Isotope Tracer Method for Real-Time Latent Space Diagnostics in Large Language Models
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2026
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| _version_ | 1866901506246049792 |
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| author | Scurin, Pavel |
| author_facet | Scurin, Pavel |
| contents | <p>A computationally efficient method for real-time diagnostic monitoring of large language models using a minimal set of synthetic tracer patterns (isotopes) as reference points in latent space. The method enables operational mode identification, confidence estimation, hallucination detection, and reasoning trajectory visualization without model modification or retraining. Implements the practical instrumentation layer for anchor-based latent cartography through distance-based monitoring during inference.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20128681 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Isotope Tracer Method for Real-Time Latent Space Diagnostics in Large Language Models Scurin, Pavel latent space diagnostics isotope tracer patterns real-time LLM monitoring hallucination detection activation trajectory visualization synthetic anchor examples semantic region mapping void region detection cross-model comparison <p>A computationally efficient method for real-time diagnostic monitoring of large language models using a minimal set of synthetic tracer patterns (isotopes) as reference points in latent space. The method enables operational mode identification, confidence estimation, hallucination detection, and reasoning trajectory visualization without model modification or retraining. Implements the practical instrumentation layer for anchor-based latent cartography through distance-based monitoring during inference.</p> |
| title | Isotope Tracer Method for Real-Time Latent Space Diagnostics in Large Language Models |
| topic | latent space diagnostics isotope tracer patterns real-time LLM monitoring hallucination detection activation trajectory visualization synthetic anchor examples semantic region mapping void region detection cross-model comparison |
| url | https://doi.org/10.5281/zenodo.20128681 |