Research / AI Paper
arXiv paper on self-speculating LLM agents that predict their next tool call to hide tool latency and improve next-call Hit@1 while preserving task success.
This is a clearly AI-focused research paper with a substantial abstract, title, authorship, submission metadata, and a concrete technical contribution around agent tool-call prediction. The page gives enough evidence to support a public research listing.
The crawl does not show the full paper, code, data, benchmarks, or implementation details, so a visitor cannot tell how to reproduce the method or whether an accompanying repository exists.
Last evaluated 33 days ago. Current rank #1825. Up 1 spot in the rankings.
Primus is an autonomous AI researcher that hypothesizes, reads papers, writes code, runs experiments on compute, and drafts research papers. The page shows example tasks, published-paper claims, waitlist access, and positioning for ML research workflows.
An interactive dashboard that analyzes New York Times coverage since 2000 using the NYT Archive API, with views for reporters, beats, sections, subjects, geography, obituaries, and corrections.
An open benchmark and leaderboard for AI CAD agents, with 308 prompts across 20 categories and layered scoring for geometry, engineering, manufacturability, and cognition.
A research article from Applied Compute on how agentic, tool-using workloads differ from traditional LLM benchmarks, with production observations, workload profiles, and an open-source harness for replaying traces.
