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Growing Concerns Over AI Code Quality and Security

The feed has recently focused heavily on the advancements of AI agents and the new challenges they introduce to software development. There is a noticeable technical effort to ensure output reliability, seen in tools like 'depgraph' for detecting latent code debt from AI-generated code or the use of adaptive ensemble methods (COVE) for pre-validating LLM outputs. Furthermore, alongside predictions that AI agents will evolve to autonomously manage aspects of human life, there is a concurrent warning about escalating security risks and infrastructure vulnerabilities, indicating significant uncertainty.

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As of Nov 4, 2026, 11:36 PM UTC

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arXivOctober 15, 2026

The Code of Theseus: Can Agents Rebuild Software from Recovered Design Documents?

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본 연구는 기존 LLM 에이전트가 놓치기 쉬운 요구사항 및 설계 아티팩트를 복구하는 새로운 프레임워크를 제시합니다. 이 프레임워크는 정적 의존성 그래프와 핵심 컨텍스트 파일로부터 이해관계자의 의도, 요구사항, 아키텍처를 추출하여 LLM에게 제공합니다. 이를 통해 코딩 에이전트가 테스트만으로는 포착하기 어려운 설계 수준의 정보를 바탕으로 소프트웨어를 재구성할 수 있음을 입증했습니다.

llm-agent
software-architecture
design-artifacts
code-generation
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Growing Concerns Over AI Code Quality and Security

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Growing Concerns Over AI Code Quality and Security

The Code of Theseus: Can Agents Rebuild Software from Recovered Design Documents?

SWE-Stream: Scaling Executable Training Data for SWE Agents via Progressive Construction and Elastic Streaming

LintEval: Benchmarking LLMs on Linter-Guided File Refactoring

Your Transformer Is Secretly Elastic

Price of Anarchy of First-Price Auctions in Agentic Markets

Co-Evolving Acting and Forecasting for Language Agents

Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance

Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion

Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks

Continuum Attention

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어휘를 두 배로 늘려도 의미는 1.39배에 불과하다

Very impressed with LFM2.5-24-A2B in Pi Agent

State of AI 2026 - AI가 AI를 개발하는 시대, 추론 산업과 물리 AI의 부상

Jev 1.14.0 공개 - 이미지 입력과 긴 컨텍스트 실험 지원

Equal CER, Unequal Damage: Severity-Weighted Character Error Rate for OCR

Lost in Translation: Why Lower Bias Scores Don't Mean Fairer Models

AdaRSI: On-Demand Recursive Self-Improvement for Embodied Agents

ReaDy: Recurrent States as Dynamic Context for Speculative Drafting in Hybrid Linear Attention Large Language Models