Will DPO or an Explicitly DPO-based Technique be Used to Train a Public Frontier Lab LLM Before Jan 1 2025? | Manifold

Will DPO or an Explicitly DPO-based Technique be Used to Train a Public Frontier Lab LLM Before Jan 1 2025?

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An explicitly DPO-based technique is one that cites DPO as seed material for its creation.

Frontier labs currently include: OpenAI, DeepMind, Anthropic, Google. I will modify this description if this changes (e.g. if Meta releases a SOTA LLM.)

Public simply means that it has been announced or otherwise discovered that this DPO LLM has been trained.

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Related questions

Will a LLM trained with FP4 have frontier-level performance before 2028?

Which next-gen frontier LLMs will be released before GPT-5? (2025)

Will a lab train a >=1e26 FLOP state space model before the end of 2025?

Will any widely used LLM be pre-trained with abstract synthetic data before 2030?

Will researchers extract a novel program from the weights of an LLM into a Procedural/OO programming language by 2026?

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Will we get a new LLM paradigm by EOY?

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