discovering shared pdes from multiple datasets
a new method uses competitive optimization to find governing partial differential equations from several datasets with different conditions.
topic
machine learning
training llms as zero-shot workflow generators
metaflow trains language models to produce reusable task-level workflows instead of instance-specific solutions, improving reliability and interpretability.
hierarchical global attention for long-context transformers
hierarchical global attention replaces dense causal attention in pretrained transformers, enabling 64k-token context on a single 32gb gpu without retraining.
why few-step text latents fail but image latents work
few-step text generation fails because of sharp categorical readouts, not poor transport, as proven by a geometric analysis of continuous text decoders.
benchmarking ai agents for java framework migration
scarfbench evaluates ai agents on real-world enterprise java framework migrations, measuring build, deploy, and behavioral success.
every eval ever results now on hugging face model pages
every eval ever and hugging face community evals are now intercompatible, enabling cross-posting and interpreting evaluation results with links to open models and leaderboards.
miles: pytorch-native stack for large-scale llm rl post-training
miles is an open source framework that combines sglang, megatron-lm, ray, and pytorch for scalable reinforcement learning post-training of large language models.
7 python projects for 2026 with guides
practical python projects covering ai automation, machine learning, apis, dashboards, and data analysis with full guides and resources.
google releases nano banana 2 lite and gemini omni flash
google deepmind launches nano banana 2 lite for fast image generation and gemini omni flash for video generation and conversational editing.
local ai agents with qwen3.6 and mcp
build a local github assistant using qwen3.6-35b-a3b and the model context protocol to read issues, fix bugs, and create pull requests without cloud dependency.
why specialization is inevitable in ai
optimization theory, biology, markets, and machine learning all point to the same conclusion: under finite resources, focused systems outperform general ones.
variance reduction in non-reversible langevin algorithms
a study shows how anti-symmetric perturbations can reduce variance in stochastic gradient langevin monte carlo estimators under small step sizes.
benchmark tests if ai can draw scientific figures
a new benchmark evaluates how well ai models generate scientific figures with correct labels, relations, and conventions.
spectral geometry initialization for sigmoidal mlps
a new method initializes sigmoidal neural network weights using spectral geometry from data, improving training and performance.
rl researchers must separate solving simulators from using them as proxies
a position paper argues that reinforcement learning researchers should clearly distinguish between optimizing for simulator performance and using simulators as stand-ins for real-world deployment.
one transformer for density and score across distributions
discoformer estimates density and score in one forward pass without retraining, outperforming kernel density estimation in high dimensions.
best value ai coding subscription plans for developers
a comparison of five ai coding subscription plans that offer strong value through token, credit, or quota-based pricing.
when rag fails: four alternatives
retrieval-augmented generation breaks in predictable ways at scale, and engineers are turning to long-context prompting, memory compression, structured retrieval, and graph-based reasoning instead.