Writer’s Post

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🚀 We're excited to share our latest research paper, Writing in the Margins (WiM). Despite advances in larger context windows, AI models still struggle with accuracy and clarity over long prompts. That’s where WiM comes in. WiM improves model performance by over 7.5% in multi-hop reasoning and more than 30% in aggregation tasks, making it super effective for long-context tasks. How does it work? WiM segments inputs into smaller units and creates summaries — like margin notes in a book. These "margins" then guide the model to the most relevant information. 🧠 What you need to know: - It boosts multi-hop reasoning accuracy (HotpotQA, MultiHop-RAG) by 7.5% - It increases F1-score for aggregation tasks (CWE) by over 30% - It improves transparency by displaying margins in real time, showing the reasoning behind responses 👏 Huge kudos to our engineering team for this breakthrough! More exciting research is on the way. For now, see the details here: https://lnkd.in/gQVu2ncA #AI #MachineLearning #Research #Innovation

Paper page - Writing in the Margins: Better Inference Pattern for Long Context Retrieval

Paper page - Writing in the Margins: Better Inference Pattern for Long Context Retrieval

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