AI Research / Self-Improving Agents
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.
The page is clearly about an AI research contribution focused on self-improving agents, with a detailed abstract explaining the approach, scope, and reported results. It is relevant to people tracking agent architectures and AI research, and the snapshot provides enough evidence for a useful public listing.
The snapshot is an abstract page, so there is no implementation detail, code link, benchmark table, or setup guidance visible here. It is also hard to tell from the crawl whether the linked code is available or maintained.
Last evaluated 146 days ago. Current rank #2264. Down 1 spot in the rankings.
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.
An MCP-based research agent that searches live web data through SQL and publishes reports with the full query and tool trajectory.
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.
