LLM
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NVIDIA LocateAnything Predicts Bounding Boxes in Parallel, Not Token by Token
LocateAnything is an NVIDIA vision-language model built around a single bet: stop generating bounding-box coordinates one token at a time. Visual grounding — pointing a model at “the red mug behind the laptop” and getting back exact pixel coordinates — has typically been autoregressive, emitting each coordinate number in sequence. That’s slow, and the speed… Continue reading
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QUEST Trains Open Deep Research Agents on 8,000 Synthetic Tasks
QUEST is a family of open deep research agents, spanning 2B to 35B parameters, trained to do something most agents still rely on closed APIs for: long-horizon search, fact-seeking, citation grounding, and report synthesis. The headline is the training data — there isn’t any human-labeled set behind it. ## Synthetic tasks, verifiable rewards QUEST is… Continue reading
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