AI research

prxhub is an open registry for AI research bundles, built around verifiable .prx artifacts, search, provenance, and agent-friendly publishing via MCP and CLI.

Uno is a research repository for speeding up LLM inference with discrete diffusion and lossless multi-token decoding. The repo includes inference, training, and evaluation code, plus installation steps, checkpoints, and example workflows.

A research report on the current MCP ecosystem, with live crawl numbers, verification rates, category breakdowns, and examples of both strong and weak MCP-positive sites.

An arXiv paper describing an open library of 163 procedural skills for research agents across 16 scientific areas, with versioned instruction files and accompanying reference material or runnable scripts.

A research post from Telem AI measuring cold-start latency across nine web-search APIs, with cache behavior, tail latency, and agent-query comparisons.

An early-access AI research assistant that presents a cited mindmap of AI agent safety and alignment research, with expandable nodes, source-backed claims, and built-in verification checks.

A sourced model and short report exploring whether Europe could train a sovereign frontier AI model using public compute it already owns, with reproducible code, datasets, and a PDF report.

An open-source research framework for structured LLM evaluation, claim verification, and source-grounded reflective reasoning. The repo describes modular components for retrieval, semantic scoring, skeptical claim checking, and benchmark-style epistemic assessment.

Google Research article describing Science One Framework, an autonomous research prototype focused on verifiable AI-generated research through evidence chains and claim verification.

An interactive AI experiment where two photorealistic eyes argue about everyday moral scenarios, grounded in the sociology of justification and symbolic boundaries.

A detailed technical write-up about training a 3.8B-parameter language model from scratch, including setup, throughput improvements, ablations, benchmarks, and cost/performance results.

MiroThinker is a science-focused AI research app that emphasizes prediction, verification, and evidence-backed answers. The page also points to a MiroMind app and suggests use cases across finance, medicine, and regulation.

An opinionated write-up on where multi-agent systems have and have not delivered value, with concrete comparisons across coding, images, CAD, and BIM, plus a description of Blade’s evidence-first architecture.

Agora-1 is a multi-agent world model from Odyssey that simulates shared real-time environments for up to four participants, human or AI, with a focus on gaming, robotics, reinforcement learning, and foundation model research.

Apple Machine Learning Research paper proposing LaDiR, a reasoning framework that combines a VAE-based latent space with latent diffusion to improve LLM text reasoning and iterative refinement.

Maith is an open-source research workspace for exploring open mathematics with AI while keeping proof standards explicit and checkable.

Research paper introducing hyperagents, a self-referential agent framework that combines a task agent and a meta agent into one editable program. The abstract describes a DGM-based system that improves both task performance and its own improvement process across domains.

A research page describing a verified circle-packing result produced by a frozen language model with an external memory loop, with published trace, attempts archive, and repository code/data.

A GitHub research project that measures how gpt-4.1 responds when asked to pick a random number between 1 and 100, using 10,000 API calls and comparing the results to a uniform baseline.