arxiv
PublishedSeptember 29, 2026 at 4:00 AM
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Highlight-Then-Summarize: Learning to Compress Evidence for Long-Context Understanding
Publisher summary· verbatim
arXiv:2609.31382v1 Announce Type: cross Abstract: Long-context understanding requires large language models (LLMs) to reason over lengthy documents, conversations, and code, yet task-relevant evidence is often sparse and scattered amid substantial irrelevant and redundant content. We propose Highlig
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Originally published on arxiv ↗