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Whitetree is a Python library for exact Mahalanobis nearest-neighbour search on low-dimensional sensor data, using multiple KD-trees to handle inserts and deletes efficiently without rebuilding. Benchmarks show it significantly outperforms alternatives like sklearn's BallTree and FAISS in dynamic scenarios.
This paper shows that the Johnson–Lindenstrauss lemma can be uninformative about retained geometry in high dimensions and derives exact limits for features like distance recovery, nearest-neighbor rankings, and covariance shape in Gaussian models.
ASK-NN is an asymmetric nearest-neighbor test for detecting distribution drifts between reference and query samples, with applications to LLM hallucination detection and artificial-text detection. It is computationally efficient, has theoretical guarantees, and performs competitively against baselines on synthetic and real-world benchmarks.
This paper introduces Layer-wise Representation Dynamics (LRD), a framework with three measurement families to analyze how hidden states change across layers in language models. Applied to 31 models on 30 MTEB tasks, LRD reveals architectural differences and enables label-free model selection and inference-time layer pruning.