@fxia61
Artificial Intelligence, Brain, Robotics. Professor @RMIT.
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Professor Richard Robson wins Nobel Prize in Chemistry unimelb.edu.au/newsroom/news/…
Submit your best work and join us in advancing the state of the art in Semantics and Knowledge at The Web Conference 2026 (#WWW 2026). 🔗 For details and submission guidelines: www2026.thewebconf.org/calls/research… #CallForPapers #Knowledge #Graphs #Semantics #Research #AI #Web #Conference
We have one #PhD position with scholarships in the BITS (#India) - #RMIT joint PhD program now open for applications! Project ID: BITSRMIT24101183 📌 To learn more and apply, please visit: tinyurl.com/yj3tw8yv #PhDopportunity #Scholarship #AI #Research #emotion #robot
CALL FOR PAPERS IEEE Transactions on Cognitive and Developmental Systems Special Issue on Neuromorphic Computing in the Age of Foundation Models PDF: cis.ieee.org/images/files/D… Submission Deadline: Dec 31, 2025 #brain #neuralnetworks #AI #foundationmodel #computing #cfp #llm
Man speaks again in medical-first brain implant breakthrough msn.com/en-au/health/m…
We welcome you to submit your papers and participate in CSoNet 2025. csonet-conf.github.io #CFP #Conference #papers #SocialNetworks #BigData #NetworkScience #AI #GraphLearning
Honoured to receive Springer Nature Editor of Distinction Awards 2025: both Editorial Contribution Award and Author Service Award. Thank you to @SpringerNature for this recognition, and congrats to all editors honoured this year! #AcademicPublishing #Editor #PeerReview #Award
Mark a wrap on 2025 Semester 1 teaching! A huge cohort of 600+ students, countless questions, brilliant guest lectures, and fantastic tutors — thank you all for making it another amazing semester! #Teaching #Students #Gratitude #AI #DataScience #HigherEd #ThankYou
"CaGE: A Causality-inspired Graph Neural Network Explainer for Recommender Systems" by Shuo Yu, Yicong Li, Shuo Wang, Tao Tang, Qiang Zhang, Jingjing Zhou, Ivan Lee, and Feng Xia got accepted in ACM TOIS (just accept).
This work is being presented at #WWW2025. Check it out. HALO: Half Life-Based Outdated Fact Filtering in Temporal Knowledge Graphs Code: github.com/yushuowiki/K-H… Day 4 - Thursday, 1 May 2025 Oral: C2.6, 10:30 - 12:00 #Web #AI #knowledgegraph #fact #filtering #datascience
This work is being presented at #WWW2025. Check it out. EmoMeta: A Multimodal Dataset for Fine-grained Emotion Classification in Chinese Metaphors Thursday, 1 May 2025 Oral: C2.6, 10:30 - 12:00 #Web #AI #Emotion #Metaphor #Classification #dataset #Multimodal
This work is being presented at #WWW2025. Towards Better Evaluation of Recommendation Algorithms with Bi-directional Item Response Theory iron13.github.io/paper/BiReIRT.… Thursday, 1 May 2025 Poster: Parkside Ballroom, 1pm #Web #AI #RecommenderSystems #evaluation #metric #dataset
This work is being presented at #WWW2025. Wednesday, 30 April Poster: Parkside Ballroom, 12.30pm #AI #KnowledgeTracing #cognitivecomputing #attention #education Enhancing Knowledge Tracing through Decoupling Cognitive Pattern from Error-Prone Data dl.acm.org/doi/10.1145/36…
This work is being presented at #WWW2025. paper ID: 1731. Friday, 2 May 2025. Oral: C3.6, 10.30am Poster: Parkside Ballroom, 2pm #Web #AI #Graph #matrix #GraphLearning #Clustering Revisiting Dynamic Graph Clustering via Matrix Factorization dl.acm.org/doi/10.1145/36…
This work is being presented at #WWW2025, on Thursday, 1 May 2025. Oral (C3.6, 2.30pm; ID: 1828) + Poster (Parkside Ballroom, 4.30pm). Check it out. SEHG: Bridging Interpretability and Prediction in Self-Explainable Heterogeneous Graph Neural Networks dl.acm.org/doi/10.1145/36…
Two papers at #ICLR2025 Biologically Plausible Brain Graph Transformer Hall 3 + Hall 2B #200 Thu 24 Apr 3pm - 5:30pm Factor Graph-based Interpretable Neural Networks Hall 3 + Hall 2B #523 Fri 25 Apr 3pm - 5:30pm #ICLR #AI #Brain #NeuralNetworks #Transformer #GraphLearning
A new survey paper: Title: Foundation Models for Anomaly Detection: Vision and Challenges Fulltext (PDF): arxiv.org/pdf/2502.06911 #FoundationModels #FM #LargeLanguageModels #LLM #AnomalyDetection #AI #MachineLearning #DeepLearning #Survey
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