{
  "timestamp": "2026-09-17T08:00:00Z",
  "papers": [
    {
      "arxiv_id": "2609.19134",
      "title": "ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments",
      "authors": "Hejia Geng, et al.",
      "published": "2026-09-16",
      "url": "https://arxiv.org/abs/2609.19134",
      "repo": "https://github.com/aitofound/ScienceIDE",
      "summary": "We introduce ScienceIDE, infrastructure for turning the world's scientific code into programmable environments for scientific agents. Guided by expert-defined scientific cases and acceptance criteria, agents transform repositories into executable environments that support task generation, execution, and scientific verification. These environments provide a shared foundation for supervised fine-tuning, reinforcement learning, and evaluation."
    },
    {
      "arxiv_id": "2609.19128",
      "title": "Cognitive Extensions for Dual-Process Language Agents: Memory and Self-Reflection in Interactive Environments",
      "authors": "João Meneses dos Santos, Arlindo L. Oliveira",
      "published": "2026-09-16",
      "url": "https://arxiv.org/abs/2609.19128",
      "summary": "We extend SwiftSage, a dual-process agent that combines a fast action proposer with a slower planner, using two modular cognitive extensions: an Adaptive Memory Module (AMM) for salience-gated episodic storage and trigger-driven retrieval, and a Self-Reflection Module (SRM) for bounded execution-time validation and corrective intervention."
    },
    {
      "arxiv_id": "2609.19100",
      "title": "Characterizing Network Centralization and Observability in the Remote MCP Ecosystem",
      "authors": "Muhammad Abdullah Sohail",
      "published": "2026-09-16",
      "url": "https://arxiv.org/abs/2609.19100",
      "summary": "The Model Context Protocol (MCP) has emerged as the dominant interface for connecting autonomous agents to external data sources. The empirical results identify a Security-Observability Tradeoff observed in the current ecosystem: the platform-level authentication mechanisms that secure the majority of servers simultaneously limit automated vulnerability scanning capabilities, constraining the ability of AI gateway operators to assess tool-poisoning vectors."
    },
    {
      "arxiv_id": "2609.18820",
      "title": "Compositional Policy Violations: When Step-Level Compliance Fails In Agentic AI Workflows",
      "authors": "Ashwini Kurady, Sri Sai Charith Grandhi, Rajesh Gupta, Sumit Mamoria",
      "published": "2026-09-16",
      "url": "https://arxiv.org/abs/2609.18820",
      "summary": "We define CPVs as the failure of step-level compliance to compose, and present a taxonomy of four types: Authority Creep, Threshold Laundering, Cumulative Sum Violation, and Context Collapse. We then introduce a provenance-aware runtime architecture that evaluates policies over complete execution traces, recomputing guarded quantities from raw provenance rather than the pipeline's derived representation."
    },
    {
      "arxiv_id": "2609.17527",
      "title": "Agentic Societies Need a Social Harness",
      "authors": "Tapan Chugh, Vidushi Singh, Krish Jain, Arvind Krishnamurthy, Ratul Mahajan",
      "published": "2026-09-15",
      "url": "https://arxiv.org/abs/2609.17527",
      "summary": "An agentic society is a collection of AI agents that coordinate autonomously across trust boundaries. We argue that agentic societies need a social harness for inter-agent interactions, in addition to each agent's personal harness, which manages its private context and communication with its principal."
    }
  ]
}