Qwen3VL-8B

ReToken: Single learnable embedding improves VLM visual retrieval in long contexts

ReToken introduces a single learnable embedding trained as an explicit retrieval target to select sparse, query-relevant visual tokens from a pre-filled KV cache, addressing performance degradation in vision-language models under long visual contexts. Trained on a small image-QA dataset, it improves Qwen3VL-8B by 13.4 points on Visual Haystacks and transfers zero-shot to long video benchmarks with an 8.0-point gain on LVBench. The method is lightweight enough for both training and long-video inference on a single H100 GPU. Code is publicly released.