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Forget brute-force context windows: a small vision-language model can compress hour-long videos below theoretical limits by intelligently prioritizing relevant content.
Achieve LLM-level semantic hyperlink verification at 47x the speed and a fraction of the cost by using a Siamese Sentence-BERT network, opening the door for scalable web quality assurance.
Forget scaling laws: a large VLM strategically paired with a smaller model's reasoning tokens can rival the performance of a much larger, monolithic model.
Scale up offline policy training for diffusion LLMs without breaking the bank: dTRPO slashes trajectory computation costs while boosting performance up to 9.6% on STEM tasks.
Forget scaling laws: this work shows you can get SOTA reasoning from sub-billion parameter models with *less* data, if you're smart about curation and resampling.
