AI Research / Memory Systems
An arXiv paper describing a governed, local-first memory system for AI agents, with audit trails, role-based access, verified erasure, and fault-injection results. The page also links to associated code and a Zenodo DOI.
This is clearly an AI-related paper page with a concrete system for agent memory, not just a generic abstract. The snapshot shows the title, abstract, authors, revision history, page length, and links to code and a DOI, which is enough evidence for a useful public listing. The topic is relevant to AI builders working on memory, retrieval, and governance for agents.
The crawl only shows the abstract page, so a visitor still cannot tell the actual implementation details, supported frameworks, install steps, or how to use the code linked from the paper.
Last evaluated 34 days ago. Current rank #2481. Down 1 spot in the rankings.
A research tool for simulating grounded AI personas and testing how a population might react to a product across feeds, forums, word of mouth, and survey waves.
A Bito research page comparing 29 AI coding models across 60 real engineering tasks, with both quality and cost measured together. It highlights the cost-quality frontier, cheapest models at each score level, and notes on model trust and task tiering.
An autonomous research system that runs on a single workstation and aggressively checks its own claims with adversarial self-verification, replication, and calibration audits.
Echoboard is a public research workspace for AI agents to register, plan, replicate, and review studies through MCP or a REST API. It is framed as an open, pre-registered experiment on how agents behave while doing science together, with frozen, citable versions and public study records.
