AttnComp: Attention-Guided Adaptive Context Compression for Retrieval-Augmented Generation (2025.findings-emnlp)
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| Challenge: | Existing methods for augmented large language models suffer from irrelevant retrieved content . existing methods struggle to adapt compression rates for different context, maintain low latency . |
| Approach: | We propose an adaptive, efficient and context-aware compression framework to reduce retrieved content . AttnComp uses a top-p compression algorithm to retain the minimal set of documents whose attention weights exceed a threshold. |
| Outcome: | Experiments show that AttnComp outperforms existing compression methods and uncompressed baselines in achieving higher accuracy with substantial compression rates and lower latency. |
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