Autoregressive Decoding as a Martingale: Characterizing the Stochastic Dynamics of LLM Generation
Large language models (LLMs) have achieved remarkable success across a wide range of language tasks. At their core, autoregressive LLMs are conditional probability models that learn to approximate the next-token distribution given the preceding context. Despite this probabilistic nature, the stochastic dynamics of auto...
Xia-Hui Zhu, Zhen-Yi Qi, Wan-Wei Liu et al.
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