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Check out all the amazing work from our @SimonsFdn Collaboration on the Physics of Learning and Neural Computation (https://www.physicsoflea…
Check out all the amazing work from our @SimonsFdn Collaboration on the Physics of Learning and Neural Computation (https://www.physicsoflearning.org/) presented at the main meeting of @ICMLconf #ICML
Check out all the amazing work from our @SimonsFdn Collaboration on the Physics of Learning and Neural Computation (https://www.physicsoflearning.org/) presented at the main meeting of @ICMLconf #ICML2026 Tuesday Efficient Learning of Compositional Targets with Hierarchical Spectral Methods,Hugo Tabanelli, Yatin Dandi, Luca Pesce, and Florent Krzakala https://icml.cc/virtual/2026/poster/61650 CompleteP for RL: Maintaining Feature Learning When Scaling Deep Reinforcement Learning M Ganesh Kumar, Adam Lee, Blake Bordelon , Cengiz Pehlevan https://icml.cc/virtual/2026/poster/66419 Universal One-third Time Scaling in Learning Peaked Distributions Yizhou Liu, Ziming Liu, Cengiz Pehlevan, Jeff Gore https://icml.cc/virtual/2026/poster/61005 Wednesday A Noise Sensitivity Exponent Controls Large Statistical-to-Computational Gaps in Single- and Multi-Index Models, Leonardo Defilippis, Florent Krzakala, Bruno Loureiro, Antoine Maillard https://icml.cc/virtual/2026/poster/64746 Single-Head Attention in High Dimensions: A Theory of Generalization, Weights Spectra, and Scaling Laws Fabrizio Boncoraglio, Vittorio Erba, Emanuele Troiani, Yizhou Xu, Florent Krzakala, Lenka Zdeborová https://icml.cc/virtual/2026/poster/66429 A Solvable High-Dimensional Model Where Nonlinear Autoencoders Learn Structure Invisible to PCA While Test Loss Misaligns With Generalization Vicente Mendes, Lorenzo Bardone, Cédric Koller, Jorge Medina Moreira, Vittorio Erba ⋅ Emanuele Troiani, Lenka Zdeborova https://icml.cc/virtual/2026/poster/60782 Deep networks learn to parse uniform-depth context-free languages from local statistics Jack T. Parley, Francesco Cagnetta, Matthieu Wyart https://icml.cc/virtual/2026/poster/61860 Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling Indranil Halder, Cengiz Pehlevan https://icml.cc/virtual/2026/poster/65764 On the Existence of Consistent Adversarial Attacks in High-Dimensional Linear Classification Matteo Vilucchio, Lenka Zdeborova, Bruno Loureiro https://icml.cc/virtual/2026/poster/64252 Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation Zier Mensch, Lars Holdijk, Samuel Duffield, Maxwell Aifer, Patrick Coles, Max Welling, Miranda C. N. Cheng https://icml.cc/virtual/2026/poster/61793 Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability Shobhita Sundaram, John Quan, Ariel Kwiatkowski, Kartik Ahuja, Yann Ollivier, Julia Kempe https://icml.cc/virtual/2026/poster/65098 Thursday Deriving Neural Scaling Laws from the Statistics of Natural Language Francesco Cagnetta ⋅ Allan Raventos ⋅ Surya Ganguli ⋅ Matthieu Wyart https://icml.cc/virtual/2026/poster/63606 Symmetry in language statistics shapes the geometry of model representations Dhruva Karkada, Daniel Korchinski, Andres Nava, Matthieu Wyart, Yasaman Bahri https://icml.cc/virtual/2026/poster/63405 A Random Matrix Perspective on the Consistency of Diffusion Models Binxu Wang, Jacob A Zavatone-Veth, Cengiz Pehlevan https://icml.cc/virtual/2026/oral/71191 Hyperparameter Transfer with Mixture-of-Expert Layers Tianze Jiang, Blake Bordelon, Cengiz Pehlevan, Boris Hanin https://icml.cc/virtual/2026/poster/62595 Analytic Bijections for Smooth and Interpretable Normalizing Flows Mathis Gerdes, Miranda C. N. Cheng https://icml.cc/virtual/2026/poster/65827 Efficient RL Training for LLMs with Experience Replay Charles Arnal, Vivien Cabannnes, Taco Cohen, Julia Kempe, Remi Munos https://icml.cc/virtual/2026/poster/63133 Embedding Trust: Semantic Isotropy Predicts Nonfactuality in Long-Form Text Generation Dhrupad Bhardwaj, Julia Kempe, Tim G. J. Rudner https://icml.cc/virtual/2026/poster/64313 What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT Yunzhen Feng, Julia Kempe, Cheng Zhang, Parag Jain, Anthony Hartshorn https://icml.cc/virtual/2026/poster/63469 From Kepler to Newton: Inductive Biases Guide Learned World Models in Transformers Ziming Liu, Surya Ganguli, Andreas Tolias https://icml.cc/virtual/2026/poster/62200
Source: Yann LeCun (X) | 2026-07-05