Prefix Language Modeling › Use Cases for Prefix LM
Michael BrenndoerferUpdated July 14, 20251 min read
Language AI HandbookAll chapters Part 22 of 67Pre-training Objectives
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Prefix LM naturally fits many sequence-to-sequence tasks where the input is fully known before generation begins:
- Machine Translation: The source sentence is the prefix, the target sentence is the target. The full source can be processed bidirectionally, enabling the model to understand the complete meaning before generating the translation.
- Summarization: Long documents form the prefix, and the concise summary is the target. Bidirectional processing of the document captures its full structure before generating a condensed version.
- Question Answering: The context passage and question together form the prefix. The answer is generated as the target. The model can cross-reference question words with passage content bidirectionally.
- Code Generation: Comments or specifications serve as the prefix, and the code implementation is the target. Understanding the full specification before generating code produces more coherent implementations.
- Dialogue: Conversation history is the prefix, and the next response is the target. The model attends to the full conversation before generating a contextually appropriate reply.