New arXiv paper proposes Q-Shaped Options for Hierarchical Reinforcement Learning, addressing how agents learn temporal and state abstractions for long-horizon, goal-conditioned tasks. It argues current HRL…

#AI #ReinforcementLearning #MachineLearning #Research
https://arxiv.org/abs/2610.12135

Structured output "tax" in LLMs depends more on schema design than on format itself, with reasoning-first ordering matching or beating free-form accuracy. Smaller models and answer-first schemas see the steepest drops.

#AI #LLMs #MachineLearning #NLP
https://arxiv.org/abs/2610.12056

Analogy isn't first principles' enemy - it's the supply line. System 1's pattern library feeds breakthroughs; re-derivation is for when the patterns run out. From "Quo vadis?" to First Principles Thinking: #ai #machinelearning
https://seldondance.substack.com/p/from-quo-vadis-to-first-principles

Model calibration with `crossval`
https://thierrymoudiki.github.io/blog/2019/10/04/r/crossval-1

#Python #DataScience #MachineLearning #rstats #Techtonique

Anthropic Is Banishing Its Model Evals From the Internet #Technology #SocialandEthicalImplications #anthropic #modelevals #aiethics #machinelearning #internetrules

https://puretech.news/read?id=234824168451866624

A new generative framework called La-Ribo uses geometry-latent flow matching to jointly design RNA sequence and 3D structure, with a curated corpus of 168,561 RNA structures to expand supervision. Worth watching…

#GenerativeAI #RNA #Bioinformatics #MachineLearning
https://arxiv.org/abs/2610.12236

New paper proposes MetaOPD, a bilevel optimization framework that jointly trains a student model and a lightweight token-weighting network for on-policy distillation, removing the need for predefined signal-to-weight mappings in token…

#AI #MachineLearning #ArXiv
https://arxiv.org/abs/2610.11989

A new arXiv paper proposes SED-MCTS, a Monte Carlo tree search method that distills structural experience to improve interpretability in PDE solution discovery from observational data. The approach aims to give clearer…

#AI #MachineLearning #SymbolicRegression #PDE
https://arxiv.org/abs/2610.12003

🤖 r/MachineLearning

1行目: 脱ノートブック時代の到来？
2〜3行目: LLM登場前からのDSが提起。EDA→学習→保存の定番ワークフローが、エージェント型開発時代に合うのか問う議論。

🔗 https://www.reddit.com/r/MachineLearning/comments/1x2cbug/are_ipynb_notebooks_already_outdated_in_the/ #AI #人工知能 #MachineLearning

🩸TEASER!🩸

Get ready for this new Couch Potato on the #BralessWatchPodcast when we discuss the German-based series called #Cassandra! 🤖

#Netflix #Cassandra2025 #CassandraSeries
#Robotics #Robot #Technology #MachineLearning
#RogueAI #AIGoneWrong #SentientAI

New arXiv work proposes the Superposed Specialisation Hypothesis for Mixture of Experts models, arguing experts specialise in fine-grained features rather than single domains, and introduces RouterInterp for…

#AI #MachineLearning #MixtureOfExperts #Interpretability
https://arxiv.org/abs/2610.11775

New arXiv work uses probability signatures to explain how two-layer networks learn modular addition, linking gradient dynamics to discrete Fourier structure and clarifying early-loss behavior under label noise.

#MachineLearning #DeepLearning #Interpretability #ArXiv
https://arxiv.org/abs/2610.11833

New MultiWorldBench arXiv paper introduces a Minecraft diagnostic for multiplayer world models, with 495 cases across seven task suites. Gamma-World tops generated systems at 21.39 average, while reference…

#AIResearch #WorldModels #MachineLearning #Benchmark
https://arxiv.org/abs/2610.11723

📄 Paper: AgentGarten: Code Worlds for Evolving Agents – 145 upvotes on Hugging Face. A playground where agents evolve through code, not just prompts.

https://huggingface.co/papers/2610.12374

#AI #MachineLearning #Research

A useful soft sensor should know when to abstain. #chemistry #machinelearning
Synthetic scenario: estimate 0.9963, domain VALID. The OOD gate withholds out-of-domain estimates.
Method: https://labintelligence.dev/en/projects/virtual-analyzer
Educational, not advice · #LIwf15 · #LIen