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https://arxiv.org/pdf/2006.01354
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https://arxiv.org/src/2211.01910v2
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https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends

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

1 Introduction

https://arxiv.org/html/2501.13956v1
2 Knowledge Graph Construction 2.1 Episodes 2.2 Semantic Entities and Facts 2.2.1 Entities 2.2.2 Facts 2.2.3 Temporal Extraction and Edge Invalidation 2.3 Communities 3 Memory Retrieval 3.1 Search 3.2 Reranker 4 Experiments 4.1 Choice

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https://arxiv.org/html/2608.03048v1
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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

Information Retrieval

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

[2006.02055] The Art of CPU-Pinning: Evaluating and Improving the

https://arxiv.org/abs/2006.02055
02055] The Art of CPU-Pinning: Evaluating and Improving the Performance of Virtualization and Containerization Platforms Skip to main content arXiv is now an independent nonprofit

Information Retrieval

https://arxiv.org/list/cs.IR/new
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1 Introduction

https://arxiv.org/html/2407.16741v3
2 OpenHands Architecture 2.1 Agent Definition and Implementation 2.2 Agent Runtime: How Execution of Actions Results in Observations 2.3 Agent Skills: The Extensible Agent-Computer Interface 2.4 Agent Delegation: Cooperative Multi-agent

Stress-Relief Annealing: Polynomial-Time Simulation-Free Layout

https://arxiv.org/html/2608.01024v1
Our experimental results show that (1) SRA improves both the throughput and the scalability of a human-designed warehouse, roughly doubling the number of robots it can sustain, (2) it matches or exceeds the throughput of the evolutionary baselines while taking only 1919 minutes on one CPU core, against their 25,00025

Hardware Architecture

https://arxiv.org/list/cs.AR/new
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Distributed, Parallel, and Cluster Computing

https://arxiv.org/list/cs.DC/new
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Multi-robot maze exploration using an efficient cost-utility method

https://arxiv.org/html/2407.14218v1
1 Introduction 2 Related Work 2.1 Socratic Approaches 2.2 Cellular Approaches 2.3 Market-Based Approaches 2.4 Tree & Graph Approaches 2.5 Hybrid Approaches 2.6 Determinstic Approaches 3 Proposed Approach 3.1 Definition of the robotic

Report GitHub Issue

https://arxiv.org/html/2608.02612v1
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Cryptography and Security

https://arxiv.org/list/cs.CR/new
Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Cryptography and Security New submissions Cross-lists Replacements See recent articles Showing new listings for Friday, 7 August 2026

1 Introduction

https://arxiv.org/html/2407.02518v2
2 Related Work 3 INDICT Framework 3.1 Problem Definition 3.2 Safety-driven and Helpfulness-driven Critics 3.3 Autonomous Collaboration between Critics 3.4 Knowledge-grounded Critics with External Tools 3.5 Preemptive and Post-hoc Critic

Very Large-Scale Multi-Agent Simulation in AgentScope

https://arxiv.org/html/2407.17789v2
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Electrical Engineering and Systems Science

https://arxiv.org/list/eess/new
Initially, with the aim of addressing bandwidth extension, this work proposes \(AEROMamba_{P}\), an efficient variant of the AERO super-resolution architecture where attention and LSTM layers are replaced by the Mamba state-space model, and which incorporates a newly developed differentiable perceptual loss derived