AINewsnow

Benchmarking Prompt Optimization of Large Language Models With Chess

arXiv:2610.00416v1 Announce Type: new Abstract: Evaluating large language models becomes increasingly challenging as their capabilities advance: benchmarks can saturate, public test sets risk contamination, and assessing harder tasks can require expensive grading or execution infrastructure. These…

Read the full story at arXiv cs.AI ↗

Timeline · 1 report

  1. 2026-10-02 04:00 · arXiv cs.AI
    Benchmarking Prompt Optimization of Large Language Models With Chess

More stories

  1. Bring near-Astra intelligence to everyday work with GPT-6.1 Sol on Amazon Bedrock — AWS Machine Learning Blog
  2. Gemini 4 Argon: our next era of frontier intelligence — Google Gemini Blog
  3. Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs — Allen Institute for AI (Ai2)
  4. Google Releases New Gemini Model With Guardrails Amid A.I. Safety Debate — New York Times Technology
  5. OpenAI scraps release of its latest AI model over safety concerns — France 24 — Artificial Intelligence
  6. Introducing GPT-6.1 Sol — OpenAI News
  7. Google tests its plan for AI data centers in space with Project Suncatcher — Scientific American
  8. OpenAI’s Dots Are Always-On AI Agents—and Its Answer to Meta’s Muse — Wired AI

Get the daily brief of stories like this at 6:30 every morning →