Summary of Sr-cis: Self-reflective Incremental System with Decoupled Memory and Reasoning, by Biqing Qi et al.
SR-CIS: Self-Reflective Incremental System with Decoupled Memory and Reasoning
by Biqing Qi, Junqi Gao, Xinquan Chen, Dong Li, Weinan Zhang, Bowen Zhou
First submitted to arxiv on: 4 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed Self-Reflective Complementary Incremental System (SR-CIS) aims to address the challenge of human-like rapid knowledge acquisition while retaining old memories in deep learning models. The system comprises a small model for fast inference and a large model for slow deliberation, enabled by the Confidence-Aware Online Anomaly Detection (CA-OAD) mechanism for efficient collaboration. The Complementary Memory Module (CMM) features task-specific Short-Term Memory (STM) and universal Long-Term Memory (LTM) regions, with LoRA and prototype weights/biases enabling external storage for parameter and representation memory. By storing textual descriptions of images during training and combining them with the Scenario Replay Module (SRM) post-training, SR-CIS achieves stable incremental memory with limited storage requirements. The system surpasses existing competitive baselines on multiple standard and few-shot incremental learning benchmarks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper proposes a new way for machines to learn quickly while remembering old things. It’s inspired by how humans learn and remember. The idea is called SR-CIS, which has two parts: one that does fast calculations and another that takes its time to think. There are also special memory modules that help the system remember important information. By combining this information with some additional tricks, SR-CIS can quickly learn new things while still remembering old ones. It’s better than other similar systems at doing this. |
Keywords
» Artificial intelligence » Anomaly detection » Deep learning » Few shot » Inference » Lora
