Summary
Large Chunk Test-Time Training (LaCT) excels in long-context 3D reconstruction but struggles with catastrophic forgetting and overfitting due to its fully plastic inference-time updates, limiting its ability to process arbitrarily long sequences in one pass. Researchers propose Elastic Test-Time Training, inspired by elastic weight consolidation, to stabilize LaCT. This new method aims to address the vulnerabilities and enable more robust handling of extended input sequences.
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