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a336a4f 84fec84 a336a4f f40318e a336a4f 0538eab | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | # ⚡️ SparseTech
**Redefining LLM reliability for edge AI through variance reduction, sparse knowledge distillation, and probability-domain manifold correction.**
Standard benchmarks measure whether a model is correct; SparseTech measures whether a model is *reliable*. We believe that in agentic and edge AI, **hallucinations live in variance**. Our mission is to crush stochastic variance and stabilize reasoning without relying on massive, server-side inference ensembles.
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## 📚 Foundational Research
We believe models should be built upon a rigorous axiomatic framework recently published in early 2026. You can read our core methodology here:
### The Core Theory
* **[Hallucinations Live in Variance (Jan 2026)](https://huggingface.co/papers/2601.07058)**
*Introduces Semantic Stability (SS) and Paraphrase Consistency (PC@k) as the true metrics for LLM reliability.*
### The Distillation Framework
* **[Sparse Knowledge Distillation: A Mathematical Framework... (Jan 2026)](https://huggingface.co/papers/2601.03195)**
* **[Multi-Teacher Ensemble Distillation (Jan 2026)](https://huggingface.co/papers/2601.09165)**
* **[Recursive Meta-Distillation: An Axiomatic Framework... (Jan 2026)](https://huggingface.co/papers/2601.13100)**
* **[Adaptive Weighting in Knowledge Distillation (Jan 2026)](https://huggingface.co/papers/2601.17910)**
### Advanced Manifold Correction
* **[Post-Training Probability Manifold Correction via Structured SVD Pruning... (Jan 2026)](https://huggingface.co/papers/2602.00372)**
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