#categorical-data News & Analysis

3 articles tagged with #categorical-data. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBearisharXiv – CS AI · Jun 117/10

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Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data

Researchers identify a fundamental limitation in large language models' ability to adapt to structured data through in-context learning, discovering that LLMs fail to update their categorical token distributions learned during pre-training even with additional examples. While parameter-efficient fine-tuning overcomes this constraint, it introduces memorization risks and potential instability in structured output generation.

AIBullisharXiv – CS AI · Jun 106/10

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Optimality of FSQ Tokens for Continuous Diffusion for Categorical Data with Application to Text-to-Speech

Researchers demonstrate that FSQ (Finite Scalar Quantization) tokenization optimally structures latent space for continuous diffusion models applied to categorical data, offering a non-autoregressive alternative to large language models. Text-to-speech experiments validate FSQ's superiority, achieving better performance than LLM-based approaches while requiring smaller model sizes and faster inference.

AINeutralarXiv – CS AI · May 296/10

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Masked Diffusion Modeling for Anomaly Detection

Researchers propose MaskDiff-AD, a novel anomaly detection method using masked diffusion models that operates on categorical and discrete data without requiring reverse-time sampling. The approach demonstrates competitive or superior performance compared to existing anomaly detection baselines across tabular and text datasets.