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Hermes 3 Technical Report
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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.
Forward citations
Cited by 9 Pith papers
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OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling
Adding 12% cross-repository code dependency contexts to the long-context fine-tuning mix improves long-range retrieval, state tracking, repo code understanding, and agentic tool use, while largely preserving short-con...
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DynamicMCPBench: A Trace-Grounded, Effect-Scored Benchmark for LLM Agents over Live MCP Servers
A trace-grounded, effect-scored benchmark framework shows that even the strongest LLM agents solve only ~half of live MCP tasks, with accuracy collapsing on longer tool chains.
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Decomposing Behavioral Phase Transitions in LLMs: Order Parameters for Emergent Misalignment
A framework using statistical dissimilarity and LLM judges quantifies what fraction of the behavioral transition during fine-tuning is captured by each order parameter.
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MELAC: Massive Evaluation of Large Language Models with Alignment of Culture in Persian Language
MELAC introduces 19 Persian and Iranian-culture evaluation datasets and benchmarks 41 LLMs, showing weak performance on Iranian-specific content.
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Hermes 4 Technical Report
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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LPCAN: Lightweight Pyramid Cross-Attention Network for Rail Surface Defect Detection Using RGB-D Data
A lightweight RGB-D cross-attention network is proposed for rail defect detection, but the SOTA accuracy and generalization claims are internally inconsistent and the implementation is not public.
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Empowering Nanoscale Connectivity through Molecular Communication: A Case Study of Virus Infection
A position paper proposing molecular communication as the link layer for epidemic-control bio-nano networks, with an ORF3a-based mutation identification simulation; the provided manuscript body does not match this abstract.
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Knowledge-Embedded and Hypernetwork-Guided Few-Shot Substation Meter Defect Image Generation Method
Fine-tuning Stable Diffusion with DreamBooth-style knowledge and hypernetwork-guided crack control maps can synthesize substation meter defect images that boost a YOLOv8 defect detector's mAP when added to the training set.
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Scout: Leveraging Large Language Models for Rapid Digital Evidence Discovery
Scout applies off-the-shelf LLMs and vision models to triage digital evidence, but only anecdotal examples are shown and accuracy is withheld.
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