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method:autoregressive-modelingautoregressive modeling
Statistical technique where outputs are regressed on previous values; used in language generation
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Methods (1)
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- Autoregressive Samplingrelated_toThe mechanism by which LLMs generate text: drawing a token from the next-token distribution and appending it to context repeatedly
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Second model system studied; used to show why flat autoregressive LLMs struggle with long-range coherence.
- Training objective interpretable as optimizing a diverse set of tasks; thus subject to multitask scaling convergence pressures
- Baseline persistence of any probe direction arising from the autoregressive nature of LLMs, not specific to emotion content
- Transformers are recurrent through autoregression because the K/V stream provides horizontal information flow across positions, even though each forward pass is feedforward.
- The training parallelization technique that latent methods are difficult to train with.
- Autoregressive model unable to converge to a single stored pattern for any finite β (Corollary 2)finding0.775Consequence of Theorem 3 and 1D no-order result
- Class of large language models designed to produce extended chain-of-thought before answering, studied in this paper