C-DIC achieves stable latency and perplexity over hundreds of dialogue turns via incremental per-thread compression with cross-turn revision.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages =
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A systematic analysis of 284 manually reviewed papers plus 1.8k+ others from 2023-2025 reveals under-reporting of human evaluation study design details, creating ambiguity in what was measured and how.
Slipstream uses asynchronous compaction with trajectory-grounded judge validation to improve long-horizon agent accuracy by up to 8.8 percentage points and reduce latency by up to 39.7%.
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Context-Driven Incremental Compression for Multi-Turn Dialogue Generation
C-DIC achieves stable latency and perplexity over hundreds of dialogue turns via incremental per-thread compression with cross-turn revision.
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A systematic analysis of 284 manually reviewed papers plus 1.8k+ others from 2023-2025 reveals under-reporting of human evaluation study design details, creating ambiguity in what was measured and how.