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20 result(s) for “okapi bm25 site terms com pp site does could goode com site studies com site:arxiv.org” · 870 ms
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Did you mean okapi bm25 site terms com pp site does could good com site studies com site:arxiv.org?
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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/2607.29281v2
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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/list/cs.CL/new
Recent studies have therefore examined how to automatically derive optimization problems from natural-language descriptions, but existing benchmarks focus on settings where objectives and constraints can be written explicitly as mathematical expressions
https://arxiv.org/html/2608.03703v1
An LETF is a repackaging: it holds the underlying and borrows, and spans no payoff an investor could not construct directly
https://arxiv.org/html/2609.03159v1
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arXiv is now an independent nonprofit
https://arxiv.org/list/cs.AI/new
CL)
Recent studies have identified an ``Artificial Hivemind'' effect in Large Language Models (LLMs) causing models to converge on a narrow, homogenized consensus even for open questions
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/2407.01757v1
Distributed instruments are ubiquitous in Earth science, where they are routinely employed for weather and climate science, seismic studies and resource prospecting, and detection of industrial emissions
https://arxiv.org/list/cs.CV/new
Project Page: this https URL
[2] arXiv:2608
https://arxiv.org/html/2407.17789v2
com/modelscope/agentscope/tree/main/examples/paper_large_scale_simulation to inspire further research and development in large-scale multi-agent simulations
https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands
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https://arxiv.org/list/hep-ph/new
A smooth log-linear trend is given a conditional renormalization-group motivation through dimensional transmutation in a hypothetical asymptotically free confining sector; this motivates, but does not microscopically derive, the mass formula
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/new
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https://arxiv.org/list/eess/new
Comparative case studies under different operating scenarios demonstrate the effectiveness and superiority of the proposed strategy
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/list/cs.IR/recent
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Tue, 4 Aug 2026 (showing first 34 of 45 entries )
[17] arXiv:2608
https://arxiv.org/html/2407.04503v4
While significant research has examined individual LLM behaviors, existing studies have largely overlooked the collective behaviors and information distortions arising from iterated LLM interactions