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However, their rigid dataset-specific adaptation inherently restricts cross-site generalization
from the top result below

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
Project Page: this https URL [2] arXiv:2608

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https://arxiv.org/pdf/2608.03833
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https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv

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https://arxiv.org/pdf/2608.00785
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https://arxiv.org/src/2006.01048
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https://arxiv.org/src/2002.02145
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https://arxiv.org/pdf/2410.05779
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https://arxiv.org/src/2006.02085
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Artificial Intelligence

https://arxiv.org/list/cs.AI/new
Extending the pattern-generation paradigm of Neural Cellular Automata (NCA), it navigates the degenerate Boolean search space to satisfy a computational task, rather than regenerating a fixed target state

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https://arxiv.org/pdf/2609.18842
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Report GitHub Issue

https://arxiv.org/html/2608.03063v1
††journalyear: 2027††conference: Proceedings of the 33rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining; August 2027; TBD 1

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https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2608.01785
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https://arxiv.org/pdf/2002.02145
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arXiv

https://arxiv.org/category_taxonomy
Roughly includes material in ACM Subject Classes I

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https://arxiv.org/src/2006.02759
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Report GitHub Issue

https://arxiv.org/html/1802.00050v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

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https://arxiv.org/pdf/2608.03118
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Cryptography and Security

https://arxiv.org/list/cs.CR/new
fewer | more | all New submissions (showing 32 of 32 entries) [1] arXiv:2608

Software Engineering Aug 2026

https://arxiv.org/list/cs.SE/current
301-314 Showing up to 50 entries per page: fewer | more | all [1] arXiv:2608

From SQL Errors to Concept Gaps: An AI-Powered Knowledge Graph Analytics

https://arxiv.org/html/2608.03118v1
org perpetual non-exclusive license arXiv:2608

Report GitHub Issue

https://arxiv.org/html/2608.00785v1
com Abstract Content discovery systems depend on relevance judgment for search quality evaluation, but human annotation faces inter-annotator disagreement and scaling costs

1 Introduction

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

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https://arxiv.org/pdf/2608.02854v1
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https://arxiv.org/pdf/2205.01882v5
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https://arxiv.org/src/2608.03994
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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2608.04008
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https://arxiv.org/pdf/2608.03233
T+jq8 M\c~wD`%::P sC` zzTrH`${0F{kʆƄ endstream endobj 411 0 obj > stream On the Diversity of Analogy Making in Large Language ModelsYuanhao ShenDaniel Xavier de SousaCaio César Sifuentes BarcelosHongyu GuoXiaodan Zhuhttp://arxiv