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Related Articles from SNS
Identifying unique developers in OSS projects: A family of models
arXiv:2606.08096v1 Announce Type: new Abstract: Organizational and logical coupling metrics require reliable identification of unique developers. In OSS, commit metadata is limited to names and emails, and the same developer may appear under multiple aliases, which can distort coupling measurements if de-duplication is missing. We aim to build a scalable and accurate pipeline for OSS developer de-duplication and to provide guidance on choosing a model based on precision vs. computational effort.
A Longitudinal Analysis of Good First Issue Practices and Newcomer Pull Requests in Popular OSS Projects
arXiv:2604.27532v2 Announce Type: replace Abstract: Open-source software (OSS) projects rely on effective newcomer onboarding to sustain their communities. OSS projects widely adopt "good first issue" (GFI) labels to highlight beginner-friendly tasks. As development practices continue to evolve, understanding how these onboarding mechanisms change over time is important for both maintainers and researchers.
DRS-OSS: A Diff-Risk Scoring Tool for Continuous Integration Workflows
Announce Type: replace Abstract: Software teams need change-risk scores that can guide continuous integration decisions such as review prioritization, test scheduling, and downstream validation before risky changes are merged or released. However, open-source teams often lack deployable tools for surfacing these risk signals in everyday CI workflows. We present DRS-OSS, an open-source diff-risk scoring tool for continuous integration workflows.
Wall-OSS-0.5 Technical Report
arXiv:2605.30877v2 Announce Type: replace Abstract: Large-scale Vision-Language-Action (VLA) pretraining is increasingly adopted as the foundation for robot policies, yet the evidence for pretrained VLAs is almost invariably reported after task-specific fine-tuning. This leaves a foundational question unanswered: does VLA pretraining itself yield executable robot behavior, or does it merely furnish a better initialization for downstream policy learning? We present Wall-OSS-0.5, an...
Wall-OSS-0.5 Technical Report
Announce Type: new Abstract: Large-scale Vision-Language-Action (VLA) pretraining is increasingly adopted as the foundation for robot policies, yet the evidence for pretrained VLAs is almost invariably reported after task-specific fine-tuning. This leaves a foundational question unanswered: does VLA pretraining itself yield executable robot behavior, or does it merely furnish a better initialization for downstream policy learning? We present Wall-OSS-0.5, an open-source 4B VLA built upon a...
Advancing Digital Government: Integrating Open Source Software Enablement Indicators in Maturity Indexes
arXiv:2510.04603v2 Announce Type: replace Abstract: Context: Open Source Software (OSS) is a vital public good, included across most of modern software stacks, significantly impacting GDP and national tech growth, while supporting interoperability, sovereignty, and transparency. However, systematic measurement of governmental OSS adoption remain limited. Research Aim: This study contributes to digital government maturity indexes by analyzing policies and support actions leveraging OSS for...
Public Sector Open Source Program Offices -- Archetypes for how to Grow (Common) Institutional Capabilities
Announce Type: replace Abstract: Context: Open Source Software (OSS) is a crucial component of over 90\% of digital infrastructure underpinning industry and public digital services, facilitating collaborative software development and dissemination. Its significance in the European public sector has been emphasised through various Ministerial Declarations, highlighting its potential to accelerate digitalisation, transform businesses, and foster a digitally skilled population. Research Aim:...
LLM Consortium for Software Design Refinement: A Controlled Experiment on Multi-Agent Collaboration Topologies
Announce Type: new Abstract: We present a controlled experiment evaluating 12 multi-agent LLM collaboration topologies for software architecture design. Using a $2\times2\times2$ factorial design (Authority $\times$ Roles $\times$ Dynamics), we conducted 520 experimental runs across 8 design tasks of varying complexity, with 5 repetitions each. Designs were evaluated on a 12-dimensional rubric by three independent automated evaluators (GPT-OSS 120B, Claude Opus 4.6, Claude Sonnet 4.6).
Beyond Pass/Fail: Using Process Mining to Understand How LLMs Resist (and Fail) Red Team Attacks
Announce Type: new Abstract: Standard AI red teaming evaluations reduce adversarial campaigns to a single binary outcome, attack success rate (ASR), not taking into account the sequential structure of how models resist or yield to attacks. We propose applying process mining, a discipline for discovering and analyzing process models from event logs, to red teaming traces. We conduct a controlled experiment pitting 60 HarmBench prompts against two LLMs, GPT-OSS 120B and Llama 3.3 70B, using 10...