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A 440MB multilingual translation model now rivals commercial APIs, opening the door for performant on-device translation.
SkillSynth's skill graph approach lets you explicitly control the diversity of execution trajectories during terminal task synthesis, leading to more effective agent training.
On-policy data generation closes the training distribution gap and unlocks +2.54 performance gains at 128K context lengths, proving that LLMs learn best from data that evolves with their capabilities.
Forget rewriting single web pages – WRAP++ unlocks a 10x data scale-up and boosts LLM knowledge by synthesizing QA pairs that demand reasoning across multiple linked documents.
