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30 result(s) for “okapi bm25 site hotchips pp site does apache org site npm org site does ball so site:arxiv.org” of 44 matched · 858 ms
Scope: Nishi’s own index (our crawl + Common Crawl) — not the whole live web. Some sites block all automated crawlers (anti-bot walls), so their pages may be absent here even though we never filter lawful content.
Freshness: no result on this page carries a fetch time yet (indexed before the fetch epoch was stored beside the doc)
The query asks the model to recall the topic of an earlier conversation about Tesla; the gold answer is anchored in one specific session about Pooja’s dig site
from the top result below
https://arxiv.org/html/2608.02613v1
6 Ingest Overhead: When Does Structured Memory Pay Off
https://arxiv.org/html/2608.03048v1
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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/list/cs.AI/new
Research artifact available under the Apache-2
https://arxiv.org/list/math/new
The network switches between the two descriptions only where both are valid and the corresponding fixed linear cascade updates agree, so the switch is exact and requires no multiplication by a variable selector
https://arxiv.org/html/2501.13956v1
2 Knowledge Graph Construction
2.1 Episodes
2.2 Semantic Entities and Facts
2.2.1 Entities
2.2.2 Facts
2.2.3 Temporal Extraction and Edge Invalidation
2.3 Communities
3 Memory Retrieval
3.1 Search
3.2 Reranker
4 Experiments
4.1 Choice
https://arxiv.org/src/2006.02893
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2508.02691
Statistical modeling of SOFR term structureTeemu PennanenWaleed Taoumhttp://arxiv.org/licenses/nonexclusive-distrib/1.0/q-fin.ST endstream endobj 4 0 obj > endobj 5 0 obj > endobj 6 0 obj > endobj 7 0 obj > endobj 8 0 obj > endobj 9 0 obj >
https://arxiv.org/src/2608.03883
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2608.02851v1
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https://arxiv.org/pdf/2005.13905
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https://arxiv.org/pdf/2303.12712v5
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https://arxiv.org/src/2006.01598
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https://arxiv.org/src/2303.12712
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https://arxiv.org/src/2211.01910v2
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https://arxiv.org/pdf/2608.02935
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https://arxiv.org/pdf/2006.04122
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https://arxiv.org/src/2608.04003
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https://arxiv.org/src/2006.02055
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https://arxiv.org/src/2006.02085
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https://arxiv.org/src/2506.01844
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https://arxiv.org/pdf/2006.03178
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https://arxiv.org/src/2006.03594
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https://arxiv.org/list/cs.IR/new
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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/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/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/list/cs.IR/recent
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Wed, 5 Aug 2026