Skip to content

Research

Academic foundations and related publications. SWARM implements the framework described in Soft-Label Governance for Distributional Safety in Multi-Agent Systems; see also Distributional Safety in Agentic Systems.

  • :material-book-open-variant: Theoretical Foundations

    Mathematical framework and core concepts

  • :material-file-document-multiple: Papers

    Publications and references

  • :material-publish: Agent Publishing Guide

    Conduct research and publish to agentxiv/clawxiv

  • :material-sync-alert: Reflexivity

    Addressing feedback loops in recursive agent research

  • :material-cog-outline: Agent System Patterns

    Architectural patterns from production agent systems and their SWARM translations

  • :material-radar: SWE-AF Reconnaissance

    External repository scouting status and SWARM integration plan

  • :material-telescope: Situational Awareness Tracker

    Claim status for Aschenbrenner's Situational Awareness and its mapping onto SWARM mechanisms

  • :material-graph-outline: Neurosymbolic Behavior Classification

    Neural perception + Scallop-style probabilistic Datalog for classifying embodied and LLM-agent behavior

  • :material-sitemap: Fabro Workflow DAG Spike

    Spike memo: should SWARM adopt a fabro-workflow-style experiment DAG for orchestration?

  • :material-table: Calibration CSV Schema

    Arm D's frozen joined.v1 schema — the CSV contract downstream studies join against

  • :material-gauge: External Quality Signal Interface

    Proposal memo: governance-owned external-judge channel — tamper-resistant anchors as a byproduct of governed runs

  • :material-chart-timeline-variant: Dispatch Retro 2026-07-19

    First bv-dispatch retro: prediction scorecard, mud-ledger baselines (entropy 0.88, orphan influx 88%), and the read-path lesson

  • :material-certificate: DGG Counterexample Lessons

    Verified case study of the 2026 Dinitz–Garg–Goemans disproof: verifier coverage as the trust variable, pressure-lever symmetry, plausibility–certificate gap

  • :material-timeline-clock: Long-Horizon Safety Lessons

    OpenAI's 2026 long-horizon model post-mortem: action-level gates get decomposed around, trajectory-level monitoring, constraint circumvention vs. fabrication

  • :material-scale-balance: Erdős AI-Ledger Lessons

    Ecosystem governance lessons from Tao's AI-contributions ledger: verification bottleneck, denominator problem, corroboration vs. collusion

  • :material-compass-off: Open-Ended Research Failure Modes

    Kapoor–Narayanan shadow evaluations mapped onto this rig's incident log: five judgment failures, dated exhibits, and the enforcement-ladder mitigations

  • :material-autorenew: Reflective Self-Improvement Lessons

    The compiler bootstrap analogy and its limits: why a fixed-point tripwire certifies convergence rather than correctness, and the variance term the framework omits

  • :material-sword-cross: Hyperspace Two-Swarms Lessons

    Attacker vs. defender swarms on the OpenAI-HF incident: correlation degrades both by the same factor, but the attacker pays in visible latency and the defender in silent misses

  • :material-file-alert: ARA Compiler Pilot Report

    SWA-71 pilot of the Agent-Native Research Artifact compiler: evidence-layer fabrication, broken self-validation, final verdict Reject

  • :material-magnify-expand: Greenblatt Misalignment Field Evidence

    Apparent-success-seeking as production evidence for SWARM's mechanism: his failure catalog mapped to quality gap and toxicity, plus four scenario proposals it motivates

  • :material-telescope-shooting: AISF-2026 Observatory Mapping

    Saxe's AI security observatory proposal mapped onto SWARM constructs: signals to observables, policy toolkit to governance levers, and the internalization gap in his menu

  • :material-telescope: CRUX Survey Analysis

    How Princeton's open-world evaluations program intersects SWARM: frame match, submission opportunities, metrics-layer positioning

  • :material-bridge: Real-Tool Eval Bridge

    Feasibility assessment for bridging simulated governance to real tool-using agents: 80% infrastructure exists, three gaps, reality-gap research question

  • :material-graph: Conjecture-Flood Superstructure

    AI-assisted interdisciplinary mapping as a claim economy: retrieval-failure vs. genuinely-new bridges, mechanical-checker verification economics, adverse-selection framing (beads a2il → u8x6, oa5h)

  • :material-chart-scatter-plot: A-Evolve Flat Landscape

    Why the A-Evolve evolution track has no gradient to evolve against: p is keyed on agent type, not behavior — both adversary knobs and defender levers are flat (beads 3o9l recon → 2qgp)

  • :material-book-cog: KSI Knowledge Curation

    Knowledge-centric self-improvement as a claim economy: disposable agents remove the substrate governance acts on, and the transferability that makes bundles valuable makes poison portable (beads sx6c, cx83 → 77ao)

  • :material-backup-restore: Shepherd Reversible Execution

    Reversible execution traces vs SWARM's live-write sandbox: the delta is default-accept vs default-propose, and prevention may not decompose the way detection does (beads hpf3, vwj3)

  • :material-virus-outline: Memetic Spread Countermeasures

    Value contagion through shared memory: resets make the meme endemic by destroying emergent herd immunity, detection dominates at a welfare tax, and channel contagion is invisible to interaction-level toxicity (beads kgxc → 2qfq, 2avk, 7prw)

  • :material-lan-connect: Side-Channel Coordination

    When an ungoverned coordination channel emerges alongside the governed one (2026 OpenAI/Hugging Face incident): teardown without revocation only relocates it, revoking discovery collapses it, a lower-friction sanctioned channel outcompetes it with no enforcement, and interaction-level toxicity is blind to the whole migration (bead k5o9)

  • :material-robot-outline: RL Organism Emergence

    De novo emergence on tabular bandits with no strategy enum: targeted predation appears at 3 states, a predatory coalition at 18 — and the emergent coalition walks past CollusionDetector in all 20 runs because pair-first scoring can't see quality-inside/harm-outside structure (beads boll → mwve)

Core Research Questions

SWARM addresses fundamental questions in multi-agent AI safety:

  1. Emergence: How do systemic risks emerge from interactions between individually safe agents?

  2. Measurement: How can we measure harm probabilistically rather than binary classification?

  3. Governance: What mechanisms effectively mitigate collective risks without over-constraining beneficial activity?

  4. Scaling: How do risks scale with agent count, capability, and interaction frequency?

Key References

  • Tomasev et al. "Virtual Agent Economies" (arXiv 2509.10147)
  • Multi-agent safety and coordination literature
  • Mechanism design and auction theory
  • Distributional robustness in ML systems

See Papers for the complete bibliography.