Retrieval
PulseAugur coverage of Retrieval — every cluster mentioning Retrieval across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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Feature stores solve ML training-serving drift and target leakage
Feature stores are essential for production machine learning, addressing the critical problem of feature definition drift between training and serving environments. This drift can silently degrade model performance, par…
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DART architecture enhances long-context sequence modeling by merging Transformers and SSMs
Researchers have introduced DART (Decoded Attention over Recurrent States), a novel architecture that combines the strengths of Transformers and State Space Models (SSMs) for efficient long-context sequence modeling. DA…
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Cologne Information Retrieval group presents agentic conversational search system
Researchers from the Cologne Information Retrieval group have developed an agentic conversational search system for the iKAT SCAI 2026 shared task. This system incorporates tools for query rewriting, retrieval, rerankin…
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New research questions spectral analysis for time-series forecasting
Two recent arXiv papers explore the limitations of using spectral analysis for time-series forecasting, particularly when incorporating external context. The first paper introduces CAF-7M, a large dataset designed to im…
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New benchmarks evaluate Portuguese text embedding models, revealing performance gaps
Two new benchmarks, MTEB-PT and MTEB-PT (Brazilian Portuguese), have been released to evaluate text embedding models specifically for the Portuguese language. These benchmarks address the underrepresentation of Portugue…
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LLM context windows are not knowledge bases; strategic selection is key
The article argues that simply increasing the context window size of an LLM does not equate to effective context engineering. Instead, it emphasizes the importance of strategically selecting and presenting the most rele…