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14 result(s) for “okapi bm25 site www eyespy cy site iris who in site:arxiv.org” · 455 ms

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In our context, a message consists of relatively short text (several messages can fit within an LLM context window) along with the associated actor who produced the utterance
from the top result below

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

Report GitHub Issue

https://arxiv.org/html/2608.03048v1
To address these issues, we propose PI-Mem (Parallel-Iterative Memory), a mechanism that processes all chunks in parallel and iteratively refines a shared memory over a bounded number of turns

Report GitHub Issue

https://arxiv.org/html/2608.02613v1
7 Extrapolation across readers for cache-replay backends TTFT rows in Table 3

Computation and Language

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

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
In practice, many field descriptions remain ambiguous or incomplete, as much of the essential context (e

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

https://arxiv.org/abs/2608.03883
All submitted systems follow a staged retrieval design in which BM25 retrieves candidates at scale and semantic or LLM rerankers refine the final rankings

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

https://arxiv.org/abs/2104.08663
Benchmark for Zero-shot Evaluation of Information Retrieval Models, by Nandan Thakur and 4 other authors View PDF HTML (experimental) Abstract:Existing neural information retrieval (IR) models have often been studied in homogeneous and narrow settings, which has considerably limited insights into their out-of

[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

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
In a live A/B test on Shopee Homepage Search, it increases GMV per user by 1

1 Introduction

https://arxiv.org/html/2407.16741v3
2 Agent Runtime: How Execution of Actions Results in Observations 2

Activation-Guided Neuron Intervention to Induce Alzheimer’s-Related

https://arxiv.org/html/2608.03067v1
CL] 04 Aug 2026 Activation-Guided Neuron Intervention to Induce Alzheimer’s-Related Computational Language Phenotypes in a Large Language Model Rui He1,*, Ercong Nie2, Hong Jiang3, Iris E

Distributed Instruments for Planetary Surface Science: Scientific

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

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
CV) Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing