John Carmack (@ID_AA_Carmack) “#PaperADay recap On January 8th, I set out to read and take notes on one paper e” — TopicDigg

#PaperADay# recap On January 8th, I set out to read and take notes on one paper each weekday for the rest of the month. I missed one day due to a funeral, and another day due to bad time management, but not too bad. I probably averaged a bit over 2 hours on each of them, which is only a rough read in some cases, but still enough to put a pinch in my work days. You can easily spend all day on a single paper if you dig in deep. I have written code based on six of the papers so far, and the others are still kicking around in my head. For now, back to my previous habits, but I may consider doing “week of papers” in the future after I digest where this fits in the exploration / exploitation time tradeoff. 15: Mastering Diverse Domains through World Models 14: MASTERING ATARI WITH DISCRETE WORLD MODELS 13: DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION 12: Learning Latent Dynamics for Planning from Pixels 11: Discovering state-of-the-art reinforcement learning algorithms 10: LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics 9: floq: Training Critics via Flow-Matching for Scaling Compute in Value-Based RL 8: Beyond Gradient Averaging in Parallel Optimization: Improved Robustness through Gradient Agreement Filtering 7: Cautious Weight Decay 6: LOCAL FEATURE SWAPPING FOR GENERALIZATION IN REINFORCEMENT LEARNING 5: Small Batch Size Training for Language Models: When Vanilla SGD Works, and Why Gradient Accumulation Is Wasteful 4: Patches Are All You Need? 3: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture 2: Deep Delta Learning 1: Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning