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21 result(s) for “okapi bm25 site terms com pp site github com site lemmy world site www irs gov site:arxiv.org” · 732 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
MemArena fills these gaps with a single-world conversational benchmark built with its MASim agent simulator, for 5050 agents over 1515 days (10
https://arxiv.org/html/2608.03048v1
com/JetAstra/PI-Mem
Introduction
The ability to reason over long contexts is increasingly important for large language models (LLMs), supporting applications such as long-document question answering (Gemini Team 2025; Yang et al
https://arxiv.org/html/2501.13956v1
com
Abstract
We introduce Zep, a novel memory layer service for AI agents that outperforms the current state-of-the-art system, MemGPT, in the Deep Memory Retrieval (DMR) benchmark
https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands
Slack http://bit
https://arxiv.org/list/cs.AI/new
SE)
Large language model (LLM) agents increasingly rely on external tools to complete complex real-world tasks
https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2407.00125
Reliability.Performance.- Software and its engineering -> Software organization and properties.- Computing methodologies -> Artificial intelligence.) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False
https://arxiv.org/pdf/2407.00273
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https://arxiv.org/pdf/2005.13905
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https://arxiv.org/pdf/2608.03233
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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/list/cs.CL/new
LG)
Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, leaving a 4,000-year cultural barrier that existing NLP tools have only partially addressed
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
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Information Retrieval
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Wed, 5 Aug 2026
https://arxiv.org/list/cs.IR/new
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https://arxiv.org/html/2607.22511v2
The source code, formal library, and run records are available at https://github
https://arxiv.org/html/2407.02518v2
com
Abstract
Large language models (LLMs) for code are typically trained to align with natural language instructions to closely follow their intentions and requirements
https://arxiv.org/html/2508.16279v1
Such advancements have laid a robust foundation for developing powerful LLM-based agent applications that can effectively interface with the world through a variety of tools, to perform diverse and complex tasks with increased autonomy and precision (Qin et al
https://arxiv.org/pdf/2608.00785
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https://arxiv.org/pdf/2407.00323
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