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Hermes 3 Technical Report

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arxiv 2408.11857 v1 pith:TDTFIP4P submitted 2024-08-15 cs.CL

Ryan Teknium , Jeffrey Quesnelle , Chen Guang This is my paper
classification cs.CL
keywords modelshermesinstructabilitiesachievesbasebecomebenchmarks
verification ladder T0 review T1 audit T2 compute T3 formal
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Instruct (or "chat") tuned models have become the primary way in which most people interact with large language models. As opposed to "base" or "foundation" models, instruct-tuned models are optimized to respond to imperative statements. We present Hermes 3, a neutrally-aligned generalist instruct and tool use model with strong reasoning and creative abilities. Its largest version, Hermes 3 405B, achieves state of the art performance among open weight models on several public benchmarks.

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Cited by 12 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling

    cs.AI 2026-08 conditional novelty 7.0 of 10

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  3. Decomposing Behavioral Phase Transitions in LLMs: Order Parameters for Emergent Misalignment

    cs.LG 2025-08 conditional novelty 6.0 of 10

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  4. MELAC: Massive Evaluation of Large Language Models with Alignment of Culture in Persian Language

    cs.CL 2025-08 conditional novelty 6.0 of 10

    MELAC introduces 19 Persian and Iranian-culture evaluation datasets and benchmarks 41 LLMs, showing weak performance on Iranian-specific content.

  5. Hermes 4 Technical Report

    cs.AI 2025-08 conditional novelty 5.0 of 10

    Hermes 4 releases three open-weight reasoning models (14B, 70B, 405B) trained with synthetic data and a length-control SFT stage, evaluated on mathematics, code, knowledge, and alignment benchmarks.

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