Evaluation & benchmarks for intermediate learners
454 resources · page 15 of 15
Sarvam-M multilingual language model (Sarvam AI)
by Sarvam AI
Sarvam AI technical post on Sarvam-M, a hybrid reasoning model for Indian languages, with post-training and inference details.
SWE-bench paper
by Carlos E. Jimenez et al. (Princeton University)
arXiv paper (2023) introducing SWE-bench, evaluating language models on resolving real GitHub issues.
The SWE-Bench Illusion
by Shanchao Liang et al. (Purdue University)
arXiv paper (2025) "The SWE-Bench Illusion", testing whether LLMs memorise SWE-bench instead of reasoning.
W&B Weave documentation
by CoreWeave (Weights & Biases)
W&B Weave documentation, now hosted by CoreWeave: tracing, testing and evaluating LLM applications.
What We've Learned From A Year of Building with LLMs
by Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu and Shreya Shankar
Applied LLMs guide by Yan, Bischof, Frye, Husain, Liu and Shankar: tactical, operational and strategic lessons from building LLM products.
Wikipedia: AI safety institutes
by Wikipedia (Wikimedia Foundation)
Wikipedia article on AI safety institutes: state-backed bodies that evaluate AI safety, listed by country.