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🎉 Our work on attribution in summarization is now accepted to #EMNLP2025 main! 🎉 "Unstructured Evidence Attribution for Long Context Query Focused Summarization" w/ @zainmujahid.me , Lu Wang, @iaugenstein.bsky.social , and @davidjurgens.bsky.social

💡 Normally when automatically generated summaries cite supporting evidence, they cite fixed-granular evidence e.g., individual sentences or whole documents. Our work proposes to extract spans of *any* length as more relevant and consistent evidence for long context query focused summaries.

🦾 We demonstrate across 5 LLMs and 4 datasets that LLMs adapted with SUnsET generate more relevant and factually consistent evidence, extract evidence from more diverse locations in their context, and can generate more relevant and consistent summaries than baselines.