AutoIndex learns executable programs that shape how search corpora are represented
mrdrozdov · x · 2026-07-22
The post points to AutoIndex, a new research project on Learning Representation Programs for Retrieval.
- AutoIndex learns executable programs that decide how a corpus should be represented for a search engine.
- The authors frame it as part of a broader class of AI systems that optimize the executable programs around them.
- The post includes a site, arXiv paper, and code release.
Related event: AutoIndex Framework Proposes Optimization via Representation Programs(8 posts)→
More from Research
- EdgeRock-4B holds KV cache at 72 MiB across 256K context, 99.1% smaller than Qwen3.5-4B — alifcoder · 2026-10-27
- TRL adds Score Centering, a simple fix for RLHF training instability — lvwerra · 2026-10-27
- Latent-Foresight: world models that learn to predict their own future — abursuc · 2026-10-27
- UK AISI papers: no good safeguards yet against misuse of biological AI tools — davidmanheim · 2026-10-27
- CMU's XYBench: LLMs answer queries literally and reinforce user misconceptions — valentina__py · 2026-10-27
- arXiv advice from T. Dietterich: wrong primary category will almost surely get your paper on hold — tdietterich · 2026-10-27