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Evaluating Model Adaptation Strategies for Long-Context Tasks
A research lab has a language model that was initially trained on short documents using a standard attention mechanism where every word is compared to every other word. This process is computationally expensive. The lab now needs to adapt this model to analyze very long legal transcripts, but they have a strict, limited budget for computation.
They are considering two approaches:
Approach 1: Continue training the original model on the long legal transcripts without changing its internal architecture.
Approach 2: Use the original model's learned parameters to initialize a new, architecturally different model. This new model would use a more efficient 'sparse' attention mechanism (where each word is only compared to a subset of other words) and would then be trained on the legal transcripts.
Given the lab's severe budget constraints, which approach is the more justifiable choice? Defend your selection by evaluating the computational cost and potential effectiveness of each approach for handling long documents.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Evaluation in Bloom's Taxonomy
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Evaluating Model Adaptation Strategies for Long-Context Tasks
A team is adapting a language model, originally pre-trained with a standard full attention mechanism, to handle tasks involving extremely long text sequences. Their strategy is to replace the full attention with a more computationally efficient sparse attention mechanism and then fine-tune the model on their long-context dataset. What is the primary reason for using the original model's parameters to initialize this new sparse-attention model, instead of starting the fine-tuning process with randomly initialized parameters?
A research team is adapting a pre-trained language model to handle tasks requiring the analysis of very long documents, such as legal contracts. Their strategy involves modifying the model's architecture for greater efficiency. Arrange the following steps in the correct chronological order to execute this adaptation method.