Web This site Trusted
11 result(s) for “okapi bm25 site hotchips pp site does apache org site as apache org site help splunk site:arxiv.org” · 773 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
A million-token cloud context window does not help here, as it requires off-device upload, which privacy-sensitive personal memory management is meant to avoid
https://arxiv.org/html/2608.03048v1
for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates can overwrite early critical evidence with later irrelevant content, and serial inter-chunk dependencies limit parallelism and cause latency to increase with context length
https://arxiv.org/html/2501.13956v1
In the DMR benchmark, which the MemGPT team established as their primary evaluation metric, Zep demonstrates superior performance (94
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/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/list/cs.IR/new
For what to learn, conventional next-token prediction treats adjacency as dependency and may encode spurious transitions across unrelated sessions
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
Skip to main content
System maintenance August 4th and 5th Learn more ×
Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Information Retrieval
Authors and titles for recent submissions
Wed, 5 Aug 2026
https://arxiv.org/html/2407.16741v3
2024), user-facing AI systems (such as ChatGPT) have become increasingly capable of performing complex tasks such as accurately responding to user queries, solving math problems, and generating code