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This paper argues that cosine similarity alone is insufficient evidence for interpretability transfer under quantization in AI models, proposing a method to measure the noise floor and demonstrating that high similarity values may not indicate true preservation.
The article argues that cosine similarity in vector databases is a mathematical property that does not ensure factual accuracy, rendering retrieval systems susceptible to poisoning attacks where malicious documents can surpass legitimate ones in ranking.
The paper proposes locally straightening latent trajectories by maximizing cosine similarity between adjacent velocity vectors to reduce optimization difficulty in world model planning, with experiments on PushT dataset achieving 36% success rate for long-horizon planning.
IMGNet is a face verification model that identifies people using sign patterns instead of cosine similarity, offering a new approach to facial recognition.
The author shares pitfalls from building a shared decision log for AI agent teams, including race conditions exposed by faster models, unreliable contradiction detection with cosine similarity, and challenges in testing multi-agent promises.
This paper demonstrates that cosine similarity is a poor proxy for assessing layer importance in LLMs, and proposes using the actual accuracy drop from layer removal as a more robust metric.
This paper demonstrates that mean-pooled cosine similarity is not length-invariant under anisotropic representations, showing it artificially inflates similarity with sequence length. It argues for using Centered Kernel Alignment (CKA) as a default metric to correct biases in cross-lingual and cross-representation analysis.
A model on Replicate that outputs CLIP ViT-L/14 features for text and images, allowing similarity computation between inputs.