IFBench

A new arXiv paper (2608.10694v1) proposes a cost-aware cross-tier transfer method for evolutionary optimization of LLM prompts and agentic programs, reducing search cost by 5.6-14x (up to 25-54x with …

Shanghai AI Laboratory's Agents-A1, a 35-billion-parameter Mixture-of-Experts model, matches or outperforms trillion-parameter rivals by training on longer task sequences instead of increasing paramet…

Researchers propose BINEVAL, a framework that decomposes LLM evaluation into atomic binary questions for interpretable, multi-dimensional scoring. The method matches or outperforms strong baselines on…