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Shifting the evaluation of agentic search to a vast, uncurated corpus reveals a dramatic decline in retrieval effectiveness, challenging current models' capabilities.
Reconstructing 3D scenes from images obscured by smoke and extreme darkness is now significantly more achievable, thanks to insights gleaned from the NTIRE 2026 challenge.
NanoKnow reveals that even with external evidence, LLMs are more accurate when answers were seen during pre-training, highlighting the crucial role of parametric knowledge.
