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Continual Learning Futures

Chart pathways beyond static language models by integrating continual learning, hybrid architectures, and on-the-job adaptation.

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Evaluation evolution

Static benchmarks cannot capture ongoing adaptation. Modern approaches include:

  • Streaming benchmarks: Continuously evolving datasets that reflect current events or domain changes.
  • Behavioral diaries: Human evaluators log qualitative observations about model behavior over time.
  • Counterfactual testing: Re-run past prompts to ensure prior knowledge remains intact after updates.
  • Safety regression suites: Automated tests targeting known failure patterns post-update.
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