“The article aims to provide a clear explanation of 'supervised learning', 'unsupervised learning', and 'reinforcement learning'.”

“That's why there's a task AI simply can't do: accepting judgments that might be disliked.”

“Unsloth now enables 7x longer context lengths (up to 12x) for Reinforcement Learning!”

“この記事では、VeRLというフレームワークを使ってMegatron-LMをベースにLLMをRL（PPO、GRPO、DAPO）する方法について解説します。”

“SFT: Phase for teaching 'etiquette (format/inference rules)'; RL: Phase for teaching 'preferences (good/bad/safety)'”

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“An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence.”

“It’s built to power reliable on-device agentic applications: higher quality, lower latency, and broader modality support in the ~1B parameter class.”

“We propose an approach to enhance planning with JEPA world models by shaping their representation space so that the negative goal-conditioned value function for a reaching cost in a given environment is approximated by a distance (or quasi-distance) between state embeddings.”

“Article URL: https://bostondynamics.com/blog/boston-dynamics-google-deepmind-form-new-ai-partnership/”

“By reducing propagation steps in LLM deployments, MetaJuLS contributes to Green AI by directly reducing inference carbon footprint.”

“I just watched this video and I believe that it’s a very clear view of our present situation. Even if it didn’t help the fear of an AI takeover, it did make me even more sure about the necessity of regulations and more tests for AI safety. Even if it meant slowing down.”

“Tweet from a DeepMind RL researcher outlining how agents, RL phases were in past years and now in 2026 we are heading much into continual learning.”

“After years of hype about generative AI increasing productivity and making lives easier, 2025 was the year erotic chatbots defined AI’s narrative.”

“B-Trans effectively leverage the wisdom of crowds, yielding superior semantic diversity while achieving better task performance compared to deterministic baselines.”

“ResponseRank robustly learns preference strength by leveraging locally valid relative strength signals.”

“MSACL achieves exponential stability and rapid convergence under simple rewards, while exhibiting significant robustness to uncertainties and generalization to unseen trajectories.”

“Later models display emergent generalization by discovering much longer plans than the initial models.”

“The paper proposes a joint-state abstraction that compresses the state space while preserving the information necessary to discover strongly coordinated behaviours.”

“The paper provides the first convergence guarantee for Optimistic Multiplicative Weights Update (OMWU) in NLHF, showing that it achieves last-iterate linear convergence after a burn-in phase whenever an NE with full support exists.”

“The proposed DRL controllers achieve online inference times of 0.6 ms per decision versus roughly 370-550 ms for AO-WMMSE solvers.”

“The paper provides the first non-vacuous guarantees in high-dimensional sparse MDPs with single-policy concentrability coverage and corruption, showing that learning a near-optimal policy remains possible in regimes where traditional robust offline RL techniques may fail.”

“The paper explores integer (Int8) quantization and a resource-aware gait scheduling viewpoint to maximize RL reward under power constraints.”

“EVOL-SAM3 not only substantially outperforms static baselines but also significantly surpasses fully supervised state-of-the-art methods on the challenging ReasonSeg benchmark in a zero-shot setting.”

“The paper introduces a continuation-based learning framework that combines simplified model pretraining and model homotopy transfer to efficiently generate and refine complex dynamic behaviors.”

“The core of embodied intelligence is "intelligent robots," which gives various robots the ability to perceive, reason, and make generalized decisions. This is no exception for flight, which will redefine flight robots.”

“The proposed HOOA achieves significant improvements, which reduces average task completion delay by 2.5% and average energy consumption by 3.1% compared with the best-performing benchmark approach and state-of-the-art DRL algorithm, respectively.”

“HMP-DRL consistently outperforms other methods, including state-of-the-art approaches, in terms of key metrics of robot navigation: success rate, collision rate, and time to reach the goal.”

“PAM supports a 300-frame history window while maintaining high inference speed (above 20Hz).”

“Experiments demonstrate that Youtu-Agent achieves state-of-the-art performance on WebWalkerQA (71.47%) and GAIA (72.8%) using open-weight models.”

“The framework delivers a 3x increase in task processing speed over single-agent baselines, 98.7% structural/style consistency in writing, and a 74.6% test pass rate in coding.”

“DARFT suppresses strong distractors and sharpens decision boundaries without additional supervision.”

“The Bayesian DP algorithm alternates between posterior updates and value iteration, employing an estimator for the risk-based Bellman operator that combines Monte Carlo sampling with convex optimization.”

“HUMOR employs a hierarchical, multi-path Chain-of-Thought (CoT) to enhance reasoning diversity and a pairwise reward model for capturing subjective humor.”

“The two-stage approach decomposes spatial reasoning into atomic building blocks and their composition.”

“Analyzing 1.4 million customer transactions across seven markets, our approach reduces false positive and false negative rates to 4.64% and 11.07%, substantially outperforming single-institution models. The framework prevents 79.25% of potential losses versus 49.41% under fixed-rule policies.”

“The paper proposes a diagnostic-driven adaptive learning framework that explicitly models error evolution through a principled decomposition into bias, capturing persistent drift; noise, capturing stochastic variability; and alignment, capturing repeated directional excitation leading to overshoot.”

“The paper's key finding is the development of a semiparametric framework for debiased inverse reinforcement learning that yields statistically efficient inference for a broad class of reward-dependent functionals.”

“ViReLoc plans routes between two given ground images.”

“SenseNova-MARS achieves state-of-the-art performance on open-source search and fine-grained image understanding benchmarks. Specifically, on search-oriented benchmarks, SenseNova-MARS-8B scores 67.84 on MMSearch and 41.64 on HR-MMSearch, surpassing proprietary models such as Gemini-3-Flash and GPT-5.”

“MaRCA delivered a 16.67% revenue uplift using existing computation resources.”

“The paper proves the existence of an optimal closed-loop policy for the original MFTG when the state spaces are at most countable and the action spaces are general Polish spaces.”

“FIGR improves the base model by 13.12% on AIME 2025 and 11.00% on BeyondAIME, highlighting the effectiveness of figure-guided multimodal reasoning in enhancing the stability and reliability of complex reasoning.”

“SiLRI effectively exploits human suboptimal interventions, reducing the time required to reach a 90% success rate by at least 50% compared with the state-of-the-art RL method HIL-SERL, and achieving a 100% success rate on long-horizon manipulation tasks where other RL methods struggle to succeed.”

“DRL-TH outperforms existing methods in various crowded environments. We also implemented DRL-TH control policy on a real UGV and showed that it performed well in real world scenarios.”

“The method exhibits notable advantages in terms of computational efficiency and scalability, particularly in large-scale and time-constrained scenarios.”

“D^2-Align achieves superior alignment with human preference.”

“GARDO's key insight is that regularization need not be applied universally; instead, it is highly effective to selectively penalize a subset of samples that exhibit high uncertainty.”