Unverified50% confidenceBenchmarkExact time
In the IGG test, the strongest open-source vision-language model (VLM) achieved only 31.6% accuracy.
1
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50%
Confidence
Medium-term (~90 days)
Relevance
10/26/2026
First Seen
Valid until: 1/24/2027
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UnverifiedDirectly querying the VLM yielded a four-label exact-match accuracy of only 22.6%.69% similarUnverifiedIn a speculative decoding test using Qwen2.5 0.5B as the draft model proposing 4 tokens at a time, the overall draft acceptance rate was 32.9% for serial processing and 37.1% for concurrent processing.69% similarUnverifiedWhen DINOv3 ViT-H+/16 is pruned to 50% sparsity, removing 427 million parameters, ImageNet-1k linear probe accuracy drops by only 0.8%, without weight correction or retraining.65% similarUnverifiedThe best-performing test generator achieved a test quality score of 0.71 on QHack and only 0.34 on Qiskit HumanEval.65% similarUnverifiedUnder conditions where the target language is explicitly specified in the prompt (L3 prompts), GLM-5.1 achieved a generation accuracy of 72.29%, while Llama-3.3 70B reached only 24.24%.64% similar
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