Summary
ColQwen3.5-v2, a 4.5B parameter visual document retrieval model, has been released, built upon Qwen3.5-4B with a simplified two-phase training recipe. This new version incorporates domain-specific data and reuses hard negatives, leading to improved efficiency. It currently holds the top position on the ViDoRe V3 nDCG@10 leaderboard and significantly narrows the performance gap to other leading models on nDCG@5.
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