LMEB
PulseAugur coverage of LMEB — every cluster mentioning LMEB across labs, papers, and developer communities, ranked by signal.
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KaLM-Reranker-V1: Efficient Document Reranking Model Unveiled
Researchers have introduced KaLM-Reranker-V1, a novel document reranking model designed for efficiency and flexibility in retrieval systems. This model decouples query and passage computation, allowing for faster proces…
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KaLM-Reranker-V1: Efficient Document Reranking Model Unveiled
Researchers have introduced KaLM-Reranker-V1, a novel reranking model designed for efficiency in large-scale retrieval systems. This model decouples query and passage computation using an encoder-decoder architecture wi…
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LMEB benchmark evaluates long-horizon memory retrieval beyond traditional passage retrieval
Researchers have introduced the Long-horizon Memory Embedding Benchmark (LMEB), a new evaluation framework designed to assess the capabilities of embedding models in handling complex, long-horizon memory retrieval tasks…