AI needs meaningful versioning
Nature Machine Intelligence, Published online: 02 November 2026; doi:10.1038/s42256-026-01323-8 Artificial intelligence (AI) providers frequently update their models and system integrations…
LRMoE: Demand-Side Load Re-Calibration for Efficient MoE Training on Memory-Constrained Nodes
arXiv:2610.37720v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) models offer scalable capacity for Web applications, but uneven routing creates computation…
REGER: Modeling inter-item Relations with Semantic IDs for Generative Recommendation
arXiv:2610.37584v2 Announce Type: replace-cross Abstract: Personalized recommendation depends on learning semantic and collaborative relations among items from online content and…
Learning to Bound: Monotonic, Calibrated Neural Upper Bounds for MPE Inference
arXiv:2610.39305v1 Announce Type: cross Abstract: Probabilistic graphical models (PGMs) compactly encode structured joint distributions, but Most Probable Explanation (MPE), which…
There Is No Free Lunch in RLVR: Every pass@1 Gain Has a pass@k Price
arXiv:2610.39295v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) makes a language model solve more problems on the…
Proposing Better Rollouts for On-Policy Distillation
arXiv:2610.36477v2 Announce Type: replace-cross Abstract: On-policy distillation (OPD) improves language-model post-training by letting the student learn from its own sampled…