AI and infrastructure news

Post27

Reinforcement learning

Reinforcement learning Post
10/08/2618 days ago x.com
Fine-tuning a 14B code model with SFT and DPO
A January 20, 2026 article describes tuning a 14B model on code conversations and reports figures, costs, and difficulties.
Reinforcement learning Post
10/08/2618 days ago x.com
Architecture also shapes continual learning
An article published on January 17, 2026 reports that wider networks and less global average pooling may improve retention, while ResNets and WideResNets learn new tasks quickly but forget more.
Reinforcement learning Post
10/08/2618 days ago x.com
Measuring scale and cost in RL experiments
A post published on April 18, 2026, compares scaling laws for pre-training and reinforcement learning, highlighting sampling and policy-update costs and evaluation challenges.
Reinforcement learning Post
10/08/2618 days ago x.com
Progressive distillation for improving VLMs
In a post published on January 4, 2026, the author describes the Masters framework and reports gains on two vision-language models using an approach intended to avoid the computational cost of online RL.
Reinforcement learning Post
10/08/2618 days ago x.com
AI may discover reinforcement learning algorithms
A Nature article published on October 28, 2025, reports autonomous discovery of reinforcement learning algorithms and points to a potential new approach for engineers.
Reinforcement learning Post
10/08/2618 days ago x.com
LaSeR explores last-token rewards for LLMs
In a post published on October 19, 2025, Tencent presents LaSeR, a reinforcement learning algorithm that aligns last-token scores with real rewards and uses one extra token inference.
Reinforcement learning Post
10/08/2618 days ago x.com
MaxRL proposes another approach to RL with binary rewards
Published on February 9, 2026, the post describes MaxRL and reports up to 20 times greater test-time efficiency than GRPO.
Reinforcement learning Post
10/08/2618 days ago x.com
Looped models: scaling and practical evaluation
An article dated October 30, 2025 reports training looped language models with 2.6 billion parameters and more than 7 trillion tokens, with performance comparable to models two to three times larger.
Reinforcement learning Post
10/08/2618 days ago x.com
The Olmo 3 pipeline and training reasoning models
A post published on December 15, 2025 describes SFT with curated traces, followed by DPO and RLVR using group-relative policy optimization.
Reinforcement learning Post
10/08/2618 days ago x.com
Long prompts: recursive processing with code
An MIT post published on January 6, 2026 describes models using a Python interface to filter and recursively process segments of long prompts.
Reinforcement learning Post
10/08/2618 days ago x.com
Ring-1T: three-stage training for a 1-trillion-parameter MoE
A post published on October 22, 2025 describes Ring-1T, a reasoning MoE model with 1 trillion parameters and about 50 billion active per token, trained in three stages.
Reinforcement learning Post
10/08/2618 days ago x.com
Offline RL: Bayesian generalization in models
A post dated January 14, 2026, describes a paper exploring adaptive Bayesian generalization in model-based offline RL, using long-horizon rollouts to reduce conservative constraints.
Reinforcement learning Post
10/08/2618 days ago x.com
RLAC proposes an adversarial critic for open-ended generation
In a post published on November 5, 2025, the RLAC approach reports greater factuality and better code scores, with fewer validation calls, data, and test cases.
Reinforcement learning Post
10/08/2618 days ago x.com
RLoop alternates exploration and consolidation in RL
A post published on November 7, 2025 describes an iterative policy initialization strategy and reports gains on two evaluation metrics.
Reinforcement learning Post
10/08/2618 days ago x.com
Self-play for training code agents with real bugs
A publication dated December 26, 2025 describes Self-play SWE-RL, a method that trains an agent to insert and fix bugs in real repositories without human-labeled issues or natural-language problem descriptions.
Reinforcement learning Post
10/08/2618 days ago x.com
SETA launches 400 RL environments for terminal agents
On January 9, 2026, SETA announced training environments, an RL pipeline, and model weights for experiments with terminal agents.
Reinforcement learning Post
10/07/2619 days ago x.com
Training terminal agents in Dockerized RL environments
A post published on June 24, 2026 describes 14,600 Dockerized reinforcement-learning environments and an outcome-only DPPO recipe. A 9B model reached 27% on Terminal-Bench 2.0.
Reinforcement learning Post
10/07/2619 days ago x.com
AutoDecompiler applies RL to iterative decompilation
A post dated June 25, 2026 describes a model using reinforcement learning and direct feedback across multiple stages of decompilation.
Reinforcement learning Post
10/07/2619 days ago x.com
CodeMidas creates RL training tasks from code
In a post dated September 21, 2026, Xiaomi describes CodeMidas, which uses agents to generate 5,545 executable tasks in 23 languages from open-source codebases.
Reinforcement learning Post
10/07/2619 days ago x.com
How to measure RL gains on software engineering tasks
A post dated September 21, 2026 reports that MiMo Pro's DeepSWE score rose from 58.41 to 72.57 after reinforcement learning runs.
Reinforcement learning Post
10/07/2619 days ago x.com
How RL Could Expand Skills Learned Through SFT
A post published on July 11, 2026, presents the hypothesis that RL can separate useful SFT components into reusable skills and routing rules.
Reinforcement learning Post
10/07/2619 days ago x.com
On-policy distillation for consolidating specialist models
MOPD trains a student model on its own completions and uses token-level probabilities from multiple teachers to transfer specialist capabilities.
Reinforcement learning Post
10/07/2619 days ago x.com
Policy gradients: from derivation to practical evaluation
Published on August 30, 2026, the article reviews foundational reinforcement learning work, derives the policy gradient algorithm, and discusses its variants.
Reinforcement learning Post
10/07/2619 days ago x.com
ProRL Agent separates rollouts from LLM policy training
Published on September 30, 2026, ProRL Agent describes open-source rollout infrastructure that separates trajectory generation, environment orchestration, and evaluation from policy optimization for multi-turn agents.
Reinforcement learning Post
10/07/2619 days ago x.com
RubricEM uses step-by-step criteria to train research agents
Published on July 5, 2026, the work describes agents that create evaluation criteria before researching and reuse lessons from assessed attempts.
Reinforcement learning Post
10/07/2619 days ago 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.
Reinforcement learning Post
10/07/2619 days ago x.com
Training decision models with calibrated probabilities
A publication dated October 4, 2026 describes a reinforcement-learning setup that scores options in separate branches and combines outcome prediction with confidence calibration.

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