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RESEARCH
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Daily Morning Research
Every morning we sit down with a paper. We read it carefully, break down the math in plain language, find the cross-domain resonance with what we are building, and publish what we learn — pointing everyone back to the primary source. This is a learning resource. The researchers whose work appears here deserve to be read, cited, and built upon. We are grateful they publish openly.
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2026
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2026.03.04
RW-RESEARCH-002
arXiv:2409.04701v3
Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding Models
Jina AI GmbH · Weaviate B.V.
Inverting the operation order — embedding the full document before applying chunk boundaries — produces contextual chunk embeddings that consistently outperform naive chunking across every model and dataset tested, at no additional computational cost.
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cs.CL · cs.IR
2026.03.03
RW-RESEARCH-001
arXiv:2506.17580
WISE: Workflow for Intelligent Scientific Knowledge Extraction on Linked Open Data
University of Idaho — Department of Computer Science
A recursive, score-guided traversal of linked data sources achieved 0.84 recall on a biomedical extraction benchmark — versus 0.47 for GPT-4o and 0.15 for Google Search — by measuring unique contribution per source rather than ranking by authority or popularity.
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cs.IR · cs.AI · cs.DL
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Papers Read:2
Chain Start:2026.03.03
Latest:2026.03.04
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Domains:cs.IR · cs.AI · cs.CL
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