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15 result(s) for “okapi bm25 site terms com pp site www evan off course org site:arxiv.org” · 545 ms

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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

Report GitHub Issue

https://arxiv.org/html/2608.02613v1
6 Ingest Overhead: When Does Structured Memory Pay Off

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
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 Artificial Intelligence New submissions Cross-lists Replacements See recent

Report GitHub Issue

https://arxiv.org/html/2608.03048v1
These results demonstrate that PI-Mem breaks the accuracy–efficiency trade-off in long-context reasoning and provides a scalable approach to complex multi-hop question answering over extremely long documents

1 Introduction

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

1 Introduction

https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands Slack http://bit

Computation and Language

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

[2608.03883] DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM

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

[2104.08663] BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of

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

[2608.03860] SciRet: A Compute-Aware Empirical Study of Retrieval and

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

Computational Engineering, Finance, and Science Aug 2026

https://arxiv.org/list/cs.CE/current
page: fewer | more | all [1] arXiv:2608

[2509.02523v1] Flavors of Moonshine: Tiny Specialized ASR Models for

https://arxiv.org/abs/2509.02523v1
arXiv is committed to these values and only works with partners that adhere to them

[2410.15608v2] Moonshine: Speech Recognition for Live Transcription and

https://arxiv.org/abs/2410.15608v2
arXiv is committed to these values and only works with partners that adhere to them

[2410.15608] Moonshine: Speech Recognition for Live Transcription and

https://arxiv.org/abs/2410.15608
15608] Moonshine: Speech Recognition for Live Transcription and Voice Commands Skip to main content arXiv is now an independent nonprofit

Information Retrieval

https://arxiv.org/list/cs.IR/recent
IR) Tue, 4 Aug 2026 (showing first 34 of 45 entries ) [17] arXiv:2608

Information Retrieval

https://arxiv.org/list/cs.IR/new
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 New submissions Cross-lists Replacements See recent