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Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment Agentic Proving for Program Verification MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework Benchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts Solving the Aircraft Disassembly Scheduling Problem Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem Asking For An Old Friend: Diagnosing and Mitigating Temporal Failure Modes in LLM-based Statutory Question Answering EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction Naturalistic measure of social norms alignment Articulatory strategy as a source of variation in acoustic vowel dynamics When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning Cultural Adaptation in Large Language Models for Political Discourse Emotion Recognition in Sign Language Conversation ClimateChat-300K: A Multi-Modal Facebook Dataset for Understanding Diverse Perspectives in Climate Communication AraHopeCorpus: Annotation Guidelines and Dataset for Hope Speech in Arabic Social Media Crisis Discourse Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning DART: Semantic Recoverability for Structured Tool Agents Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems Parallel Context Compaction for Long-Horizon LLM Agent Serving
Building Digital Societies as Ecosystems: How Recognition...
[Submitted on 24 May 2026 (v1), last revised 16 Aug 2026 (this v · 2026-05-24 · via cs updates on arXiv.org

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Abstract:We measure cross-boundary collaboration in an open-source software (OSS) ecosystem by reconstructing the bipartite contributor-repository graph of 464 cybersecurity projects and 11,372 contributors active over October 2001-May 2022 (Rawsec Cybersecurity Inventory). Louvain community detection identifies 163 non-singleton communities; per-community contributor count scales superlinearly with repository count (n_contributors ~ n_repos^1.4), and community formation follows a logistic trajectory saturating around 2018. Three patterns support a recognition/repeat-relationship account of cross-boundary work. First, cross-community work concentrates in a thin carrier layer: only nine canonical humans span seven or more communities at the commit level, authoring 14% of 4,015 inter-community merged pull requests; the top 50 cross-community contributors produce 54%. Second, boundary friction is a recognition cost, not a fixed boundary property: inter-community pull-request acceptance rises from 42% at breadth k=1 to 87% at k=5-9, with median latency compressing from 147 h to 49 h. Third, community survival is cohort-structured: per-cohort residualisation hazard rises an order of magnitude between pre-2010 and 2018 cohorts, and external community reach predicts survival mainly through size, leaving late cohorts under-served despite a stable carrier layer. The corpus predates mainstream LLM coding assistants; this baseline of carrier-layer thinness, friction gradient, and cohort hazard informs debates on social coding as a template for digital societies and on what AI-mediated OSS ecosystems should not optimise away.

Submission history

From: Thomas Maillart [view email]
[v1] Sun, 24 May 2026 13:04:24 UTC (4,127 KB)
[v2] Sun, 16 Aug 2026 09:46:26 UTC (4,132 KB)