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Context Shifting in Auto-Regressive Generation
In auto-regressive language modeling, text generation is an iterative process. At every step, after the model generates an output token, this new token is appended to the existing input sequence. This updated, longer sequence then serves as the context for predicting the subsequent token, effectively shifting the model's focus one position forward.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Related
Token Selection from Probability Distribution
Step-by-Step Example of Auto-Regressive Sequence Generation
Mathematical Formulation of Draft Model Prediction in Speculative Decoding
Iterative Context Update in Autoregressive Generation
Key-Value (KV) Cache in Transformer Inference
Sequential Generation of Output Tokens
Context Shifting in Auto-Regressive Generation
A language model is generating a sentence and has so far produced the sequence:
['The', 'cat', 'sat']. Based on the principles of sequential, one-at-a-time token generation where each new token depends on the ones before it, what is the direct input the model will use to determine the next token in the sequence?A language model generates text by producing a single token at each step, using the entire sequence generated so far as the context for the next token. Arrange the following events in the correct chronological order to illustrate the generation of two new tokens following the initial input 'The ocean is'.
A researcher develops a novel text generation model. Given an input like 'The movie was', instead of generating one token at a time, this model predicts the entire completion (e.g., 'incredibly boring and predictable') in a single, parallel step. Which core principle of the standard auto-regressive process is fundamentally violated by this new model's design?
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An auto-regressive language model is provided with the input sequence 'The sun is shining and the'. The model's next step is to generate the token ' birds'. To predict the token that will come after ' birds', what complete sequence will the model use as its new input?
An auto-regressive language model generates text one token at a time. Arrange the following actions into the correct chronological sequence that describes the process of generating one token and preparing for the next.
Debugging a Repetitive Generation Loop