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How can we predict which base checkpoint is worth an expensive round of agentic post-training? End-to-end pass@$K$ tests whether successful behavior already appears in a base model's distribution, but it is a poor fit for agentic coding: many base checkpoints cannot reliably produce the well-formed tool invocation requ...
This work addresses three challenges: finding conversational events in multilingual speech, evaluating their timing without reliable word-level alignment, and judging responses across languages with IndicFDB, which extends it to ten languages spoken in India with 12,350 samples.
This work adapt and enhance preconditioned gradient methods to overcome the practical challenges of large-scale LLM pretraining and proposes algorithmic modifications including per-step QR orthogonalization and improved preconditioning strategies to enable stable training in these regimes.
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