Massive Text Embedding Benchmark: A global effort to expand text embedding evaluation to all languages

  • Enevoldsen, Kenneth Christian (PI)
  • Bernstorff, Martin (Deltager)
  • Kardos, Márton (Deltager)
  • Kerboua, Imene (Projektkoordinator)
  • Schaeffer, Marion (Deltager)
  • Xiao, Shitao (Deltager)
  • Cassano, Federico (Deltager)
  • Li, Wen-Ding (Deltager)
  • Rystrøm, Jonathan (Deltager)
  • Lee, Taemin (Deltager)
  • Zhang, Xin (Deltager)
  • Weller, Orion (Deltager)

Projekter: ProjektForskning

Projektdetaljer

Beskrivelse

Massive Text Embedding Benchmark (MMTEB) is a global effort to expand text embedding evaluation to all languages with more than 50 contributors. The benchmark seeks to evaluate the quality of embeddings of text, e.g. used for search, retrieval etc.
Kort titelMassive Text Embedding Benchmark
AkronymMMTEB
StatusIgangværende
Effektiv start/slut dato01/04/2024 → …