NorthCUA Technical Report: Turbocharging Computer-Use Agents through Experience at Scale
Scaling computer-use agents from individual actions to complex software work requires experience that connects
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10 件Scaling computer-use agents from individual actions to complex software work requires experience that connects
Unified Multimodal Models (UMMs) achieve remarkable success on diverse multimodal understanding and generation
Short-video search needs compact query rewriters that recover users' personalized intent from ambiguous querie
A capable voice assistant must do more than recognize words; it must understand requests, reason over context,
Across coding, web, and tool-use tasks, language-model agents are now routinely trained with the same recipe:
Foundation models are typically trained in stages: pretraining, midtraining, supervised fine-tuning (SFT), and
While frontier vision-language models demonstrate strong capabilities in user interface (UI) navigation, their
Metis is a bet that better data, better training methods and new architectures can buy what a bigger parameter
Scaling supervised training for working agents requires diverse professional tasks that yield reliable expert
Many Indian banks serve customers through FAQ pages and scripted chatbots. Assistants based on language models