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The authors introduce a new benchmark, CODETASK-CL, which covers a wide range of tasks including code generation, translation, summarization, and refinement. They then evaluate popular CL techniques from the Natural Language Processing (NLP) and Vision domains on this benchmark.

One of the key findings is that a popular CL method, Prompt Pooling (PP), suffers from catastrophic forgetting due to the unstable training of the prompt selection mechanism caused by stark distribution shifts in coding tasks. C