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11 result(s) for “okapi bm25 site terms com pp site inventaire and fr site:arxiv.org” · 541 ms
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” Gold: “Pooja was dealing with some wild stuff at her dig site and complaining about Tesla parts taking forever
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https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/html/2501.13956v1
3 Temporal Extraction and Edge Invalidation
2
https://arxiv.org/html/2608.03048v1
Iterative Refinement and Exit Mechanism
https://arxiv.org/list/cs.CL/new
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/html/2407.16741v3
2 How OpenHands builds and maintains runtime images
F
https://arxiv.org/list/cs.AI/new
IR)
LLM-based agents are increasingly being deployed for data-related tasks, including data sense-making, exploration, and retrieval
https://arxiv.org/abs/2608.03883
Our systems combine sparse BM25 retrieval, evidence-aware rescoring for self-referential symptom reports, embedding-based reranking, query-prototype expansion, and LLM-based reranking
https://arxiv.org/abs/2104.08663
Our results show BM25 is a robust baseline and re-ranking and late-interaction-based models on average achieve the best zero-shot performances, however, at high computational costs
https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation
https://arxiv.org/list/cs.IR/recent
Includes appendix with proofs and additional experiments
Subjects: Information Retrieval (cs
https://arxiv.org/list/cs.IR/new
IR)
Industrial recommenders increasingly adopt the pretrain-then-transfer paradigm, yet behavioral distribution drift raises two questions: what to learn from behavior sequences, and how to transfer the learned knowledge while the pretrained model is continually refreshed