🔱 Why can irrelevant text outrank an image that actually contains the answer?

We find that multimodal retrievers can perform well on text-only and image-only corpora, yet degrade sharply when text and images are mixed.

We call this phenomenon "Chaos in the Text."

Our analysis reveals a systematic Modality Preference: text often receives higher similarity scores than semantically aligned images. We introduce Trident, which jointly trains Text / Image / Fused views with Multi-Positive View InfoNCE.

On 6 visual-document retrieval benchmarks, Trident-Qwen3VL-2B improves Mix Avg NDCG@10 from 40.12 → 73.90.

📄 Paper/Project: https://chaos-in-texts.github.io/
💻 Code: https://github.com/OpenBMB/Trident

#MultimodalRetrieval #MultimodalRAG #RAG #VLM #Embedding #Trident #ChaosInTheText #OpenBMB