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MIT License

Copyright (c) 2026 Zhang Ning

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
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The above copyright notice and this permission notice shall be included in all
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About

The superior performance of the DOD framework suggests that transitioning from offline to collaborative online distillation is essential for mitigating recency biases in CL. This research paves the way for more robust and balanced knowledge retention in continual learning scenarios where memory resources are strictly limited.

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