Many users attacked LeCun with personal and ethnic insults over his claim on the 1990 neural world models paper while a few praised Schmidhuber's refutation and noted good papers are often rejected in peer review.
Based on 4 visible X reactions from 7 accounts; directional sample.
Ask a question below.
Published answers will appear here.
@SchmidhuberAI It's honestly hilarious How french r always these disgusting lying bastards And Germans always the good guys
@SchmidhuberAI Bringing up peer review at all is a cope. You would deserve credit even if it was not peer reviewed.
@SchmidhuberAI There are many good papers which were not accepted through peer review.
Yann LeCun claimed on social media [7] that my foundational 1990 paper on Neural World Models [1] "was never accepted through peer review." This is simply false. The core concepts from the tech report [1] were peer-reviewed and published at international conferences right away: ★ Planning with recurrent world models: peer-reviewed and published at IJCNN'90 (San Diego, June 1990) [2]. ★ Artificial curiosity through generative & adversarial nets (GANs): peer-reviewed and published at SAB'91 [3][4]. BTW, the 1990 paper [1] was the first of its kind to use the term "World Model" for a predictor neural network learning to predict the consequences of the actions of a controller neural network. Instead of acknowledging that "modern" architectures like "JEPA" (2022) are essentially identical to our 1992 Predictability Maximization (PMAX) [6][7] - a fact recently validated by others [8] - LeCun resorts to false claims about peer review. For the full timeline of the 1990-2015 publications that his 2022 AMI paper rehashes without citation, read the complete, updated receipts here [6]: https://people.idsia.ch/~juergen/lecun-rehash-1990-2022.html Other claims about LeCun are debunked in [8][9]. REFERENCES (easy to find on the web): [1] J. Schmidhuber (JS). Making the world differentiable: On using fully recurrent self-supervised neural networks for dynamic reinforcement learning and planning in non-stationary environments. Technical Report FKI-126-90, TUM, Feb 1990, revised Nov 1990. The first paper on planning with reinforcement learning recurrent neural networks (NNs) and recurrent world models (more), and on generative adversarial networks where a generator NN is fighting a predictor NN in a minimax game (more). Apparently, it was also the first paper of this kind to use the term "world model" for the predictor NN (although the basic concept of a world model is much older than that). [2] JS. An on-line algorithm for dynamic reinforcement learning and planning in reactive environments. Proc. IEEE/INNS International Joint Conference on Neural Networks, San Diego, volume 2, pages 253-258, June 17-21, 1990. Based on [1]. [3] JS. A possibility for implementing curiosity and boredom in model-building neural controllers. In J. A. Meyer and S. W. Wilson, editors, Proc. of the International Conference on Simulation of Adaptive Behavior: From Animals to Animats, pages 222-227. MIT Press/Bradford Books, 1991. Based on [1]. [4] JS. Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991). Neural Networks, Volume 127, p 58-66, 2020. Preprint arXiv/1906.04493 [5] JS. The Neural World Model Boom. Technical Note IDSIA-2-26, April 2026. [6] JS (2022, updated 2026). LeCun's 2022 paper on autonomous machine intelligence rehashes but does not cite essential work of 1990-2015. Years ago, Schmidhuber's team published most of what LeCun calls his "main original contributions:" neural nets that learn multiple time scales and levels of abstraction, generate subgoals, use intrinsic motivation to improve world models, and plan (1990); controllers that learn informative predictable representations (1997), etc. This was also discussed on Hacker News, reddit, and in the media. [7] JS. Who invented JEPA? With a reply to LeCun's response. Technical Note IDSIA-3-22, IDSIA, Switzerland, April 2026. [8] JS. How 3 Turing awardees republished key methods and ideas whose creators they failed to credit. Technical Report IDSIA-23-23, Switzerland, 2023 (updated 2026). [9] JS. Who invented convolutional neural networks? Hint: LeCun didn't. CNN basics: Fukushima (1979-86). Backpropagation for CNNs: Zhang et al. (1988-), others. Technical Note IDSIA-17-25, Switzerland, 2025.
@SchmidhuberAI Bringing up peer review at all is a cope. You would deserve credit even if it was not peer reviewed.
Many users attacked LeCun with personal and ethnic insults over his claim on the 1990 neural world models paper while a few praised Schmidhuber's refutation and noted good papers are often rejected in peer review.
Based on 4 visible X reactions from 7 accounts; directional sample.
Ask a question below.
Published answers will appear here.