Benchmark RadarAI BENCHMARK PROFILE
MMLongEmbed
MMLongEmbed is a benchmark for evaluating multimodal embedding models in long-context scenarios, covering four retrieval tasks across text, document, and video modalities with varying context lengths.
- Released
- 2026-06-05
- Readiness
- Paper only
- Primary field
- General AI
Why it matters
It addresses the gap in evaluating long-context multimodal embeddings, which is critical for real-world deployment where models must handle long inputs effectively.
Motivation
Recent advancements have significantly expanded the theoretical context windows of Multimodal Embedding Models (MEMs).
Primary resources
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