Denis Yarats(@denisyarats):we are releasing a new benchmark and a public leaderboard for embedding models that measure the performance of large-scale agentic web search. more info can be found here. paper: https://t.co/Sy8iq65uOl blog: https://t.co/Lbfs7wXy6e leaderboard:

2026.09.09 21:29

we are releasing a new benchmark and a public leaderboard for embedding models that measure the performance of large-scale agentic web search. more info can be found here. paper: blog: leaderboard:

Perplexity@perplexity_ai

2026.09.09 20:21

We're introducing Q2D-Web (Query2Doc-Web), a benchmark and public leaderboard for evaluating retrieval in agentic RAG systems. Q2D-Web tests how embedding models perform on large-scale web search using agent-reformulated search queries. Read more: