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  • October 7, 2026 · arxiv.org

    Red Queen Gödel Machine coevolves agents and evaluators

    A paper published June 29, 2026 describes a method that evolves agents and evaluators, keeping evaluators fixed per epoch and replacing them only after better performance on reserved ground truth.

  • October 7, 2026 · t.co

    Physical network learns without a digital model

    A Nature Communications paper published on June 24, 2026 describes a physical neural network with four programmable metasurfaces that learns through electromagnetic interactions.

  • October 7, 2026 · godbolt.org

    C++ reflection can modify private data

    An example published by Compiler Explorer on July 23, 2026, uses reflection with an unchecked access context to increment every non-static data member of Foo, including its private field secret.

  • October 7, 2026 · fa.bianp.net

    REINFORCE: policy gradients and variance

    A post published on July 12, 2026 derives the REINFORCE estimator without differentiating through the environment and analyzes how variance depends on trajectory length.

  • October 7, 2026 · arxiv.org

    Rejection sampling for on-policy LLM alignment

    A paper published on July 7, 2026 proposes using rejection sampling to treat accepted off-policy tokens as on-policy and address the variance of accumulated per-token importance sampling ratios.

  • October 7, 2026 · proceedings.iclr.cc

    RESA: recovering context with sparse attention

    Published on September 29, 2026, the RESA paper proposes using residual estimation to recover context ignored by sparse attention, with no additional computational cost, according to the paper.

  • October 7, 2026 · x.com

    Token retention may reduce reliance on the KV cache

    A publication dated September 13, 2026, claims that keeping four initial tokens and a 64-token window without training matches or exceeds distilled linear-attention models on nearly all benchmarks.

  • October 7, 2026 · github.com

    Reversecore_MCP connects AI agents to reverse engineering

    The GitHub repository describes an MCP server for AI agents that integrates binary-analysis tools and lists uses in reverse engineering, malware analysis, forensics, vulnerability research, and SAST.

  • October 7, 2026 · riotgames.com

    Riot announces on-demand Vanguard operation

    In a post published on June 24, 2026, Riot announced that Vanguard can run only during gameplay when specified device security features are enabled.

  • October 7, 2026 · zhihu.com

    Long-horizon RL may favor PPO

    A Zhihu post published on June 24, 2026, argues that long, noisy agentic rollouts may make credit assignment harder for GRPO and make PPO's value model useful.

  • October 7, 2026 · alignment.openai.com

    RL for beneficial behavior across domains

    In a post published on June 18, 2026, OpenAI reports that behavior-focused reinforcement learning improved alignment across domains and resisted adversarial pressure.

  • October 7, 2026 · x.com

    Post-training RL with fewer parameters changed

    A post published on July 5, 2026 describes an approach that reinforces high-contribution intermediate layers during post-training RL. It may match or outperform RL across all parameters while changing fewer parameters.

  • October 7, 2026 · arxiv.org

    RLSD adjusts RLVR updates at the token level

    A paper published on July 11, 2026 presents a training method that combines environmental rewards with self-distillation. Across five multimodal reasoning benchmarks, it reports higher average accuracy than the base model and GRPO.

  • October 7, 2026 · github.com

    RVC WebUI: local voice conversion with data

    A repository published on September 15, 2026 describes a web interface for training voice-conversion models, including with 10 minutes or less of voice data.

  • October 7, 2026 · arxiv.org

    RWKV combines parallel training with recurrent inference

    An article published on September 20, 2026 describes an architecture combining Transformer-style parallel training with RNN-style recurrent inference, with memory and computation scaling linearly with sequence length.

  • October 7, 2026 · x.com

    Sampling for SFT: evaluating post-training

    A post published on October 2, 2026 presents a method that adds sampling to the post-training stack and claims it may improve generalization and reduce forgetting in some cases.

  • October 7, 2026 · arxiv.org

    Elastic sandboxes for training and evaluating agents

    Published on September 23, 2026, the article describes stateful, elastic execution environments for large-scale agent training and evaluation, as well as defenses against agents exploiting training environments.

  • October 7, 2026 · x.com

    Sandbox infrastructure: a scale reference

    A publication dated September 22, 2026 reports that a production-scale compute unit spans about 160 nodes and supports more than 380,000 concurrent sandboxes.

  • October 7, 2026 · arxiv.org

    SearchEyes connects simulated worlds to agent training

    The SearchEyes paper describes a simulated search world built on a typed knowledge graph for training multimodal agents. Published on July 8, 2026, it addresses gaps among training data, search environments, and reward signals in multi-hop reasoning.

  • October 7, 2026 · x.com

    Data-free self-play: how to evaluate the approach

    A paper dated September 25, 2026 explores self-play pretraining without real data and reports predictable reductions in zero-shot validation loss across several modalities.

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