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Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning

Authors

Do you know Peng Du?You can claim authorship or link another user.Do you know Kiran Kamble?You can claim authorship or link another user.Do you know Rakshith Vasudev?You can claim authorship or link another user.Do you know Zhizhuo Yang?You can claim authorship or link another user.Do you know Rohith Nadimpally?You can claim authorship or link another user.Do you know Arjun Krishna?You can claim authorship or link another user.Do you know Waseem Alshikh?You can claim authorship or link another user.Do you know Daniel M. Bikel?You can claim authorship or link another user.

Abstract

Palmyra x6 is a large language model optimized for use with enterprise-oriented agentic tasks. The model was built by post-training a Mixture-of-Experts base model with Anchored Supervised Fine-Tuning on a compact corpus of verified, synthetic tool-use trajectories, optimized with a Muon + Adam hybrid. The recipe is deliberately conservative and deliberately controlled: 626 trajectories, a single epoch, a low learning rate, and a KL anchor to the frozen base. The model shows substantial gains over the previous default model for Writer Agent, and compares favorably with several recent models on public benchmarks, scoring the highest on BFCL Core at $0.785$ and posts the highest six-benchmark mean of the cohort. Furthermore, the model has shown itself to be competitive or leading relative to comparators in our bias and safety evaluations.

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Publication notes

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12 pages