When the Harness Carries the Model

arXiv cs.AI - Research Science (GLOBAL)

Article Gal Bakal

Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Development - arXiv:2603.14805v2 Announce Type: replace Abstract: Enterprise software organizations accumulate critical...

arxiv.org/abs/2603.14805 →

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Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Development - arXiv:2603.14805v2 Announce Type: replace Abstract: Enterprise software organizations accumulate critical...

Context

This paper directly addresses the bottleneck of 'institutional knowledge' for agentic development, a core topic. It proposes a structured framework (AKUs) that changes how agents interact with enterprise context.

Key points

• This paper directly addresses the bottleneck of 'institutional knowledge' for agentic development, a core topic. It proposes a structured framework (AKUs) that changes how agents interact with enterprise context.

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Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Kokil Jaidka, Saifuddin Ahmed

How Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment - arXiv:2606.05256v1 Announce Type: new Abstract: This study analyzes a publicly released dataset from a discontinued...

arxiv.org/abs/2606.05256 →

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How Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment - arXiv:2606.05256v1 Announce Type: new Abstract: This study analyzes a publicly released dataset from a discontinued...

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Analyzes LLM agents' persuasive tactics in a real-world debate setting (Reddit), directly addressing AI power dynamics and epistemic control.

Key points

• Analyzes LLM agents' persuasive tactics in a real-world debate setting (Reddit), directly addressing AI power dynamics and epistemic control.

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Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Chen Huang, Yuhao Wu, Wenxuan Zhang

What Should Agents Say? Action-state Communication for Efficient Multi-Agent Systems - arXiv:2606.05304v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on large language models are typically organized...

arxiv.org/abs/2606.05304 →

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What Should Agents Say? Action-state Communication for Efficient Multi-Agent Systems - arXiv:2606.05304v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on large language models are typically organized...

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This paper proposes PACT, a method to structure inter-agent communication for efficiency and performance in MAS. It directly impacts agentic coding tools and AI infrastructure costs.

Key points

• This paper proposes PACT, a method to structure inter-agent communication for efficiency and performance in MAS. It directly impacts agentic coding tools and AI infrastructure costs.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Matheus Kunzler Maldaner, Adam Fourney, Amanda Swearngin, Hussein Mozzanar, Gagan Bansal, Maya Murad, Rafah Hosn, Saleema Amershi

SentinelBench: A Benchmark for Long-Running Monitoring Agents - arXiv:2606.05342v1 Announce Type: new Abstract: AI agents are increasingly asked to carry out work that spans minutes, hours, or longer. Yet the default...

arxiv.org/abs/2606.05342 →

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SentinelBench: A Benchmark for Long-Running Monitoring Agents - arXiv:2606.05342v1 Announce Type: new Abstract: AI agents are increasingly asked to carry out work that spans minutes, hours, or longer. Yet the default...

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Introduces a new benchmark (SentinelBench) for long-running monitoring agents, directly addressing agentic coding/practice and AI infrastructure.

Key points

• Introduces a new benchmark (SentinelBench) for long-running monitoring agents, directly addressing agentic coding/practice and AI infrastructure.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Srimonti Dutta, Akshata Kishore Moharir

Stability vs. Manipulability: Evaluating Robustness Under Post-Decision Interaction in LLM Judges - arXiv:2606.05384v1 Announce Type: new Abstract: LLM-as-judge evaluation is widely used in benchmarking pipelines,...

arxiv.org/abs/2606.05384 →

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Stability vs. Manipulability: Evaluating Robustness Under Post-Decision Interaction in LLM Judges - arXiv:2606.05384v1 Announce Type: new Abstract: LLM-as-judge evaluation is widely used in benchmarking pipelines,...

Context

This paper directly challenges a core assumption (stability) in LLM evaluation/benchmarking, impacting how models are measured and deployed.

Key points

• This paper directly challenges a core assumption (stability) in LLM evaluation/benchmarking, impacting how models are measured and deployed.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Zihao Li, Kaifeng Jin, Yuanchen Bei, Jiaru Zou, Avaneesh Kumar, Xuying Ning, Yanjun Zhao, Mengting Ai, Baoyu Jing, Hanghang Tong, Jingrui He

Harnessing Generalist Agents for Contextualized Time Series - arXiv:2606.05404v1 Announce Type: new Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover,...

arxiv.org/abs/2606.05404 →

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Harnessing Generalist Agents for Contextualized Time Series - arXiv:2606.05404v1 Announce Type: new Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover,...

Context

Introduces TimeClaw, an agentic framework for time series analysis, directly addressing AI infrastructure and specialized coding tools.

Key points

• Introduces TimeClaw, an agentic framework for time series analysis, directly addressing AI infrastructure and specialized coding tools.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Yiyou Sun, Xinyang Han, Weichen Zhang, Yuanbo Pang, Tianyu Wang, Yuhan Cao, Yixiao Huang, Chris Duroiu, Haoyun Zhang, Jeffrey Lin, Weishu Zhang, Tyler Zeng, Ying Yan, Bo Liu, Hanson Wen, Mingyang Xu, Xiaoyuan Liu, Zimeng Chen, Weiyan Shi, Amanda Dsouza, Vincent Sunn Chen, Patrick Bryant, Carl Boettiger, Yamini Rangan, Bradley Rothenberg, Kyle Steinfeld, Arvind Rao, Tapio Schneider, Georgios Yannakakis, Laure Zanna, Kaan Ozbay, Ida Sim, Tarek Zohdi, George Em Karniadakis, Jack Gallant, Teresa Head-gordon, Yushan Li, Wenxi Deng, Tao Sun, Huiqi Wang, Zhun Wang, Justin Xu, Chris Yuhao Liu, Yafei Cheng, Rongwang Hu, Aras Bacho, Shengcao Cao, Zengyi Qin, Yixiong Chen, Hengduan Fan, Hao Liu, Lin Zeng, Shashank Muralidhar Bharadwaj, Litian Gong, Yingxuan Yang, Maojia Song, Ruheng Wang, Zongzheng Zhang, Honglin Bao, Shuo Lu, Jianhong Tu, Zhonghua Wang, Zheng Zhang, Zijiao Chen, yanqiong Jiang, Zhendong Li, Bohan Lyu, Chang Ma, Peiran Xu, Benran Zhang, Shangding Gu, Haoyue Hua, Haoyang Li, Wanzhe Liao, Chengzhi Liu, Junbo Peng, Haoran Sun, Zechen Xu, Bo Chen, Jiayi Cheng, Yi Jiang, Keying Kuang, Yuan Li, Youbang Pan, Ziyan Rao, Alexander Schubert, Yifan Shen, Vincent Siu, Xiatao Sun, Kangqi Zhang, Xiaopan Zhang, Yuchen Zhu, Ishaan Singh Chandok, Lei Ding, Jingxuan Fan, Andrew Glover, Jiaming Hu, Yiran Hu, Wenbo Huang, Zixin Jiang, Haoran Jin, Lukas Kim, Ming Liu, Yang Liu, Alireza Rafiei, Xuhuan Shen, Kunyang Sun, Sophia Sun, Ting Sun, Eric Wang, Yixin Wang, Hanwen Xing, Sihan Xu, Yuzheng Xu, Zhongxing Xu, Zhiling Yan, Boqin Yuan, Ruiqi Zhang, Yifan Zhang, Zibo Zhao, Liana, Santanu Bosu Antu, Haoyue Bai, Carlo Bosio, Joseph Cavanagh, Patricia Cavazos-Rehg, Tianxing Chen, Xuewen Chen, Yipu Chen, Zhu Chenyu, Chen Dai, Stefano De Castro, Yunfu Deng, Kaustubh Dhole, Jiayuan Ding, Chenchen Du, Zhehang Du, Hao Fan, Run-ze Fan, Hengyu Fu, Shi Gu, Yifan Gu, Charlie Guo, Baihe Huang, Baixiang Huang, Rimika Jaiswal, Zhihan Jiang, Ran Jin, Erin Kasson, Xin Lan, Joseph Lee, Deren Lei, Chenyu Li, Daofeng Li, Haitao Li, Hongwei Li, Jingyan Li, Xiao Li, Yi Li, Yinsheng Li, Yuangang Li, Zhixu Li, Wenyu Liang, Longtai Liao, Kevin Qinghong Lin, AndyZeyi Liu, Che Liu, Jiaming Liu, Kaiyuan Liu, Xuan Liu, Pan Lu, Wenbo Lv, Yicheng Lv, Qiuyang Mang, Kyle Montgomery, Yuzhou Nie, Ruoxi Ning, Jorin Overwiening, Xu Pan, Layna Paraboschi, Core Francisco Park, Justin Purnomo, Swati Rajwal, Scott Rankin, Bixuan Ren, Yiren Rong, HaoYang Shang, Ventus Shaw, Fiona Shen, Jiawei Shen, Minqi Shi, Qiu Shi, Huaxiu Yao, Tianneng Shi, Jonah So, Vladislav Susoy, Hannah Szlyk, Haocheng Wang, Jialu Wang, Wei Wang, Xinyu Wang, Zehao Wang, Dowling Wong, Angela Wu, Dehao Wu, Fangyu Wu, Mengyuan "Millie" Wu, Yu Wu, Yuchen Wu, Yuhao Wu, Qingpo Wuwu, Weihang Xiao, Yongyi Xiong, Fan Xu, Ruiling Xu, Mingxuan Yan, Benjamin Yang, Jirong Yang, Sen Yang, Xiaoli Yang, Yushi Yang, Haoran Ye, Xiaohu Yu, Zhengming Yu, Chenlong Zhang, Chi Zhang, Hanning Zhang, Hanwen Zhang, Junge Zhang, Kunpeng Zhang, Song Zhang, Wenjin Zhang, Wenshuo Zhang, Ying Zhang, Yizhi Zhang, Brian Zhao, Qijian Zhao, Yimin Zhao, Yuhaohua Zheng, Liwei Zhou, Tianyue Zhou, Sichen Zhu, Siqi Zhu, Yan Zhu, Yishu Zhu, Jierui Zuo, Chonghao Cai, Helena Casademunt, Wenjia Chen, Benjamin Cheng, Nawen Deng, Rao Fu, Tianfu Fu, Yifan Han, Ren He, Zhenyu He, Qiao Jin, Lang Lang, Yuetai Li, Sylvia Liu, Lu Lu, Qing Lu, Subhabrata Mukherjee, Yunqi Ouyang, Yin Ren, Dawei Shi, Haoran Wu, Zhiyue Wu, Hannah Yao, Zhuoran Yi, Jenny Yu, Rhea Zhan, Hang Zhou, Blake Zhu, Junfan Zhu, Alan Yuille, Yang Liu, Russell Alan Poldrack, Jiachen Li, Zhenglu Li, Molei Tao, Jing Huang, Wenqi Shi, Costas Spanos, Lichao Sun, Chenguang Wang, Orson Xu, Zhen Dong, Hector Gomez, Aylin Caliskan, Ali Emami, Haimin Hu, Zhi Li, Lihui Liu, Murphy Niu, Yi Shao, Jianxin Sun, Mikko Tolonen, Ting Wang, Sanjiv Das, Yanjun Gao, Wenbo Guo, Erika J Schneider, Zhiyong Lu, Mark Mueller, Radha Poovendran, Somayeh Sojoudi, Dawn Song

Agents' Last Exam - arXiv:2606.05405v1 Announce Type: new Abstract: Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful...

arxiv.org/abs/2606.05405 →

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Agents' Last Exam - arXiv:2606.05405v1 Announce Type: new Abstract: Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful...

Context

Introduces a new, large-scale benchmark (ALE) focused on economically valuable, real-world tasks and professional domains, directly addressing the gap between benchmarks and GDP-relevant impact.

Key points

• Introduces a new, large-scale benchmark (ALE) focused on economically valuable, real-world tasks and professional domains, directly addressing the gap between benchmarks and GDP-relevant impact.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Can Gurkan, Forrest Stonedahl, Uri Wilensky

Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution - arXiv:2606.05408v1 Announce Type: new Abstract: When an LLM repeatedly mutates a program, does it explore new forms or circle back to...

arxiv.org/abs/2606.05408 →

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Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution - arXiv:2606.05408v1 Announce Type: new Abstract: When an LLM repeatedly mutates a program, does it explore new forms or circle back to...

Context

Directly addresses LLM-driven program evolution and structural bias in code generation, a core topic for agentic coding tools.

Key points

• Directly addresses LLM-driven program evolution and structural bias in code generation, a core topic for agentic coding tools.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Anna Mikeda, Ben Goertzel

A Motivational Architecture for Conversational AGI - arXiv:2606.05411v1 Announce Type: new Abstract: Motivational architectures in cognitive AI have largely been designed for physical agents regulating bodily needs....

arxiv.org/abs/2606.05411 →

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A Motivational Architecture for Conversational AGI - arXiv:2606.05411v1 Announce Type: new Abstract: Motivational architectures in cognitive AI have largely been designed for physical agents regulating bodily needs....

Context

This paper proposes a novel motivational architecture for conversational AGI, directly addressing agentic design and the nature of intelligence control.

Key points

• This paper proposes a novel motivational architecture for conversational AGI, directly addressing agentic design and the nature of intelligence control.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Gianluca Guidi, Francesca Dominici, Tiziano Squartini, Callaway Sprinkle, Jonathan Gilmour, Kevin Butler, Eric Bell, Scott Delaney, Falco J. Bargagli-Stoffi

Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers - arXiv:2606.05420v1 Announce Type: new Abstract: The rapid proliferation of hyperscale data centers (HDCs) in the US, mainly driven.…

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Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers - arXiv:2606.05420v1 Announce Type: new Abstract: The rapid proliferation of hyperscale data centers (HDCs) in the US, mainly driven...

Context

Directly addresses AI infrastructure (energy/emissions) and power dynamics (US grid reliance), a core topic.

Key points

• Directly addresses AI infrastructure (energy/emissions) and power dynamics (US grid reliance), a core topic.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Rayyan Abdalla, Amir Hussein, Min Wu, Dinesh Manocha

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models - arXiv:2606.05429v1 Announce Type: new Abstract: Post-training quantization (PTQ) is critical for the efficient...

arxiv.org/abs/2606.05429 →

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Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models - arXiv:2606.05429v1 Announce Type: new Abstract: Post-training quantization (PTQ) is critical for the efficient...

Context

This is a new arXiv paper detailing an advanced quantization method (SAGE-PTQ) for LLMs, directly addressing inference efficiency and deployment costs.

Key points

• This is a new arXiv paper detailing an advanced quantization method (SAGE-PTQ) for LLMs, directly addressing inference efficiency and deployment costs.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Pierre Peign\'e, Ky Nguyen, Paul Wang

Zero knowledge verification for frontier AI training is possible - arXiv:2606.05433v1 Announce Type: new Abstract: Frontier AI governance frameworks increasingly use cumulative training compute as the primary criterion.…

arxiv.org/abs/2606.05433 →

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Zero knowledge verification for frontier AI training is possible - arXiv:2606.05433v1 Announce Type: new Abstract: Frontier AI governance frameworks increasingly use cumulative training compute as the primary criterion...

Context

Proposes technical solutions (zkVMs, Merkle commitments) to verify frontier AI training compute, directly impacting governance and control.

Key points

• Proposes technical solutions (zkVMs, Merkle commitments) to verify frontier AI training compute, directly impacting governance and control.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Jiateng Liu, Bingxuan Li, Zhenhailong Wang, Rushi Wang, Kaiwen Hong, Cheng Qian, Jiayu Liu, Denghui Zhang, Katherine Driggs-Campbell, Manling Li, Heng Ji

Brick-Composer: Using MLLMs for Assembly with Diverse Bricks - arXiv:2606.05445v1 Announce Type: new Abstract: We dream of AI agents that can read arbitrary designs and construct real-world objects from reusable...

arxiv.org/abs/2606.05445 →

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Brick-Composer: Using MLLMs for Assembly with Diverse Bricks - arXiv:2606.05445v1 Announce Type: new Abstract: We dream of AI agents that can read arbitrary designs and construct real-world objects from reusable...

Context

Directly addresses physical-world AI and agentic capability (building objects). Introduces a new benchmark (BC-Bench) and framework (Brick-Composer), which is core to the field.

Key points

• Directly addresses physical-world AI and agentic capability (building objects). Introduces a new benchmark (BC-Bench) and framework (Brick-Composer), which is core to the field.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Quanyan Zhu

Insurance of Agentic AI - arXiv:2606.05449v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) systems are transforming the risk landscape by extending beyond information generation to autonomous...

arxiv.org/abs/2606.05449 →

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Insurance of Agentic AI - arXiv:2606.05449v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) systems are transforming the risk landscape by extending beyond information generation to autonomous...

Context

Directly addresses the power dynamics (regulation/capital) surrounding agentic AI risk, a core topic of the podcast.

Key points

• Directly addresses the power dynamics (regulation/capital) surrounding agentic AI risk, a core topic of the podcast.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Abhinaw Priyadershi, Mandar Pitale, Jelena Frtunikj, Maria Spence

Output Type Before Quality: A Standards-Derived XAI Admissibility Rubric for Autonomous-Driving Safety - arXiv:2606.05461v1 Announce Type: new Abstract: Safety standards for ML-based autonomous driving specify the kind.…

arxiv.org/abs/2606.05461 →

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Output Type Before Quality: A Standards-Derived XAI Admissibility Rubric for Autonomous-Driving Safety - arXiv:2606.05461v1 Announce Type: new Abstract: Safety standards for ML-based autonomous driving specify the kind...

Context

This paper defines a structural rubric for XAI in autonomous driving safety, linking ML outputs to regulatory standards (ISO/automotive). This directly impacts physical-world AI and liability.

Key points

• This paper defines a structural rubric for XAI in autonomous driving safety, linking ML outputs to regulatory standards (ISO/automotive). This directly impacts physical-world AI and liability.

Provenance

Article · Supporting source

arXiv cs.AI - Research Science (GLOBAL)

Article Kuangshi Ai, Haichao Miao, Kaiyuan Tang, Shusen Liu, Chaoli Wang

SciVisAgentSkills: Design and Evaluation of Agent Skills for Scientific Data Analysis and Visualization - arXiv:2606.05525v1 Announce Type: new Abstract: Recent advances in agentic visualization have enabled the...

arxiv.org/abs/2606.05525 →

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SciVisAgentSkills: Design and Evaluation of Agent Skills for Scientific Data Analysis and Visualization - arXiv:2606.05525v1 Announce Type: new Abstract: Recent advances in agentic visualization have enabled the...

Context

This paper introduces reusable agent skills for scientific visualization (SciVis), directly addressing agentic coding tools and advanced AI infrastructure/capabilities.

Key points

• This paper introduces reusable agent skills for scientific visualization (SciVis), directly addressing agentic coding tools and advanced AI infrastructure/capabilities.

Provenance

Article · Supporting source

Latent Space · 40m41s

Video Latent Space

⚡️Making DeepSeek v4 outperform Opus 4.7 with Taste — @AhmadAwais , CommandCode.ai — https://x.com/MrAhmadAwais/status/2050956678502420612 We sit down with Ahmad Awais, CEO of CommandCodeAI, who developed a lightweight…

www.youtube.com/watch?v=-rIAVuaRjOg →

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⚡️Making DeepSeek v4 outperform Opus 4.7 with Taste — @AhmadAwais , CommandCode.ai — https://x.com/MrAhmadAwais/status/2050956678502420612 We sit down with Ahmad Awais, CEO of CommandCodeAI, who developed a lightweight…

Context

Directly addresses agentic coding tools and AI infrastructure (tool-calling reliability/repair logic), a core topic.

Key points

• Directly addresses agentic coding tools and AI infrastructure (tool-calling reliability/repair logic), a core topic.

Provenance

Video · Supporting source

r/ClaudeAI: Anthropic Just Published a Major Update on Recursive Self-Improvement: AI Is Already Accelerating Its Own Development (May 2026) - 0 pts · 0 comments

Article nullvector88

Anthropic just dropped a really interesting new piece called “When AI builds itself.” They go deep into how they’re handing over more and more of their own AI development to the AI systems themselves. The numbers...

www.reddit.com/r/ClaudeAI/comments/1ty8f47/… →

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Anthropic just dropped a really interesting new piece called “When AI builds itself.” They go deep into how they’re handing over more and more of their own AI development to the AI systems themselves. The numbers...

Context

Directly discusses AI acceleration, agentic coding tools, and self-improvement, hitting multiple core topics.

Key points

• Directly discusses AI acceleration, agentic coding tools, and self-improvement, hitting multiple core topics.

Provenance

Article · Supporting source

Techmeme - Industry Adjacent (US)

Article

Inside the Trump admin's push to integrate AI into the healthcare system, including an FDA regulatory fast track for digital health tech like AI chatbots (Elizabeth Dwoskin/Washington Post) - Elizabeth Dwoskin /...

www.techmeme.com/260606/p5 →

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Inside the Trump admin's push to integrate AI into the healthcare system, including an FDA regulatory fast track for digital health tech like AI chatbots (Elizabeth Dwoskin/Washington Post) - Elizabeth Dwoskin /...

Context

Directly addresses policy (FDA/Trump admin) and physical-world application (healthcare), impacting regulation and market structure.

Key points

• Directly addresses policy (FDA/Trump admin) and physical-world application (healthcare), impacting regulation and market structure.

Provenance

Article · Supporting source

r/LocalLLaMA: DeepSeek V4 Flash is amazing! (WIP llama.cpp PR #24162) - 0 pts · 0 comments

Article Lowkey_LokiSN

In case you're not aware already, the DeepSeek V4 series is finally getting supported on llama.cpp with this PR! The PR is at a very early stage right now, so only try it if you're consciously willing to experiment out.…

www.reddit.com/r/LocalLLaMA/comments/1tyb3n… →

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In case you're not aware already, the DeepSeek V4 series is finally getting supported on llama.cpp with this PR! The PR is at a very early stage right now, so only try it if you're consciously willing to experiment out...

Context

The post announces a working implementation of a frontier model (DeepSeek V4 Flash) for local inference via llama.cpp, directly addressing AI infrastructure and model capability.

Key points

• The post announces a working implementation of a frontier model (DeepSeek V4 Flash) for local inference via llama.cpp, directly addressing AI infrastructure and model capability.

Provenance

Article · Supporting source