Keynote speech 一 “Exploring Semantics in the Age of Large Language Models“ at NeusymBridge Workshop@AAAI’26 on Jan 26, Singapore. https://t.co/kmHlWsfoIT
The Workshop on “Neural Reasoning for Scientific and Mathematical Discovery” will take place from March 23 to 24, 2026 at Department of Computer Science and Technology, University of Cambridge.
https://t.co/MZACgbTlf9
Registration is open now.
https://t.co/5J99A0b6AS
Rigorous syllogistic reasoning serves as the watershed separating irrational from rational reasoning systems. Data-driven neural networks, including LLMs, are clearly located on the left side.
https://t.co/NFkDzK1EzC
Four methodological limitations prevent machine learning systems from reaching the rigour of logical reasoning. They cannot, not because of insufficient training data. On the contrary, to achieve the rigour, they shall not use training data.
https://t.co/meIgqp4rXP
Sphere Neural-Networks (SphNNs) ... imbuing neural networks with capabilities for more complex and deterministic forms of reasoning, including syllogistic reasoning—a foundational element of human rationality.
https://t.co/Cp8JONS407
Current LLMs are trained on text data that would take 20,000 years for a human to read.
And still, they haven't learned that if A is the same as B, then B is the same as A.
Humans get a lot smarter than that with comparatively little training data.
Even corvids, parrots, dogs, and octopuses get smarter than that very, very quickly, with only 2 billion neurons and a few trillion "parameters."
The 🆕 report of the @dagstuhl seminar "Structure and Learning" in #AI, organized by #ML2R researcher @DongTiansi (@UniBonn), is now available online!
Learn more about the integration of symbolic & numeric #inference from an interdisciplinary perspective: https://t.co/CCf7Ulh1W5
Want to know why it's risky to assume that your ML is going to continue work if the test regime changes from your training data? Just ask Zillow.
https://t.co/EUH71gZspy
#BoxingDay is: now!📦
🗣️ Our #ML2R#AutumnSchool kicks off today at 9.30 a.m. CEST. During this week, over 30 selected #MachineLearning enthusiasts (10 countries) will work & learn together to apply their #ML solutions to a concrete #BinPacking problem.
ℹ️ https://t.co/4jtcFq0A13
The second and last testing day at the ANA Avatar Xprize Challenge Semifinals also went very well. We may have received even more points than yesterday.
https://t.co/rYfZ1Rvq24