Spaces:
Sleeping
Sleeping
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>RecallTrace — Architecture</title> | |
| <link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800&family=JetBrains+Mono:wght@400;500;600&display=swap" rel="stylesheet"> | |
| <style> | |
| *, *::before, *::after { margin: 0; padding: 0; box-sizing: border-box; } | |
| :root { | |
| --bg: #0a0a12; | |
| --bg-card: #12121e; | |
| --border: rgba(255,255,255,0.06); | |
| --text: #e2e4ea; | |
| --text-dim: #8b8fa3; | |
| --text-bright: #ffffff; | |
| /* Layer colors */ | |
| --purple: #7c3aed; | |
| --purple-glow: rgba(124,58,237,0.15); | |
| --red: #a83232; | |
| --red-glow: rgba(168,50,50,0.15); | |
| --teal: #0d9488; | |
| --teal-glow: rgba(13,148,136,0.12); | |
| --amber: #d97706; | |
| --amber-glow: rgba(217,119,6,0.12); | |
| --emerald: #059669; | |
| --rose: #e11d48; | |
| --sky: #0284c7; | |
| --indigo: #4f46e5; | |
| --indigo-glow: rgba(79,70,229,0.15); | |
| --dteal: #0f766e; | |
| --dteal-glow: rgba(15,118,110,0.12); | |
| --connector: rgba(255,255,255,0.10); | |
| } | |
| body { | |
| font-family: 'Inter', -apple-system, sans-serif; | |
| background: var(--bg); | |
| color: var(--text); | |
| min-height: 100vh; | |
| overflow-x: hidden; | |
| } | |
| /* ── Page header ── */ | |
| .page-header { | |
| text-align: center; | |
| padding: 48px 24px 12px; | |
| } | |
| .page-header .badge { | |
| display: inline-block; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11px; | |
| font-weight: 600; | |
| letter-spacing: 2px; | |
| text-transform: uppercase; | |
| color: var(--purple); | |
| border: 1px solid rgba(124,58,237,0.3); | |
| border-radius: 100px; | |
| padding: 6px 18px; | |
| margin-bottom: 18px; | |
| background: rgba(124,58,237,0.06); | |
| } | |
| .page-header h1 { | |
| font-size: 36px; | |
| font-weight: 800; | |
| color: var(--text-bright); | |
| letter-spacing: -0.5px; | |
| line-height: 1.2; | |
| } | |
| .page-header h1 span { color: var(--purple); } | |
| .page-header .subtitle { | |
| font-size: 15px; | |
| color: var(--text-dim); | |
| margin-top: 10px; | |
| font-weight: 400; | |
| max-width: 640px; | |
| margin-left: auto; | |
| margin-right: auto; | |
| line-height: 1.55; | |
| } | |
| /* ── Flow container ── */ | |
| .flow { | |
| max-width: 920px; | |
| margin: 0 auto; | |
| padding: 32px 24px 64px; | |
| display: flex; | |
| flex-direction: column; | |
| gap: 0; | |
| } | |
| /* ── Connector line between layers ── */ | |
| .connector { | |
| display: flex; | |
| justify-content: center; | |
| padding: 6px 0; | |
| } | |
| .connector .line { | |
| width: 2px; | |
| height: 32px; | |
| background: linear-gradient(to bottom, var(--connector), rgba(255,255,255,0.04)); | |
| position: relative; | |
| } | |
| .connector .line::after { | |
| content: ''; | |
| position: absolute; | |
| bottom: -4px; | |
| left: 50%; | |
| transform: translateX(-50%); | |
| width: 0; height: 0; | |
| border-left: 5px solid transparent; | |
| border-right: 5px solid transparent; | |
| border-top: 6px solid var(--connector); | |
| } | |
| /* ── Layer card (shared) ── */ | |
| .layer { | |
| background: var(--bg-card); | |
| border: 1px solid var(--border); | |
| border-radius: 16px; | |
| padding: 28px 32px; | |
| position: relative; | |
| overflow: hidden; | |
| transition: transform 0.25s ease, box-shadow 0.3s ease; | |
| } | |
| .layer:hover { | |
| transform: translateY(-2px); | |
| } | |
| .layer::before { | |
| content: ''; | |
| position: absolute; | |
| top: 0; left: 0; right: 0; | |
| height: 3px; | |
| border-radius: 16px 16px 0 0; | |
| } | |
| /* ── Layer header ── */ | |
| .layer-header { | |
| display: flex; | |
| align-items: center; | |
| gap: 14px; | |
| margin-bottom: 16px; | |
| } | |
| .layer-num { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11px; | |
| font-weight: 600; | |
| letter-spacing: 1px; | |
| padding: 4px 10px; | |
| border-radius: 6px; | |
| flex-shrink: 0; | |
| } | |
| .layer-title { | |
| font-size: 17px; | |
| font-weight: 700; | |
| color: var(--text-bright); | |
| letter-spacing: -0.2px; | |
| } | |
| .layer-tag { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 10px; | |
| font-weight: 500; | |
| padding: 3px 8px; | |
| border-radius: 4px; | |
| margin-left: auto; | |
| flex-shrink: 0; | |
| letter-spacing: 0.5px; | |
| } | |
| /* ── Layer body ── */ | |
| .layer-body { | |
| display: flex; | |
| flex-direction: column; | |
| gap: 8px; | |
| } | |
| .layer-body .item { | |
| display: flex; | |
| align-items: flex-start; | |
| gap: 10px; | |
| font-size: 13.5px; | |
| line-height: 1.55; | |
| color: var(--text); | |
| } | |
| .layer-body .item .dot { | |
| width: 6px; | |
| height: 6px; | |
| border-radius: 50%; | |
| flex-shrink: 0; | |
| margin-top: 7px; | |
| } | |
| .layer-body .item strong { | |
| color: var(--text-bright); | |
| font-weight: 600; | |
| } | |
| .layer-body .item code { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 12px; | |
| background: rgba(255,255,255,0.05); | |
| padding: 2px 6px; | |
| border-radius: 4px; | |
| color: inherit; | |
| } | |
| /* ── Split row (for reward) ── */ | |
| .split-row { | |
| display: grid; | |
| grid-template-columns: 1fr 1fr 1fr; | |
| gap: 12px; | |
| margin-top: 4px; | |
| } | |
| .split-cell { | |
| background: rgba(255,255,255,0.02); | |
| border: 1px solid var(--border); | |
| border-radius: 10px; | |
| padding: 16px 18px; | |
| text-align: center; | |
| } | |
| .split-cell .sc-label { | |
| font-size: 11px; | |
| font-weight: 600; | |
| letter-spacing: 1px; | |
| text-transform: uppercase; | |
| margin-bottom: 6px; | |
| } | |
| .split-cell .sc-value { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 22px; | |
| font-weight: 700; | |
| line-height: 1; | |
| margin-bottom: 4px; | |
| } | |
| .split-cell .sc-desc { | |
| font-size: 12px; | |
| color: var(--text-dim); | |
| line-height: 1.4; | |
| } | |
| /* ── Demo grid (layer 7) ── */ | |
| .demo-grid { | |
| display: grid; | |
| grid-template-columns: 1fr 1fr; | |
| gap: 12px; | |
| margin-top: 4px; | |
| } | |
| .demo-card { | |
| background: rgba(255,255,255,0.02); | |
| border: 1px solid var(--border); | |
| border-radius: 10px; | |
| padding: 16px 18px; | |
| display: flex; | |
| gap: 12px; | |
| align-items: flex-start; | |
| } | |
| .demo-num { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 13px; | |
| font-weight: 700; | |
| width: 28px; | |
| height: 28px; | |
| display: flex; | |
| align-items: center; | |
| justify-content: center; | |
| border-radius: 8px; | |
| flex-shrink: 0; | |
| } | |
| .demo-text { | |
| font-size: 13px; | |
| line-height: 1.5; | |
| color: var(--text); | |
| } | |
| .demo-text strong { color: var(--text-bright); font-weight: 600; } | |
| /* ── Tool columns (layer 3) ── */ | |
| .tool-columns { | |
| display: grid; | |
| grid-template-columns: 1fr 1fr 1fr; | |
| gap: 12px; | |
| margin-top: 4px; | |
| } | |
| .tool-col { | |
| background: rgba(255,255,255,0.02); | |
| border: 1px solid var(--border); | |
| border-radius: 10px; | |
| padding: 16px 18px; | |
| } | |
| .tool-col-title { | |
| font-size: 12px; | |
| font-weight: 700; | |
| letter-spacing: 1px; | |
| text-transform: uppercase; | |
| margin-bottom: 10px; | |
| } | |
| .tool-col .tool-item { | |
| display: flex; | |
| align-items: center; | |
| gap: 8px; | |
| font-size: 13px; | |
| line-height: 1.4; | |
| margin-bottom: 6px; | |
| } | |
| .tool-col .tool-item code { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11.5px; | |
| background: rgba(255,255,255,0.06); | |
| padding: 2px 7px; | |
| border-radius: 4px; | |
| } | |
| .tool-col .tool-item .desc { | |
| font-size: 11.5px; | |
| color: var(--text-dim); | |
| } | |
| /* ── Color variants ── */ | |
| /* Layer 1: Purple */ | |
| .layer.l1 { box-shadow: 0 0 40px var(--purple-glow); } | |
| .layer.l1::before { background: linear-gradient(90deg, var(--purple), #a855f7); } | |
| .layer.l1:hover { box-shadow: 0 0 60px var(--purple-glow); } | |
| .layer.l1 .layer-num { background: rgba(124,58,237,0.15); color: #a78bfa; } | |
| .layer.l1 .dot { background: var(--purple); } | |
| .layer.l1 .layer-tag { background: rgba(124,58,237,0.12); color: #a78bfa; } | |
| /* Layer 2: Red */ | |
| .layer.l2 { box-shadow: 0 0 40px var(--red-glow); } | |
| .layer.l2::before { background: linear-gradient(90deg, var(--red), #c53030); } | |
| .layer.l2:hover { box-shadow: 0 0 60px var(--red-glow); } | |
| .layer.l2 .layer-num { background: rgba(168,50,50,0.18); color: #fc8181; } | |
| .layer.l2 .dot { background: var(--red); } | |
| .layer.l2 .layer-tag { background: rgba(168,50,50,0.15); color: #fc8181; } | |
| /* Layer 3: Teal */ | |
| .layer.l3 { box-shadow: 0 0 40px var(--teal-glow); } | |
| .layer.l3::before { background: linear-gradient(90deg, var(--teal), #14b8a6); } | |
| .layer.l3:hover { box-shadow: 0 0 60px var(--teal-glow); } | |
| .layer.l3 .layer-num { background: rgba(13,148,136,0.15); color: #5eead4; } | |
| .layer.l3 .dot { background: var(--teal); } | |
| .layer.l3 .layer-tag { background: rgba(13,148,136,0.12); color: #5eead4; } | |
| .layer.l3 .tool-col-title { color: #5eead4; } | |
| /* Layer 4: Amber */ | |
| .layer.l4 { box-shadow: 0 0 40px var(--amber-glow); } | |
| .layer.l4::before { background: linear-gradient(90deg, var(--amber), #f59e0b); } | |
| .layer.l4:hover { box-shadow: 0 0 60px var(--amber-glow); } | |
| .layer.l4 .layer-num { background: rgba(217,119,6,0.15); color: #fbbf24; } | |
| .layer.l4 .dot { background: var(--amber); } | |
| .layer.l4 .layer-tag { background: rgba(217,119,6,0.12); color: #fbbf24; } | |
| /* Layer 5: Multi */ | |
| .layer.l5 { box-shadow: 0 0 30px rgba(255,255,255,0.03); } | |
| .layer.l5::before { background: linear-gradient(90deg, var(--emerald), var(--rose), var(--sky)); } | |
| .layer.l5 .layer-num { background: rgba(255,255,255,0.06); color: var(--text); } | |
| /* Layer 6: Indigo */ | |
| .layer.l6 { box-shadow: 0 0 40px var(--indigo-glow); } | |
| .layer.l6::before { background: linear-gradient(90deg, var(--indigo), #6366f1); } | |
| .layer.l6:hover { box-shadow: 0 0 60px var(--indigo-glow); } | |
| .layer.l6 .layer-num { background: rgba(79,70,229,0.15); color: #818cf8; } | |
| .layer.l6 .dot { background: var(--indigo); } | |
| .layer.l6 .layer-tag { background: rgba(79,70,229,0.12); color: #818cf8; } | |
| /* Layer 7: Dark teal */ | |
| .layer.l7 { box-shadow: 0 0 40px var(--dteal-glow); } | |
| .layer.l7::before { background: linear-gradient(90deg, var(--dteal), #0d9488); } | |
| .layer.l7:hover { box-shadow: 0 0 60px var(--dteal-glow); } | |
| .layer.l7 .layer-num { background: rgba(15,118,110,0.15); color: #5eead4; } | |
| .layer.l7 .demo-num { background: rgba(15,118,110,0.2); color: #5eead4; } | |
| /* ── Footer ── */ | |
| .page-footer { | |
| text-align: center; | |
| padding: 24px; | |
| font-size: 12px; | |
| color: var(--text-dim); | |
| font-family: 'JetBrains Mono', monospace; | |
| letter-spacing: 0.5px; | |
| border-top: 1px solid var(--border); | |
| margin-top: 24px; | |
| } | |
| .page-footer span { color: var(--purple); font-weight: 600; } | |
| /* ── Entry animations ── */ | |
| @keyframes fadeUp { | |
| from { opacity: 0; transform: translateY(24px); } | |
| to { opacity: 1; transform: translateY(0); } | |
| } | |
| .layer, .connector { | |
| opacity: 0; | |
| animation: fadeUp 0.5s ease forwards; | |
| } | |
| .flow > :nth-child(1) { animation-delay: 0.08s; } | |
| .flow > :nth-child(2) { animation-delay: 0.16s; } | |
| .flow > :nth-child(3) { animation-delay: 0.24s; } | |
| .flow > :nth-child(4) { animation-delay: 0.32s; } | |
| .flow > :nth-child(5) { animation-delay: 0.40s; } | |
| .flow > :nth-child(6) { animation-delay: 0.48s; } | |
| .flow > :nth-child(7) { animation-delay: 0.56s; } | |
| .flow > :nth-child(8) { animation-delay: 0.64s; } | |
| .flow > :nth-child(9) { animation-delay: 0.72s; } | |
| .flow > :nth-child(10) { animation-delay: 0.80s; } | |
| .flow > :nth-child(11) { animation-delay: 0.88s; } | |
| .flow > :nth-child(12) { animation-delay: 0.96s; } | |
| .flow > :nth-child(13) { animation-delay: 1.04s; } | |
| .page-header { animation: fadeUp 0.5s ease forwards; } | |
| </style> | |
| </head> | |
| <body> | |
| <header class="page-header"> | |
| <div class="badge">Meta PyTorch OpenEnv Hackathon 2025</div> | |
| <h1>Recall<span>Trace</span> — System Architecture</h1> | |
| <p class="subtitle">Causal inference benchmark with adversarial self-play. An agent identifies hidden interventions in partially observable contamination graphs while an adversary adapts the difficulty.</p> | |
| </header> | |
| <div class="flow"> | |
| <!-- ═══ LAYER 1: Causal Graph Engine ═══ --> | |
| <div class="layer l1"> | |
| <div class="layer-header"> | |
| <span class="layer-num">LAYER 1</span> | |
| <span class="layer-title">Causal Graph Engine</span> | |
| <span class="layer-tag">THE REAL INNOVATION</span> | |
| </div> | |
| <div class="layer-body"> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span><strong>Nodes</strong> = lots, warehouses, crossdocks, retailers. <strong>Edges</strong> = shipment and repack events. <strong>Hidden edges</strong> = the inference problem.</span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>Ground truth is a <strong>DAG with latent interventions</strong> — the agent never sees it directly. 30–50% of edges are hidden at episode start.</span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>Each <code>reset()</code> generates a unique procedural graph. No two episodes share the same topology or contamination pattern.</span> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="connector"><div class="line"></div></div> | |
| <!-- ═══ LAYER 2: Hidden Intervention Layer ═══ --> | |
| <div class="layer l2"> | |
| <div class="layer-header"> | |
| <span class="layer-num">LAYER 2</span> | |
| <span class="layer-title">Hidden Intervention Layer</span> | |
| <span class="layer-tag">CAUSAL, NOT CORRELATIONAL</span> | |
| </div> | |
| <div class="layer-body"> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span><strong>3 intervention types</strong> sampled per episode: <code>lot_relabel</code>, <code>mixing_event</code>, <code>record_deletion</code></span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>Agent must infer <strong>which</strong> intervention occurred — not just where contamination spread. This is <strong>causal reasoning</strong>, not graph traversal.</span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>Adversary chooses placement: <strong>source</strong>, <strong>midstream</strong>, or <strong>downstream</strong> nodes. Adds decoys, red herrings, and phantom lots.</span> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="connector"><div class="line"></div></div> | |
| <!-- ═══ LAYER 3: Agent Tool Calls ═══ --> | |
| <div class="layer l3"> | |
| <div class="layer-header"> | |
| <span class="layer-num">LAYER 3</span> | |
| <span class="layer-title">Agent Tool Calls</span> | |
| <span class="layer-tag">3 CATEGORIES</span> | |
| </div> | |
| <div class="tool-columns"> | |
| <div class="tool-col"> | |
| <div class="tool-col-title">🔍 Observe</div> | |
| <div class="tool-item"><code>inspect_node()</code></div> | |
| <div class="tool-item"><span class="desc">Reveals hidden edges and local evidence at a node</span></div> | |
| <div class="tool-item" style="margin-top:6px"><code>trace_lot()</code></div> | |
| <div class="tool-item"><span class="desc">Returns full movement history of a lot ID</span></div> | |
| </div> | |
| <div class="tool-col"> | |
| <div class="tool-col-title">🧠 Hypothesize</div> | |
| <div class="tool-item"><code>cross_reference()</code></div> | |
| <div class="tool-item"><span class="desc">Checks shared origin between two lots</span></div> | |
| <div class="tool-item" style="margin-top:6px"><code>request_lab_test()</code></div> | |
| <div class="tool-item"><span class="desc">Confirms contamination at a specific node</span></div> | |
| </div> | |
| <div class="tool-col"> | |
| <div class="tool-col-title">✅ Commit</div> | |
| <div class="tool-item"><code>quarantine()</code></div> | |
| <div class="tool-item"><span class="desc">Containment action — penalized if target is safe</span></div> | |
| <div class="tool-item" style="margin-top:6px"><code>finalize()</code></div> | |
| <div class="tool-item"><span class="desc">Triggers ground truth evaluation and scoring</span></div> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="connector"><div class="line"></div></div> | |
| <!-- ═══ LAYER 4: Belief State Tracker ═══ --> | |
| <div class="layer l4"> | |
| <div class="layer-header"> | |
| <span class="layer-num">LAYER 4</span> | |
| <span class="layer-title">Belief State Tracker</span> | |
| <span class="layer-tag">THEME 3.1 — WORLD MODELING</span> | |
| </div> | |
| <div class="layer-body"> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>After each tool call, environment returns: <strong>P(edge exists)</strong> per hidden arc, <strong>P(contaminated)</strong> per node.</span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>Agent decides: is this belief <strong>certain enough to quarantine</strong>, or should it spend a step to reduce entropy?</span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>Trained agent learns to <strong>stop gathering evidence</strong> when marginal information gain < step cost. Untrained agent over-explores.</span> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="connector"><div class="line"></div></div> | |
| <!-- ═══ LAYER 5: Composable Reward ═══ --> | |
| <div class="layer l5"> | |
| <div class="layer-header"> | |
| <span class="layer-num">LAYER 5</span> | |
| <span class="layer-title">Composable Reward</span> | |
| </div> | |
| <div class="split-row"> | |
| <div class="split-cell"> | |
| <div class="sc-label" style="color: #34d399;">RECALL</div> | |
| <div class="sc-value" style="color: #34d399;">+2.0</div> | |
| <div class="sc-desc">per unsafe lot correctly quarantined</div> | |
| </div> | |
| <div class="split-cell"> | |
| <div class="sc-label" style="color: #fb7185;">PRECISION</div> | |
| <div class="sc-value" style="color: #fb7185;">−1.5</div> | |
| <div class="sc-desc">per safe lot incorrectly blocked</div> | |
| </div> | |
| <div class="split-cell"> | |
| <div class="sc-label" style="color: #38bdf8;">CALIBRATION</div> | |
| <div class="sc-value" style="color: #38bdf8;">+0.3</div> | |
| <div class="sc-desc">if P(contam) > 0.8 before quarantine</div> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="connector"><div class="line"></div></div> | |
| <!-- ═══ LAYER 6: Adversarial Curriculum ═══ --> | |
| <div class="layer l6"> | |
| <div class="layer-header"> | |
| <span class="layer-num">LAYER 6</span> | |
| <span class="layer-title">Adversarial Curriculum</span> | |
| <span class="layer-tag">THEME 4 — SELF-PLAY</span> | |
| </div> | |
| <div class="layer-body"> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span><strong>Replaces static difficulty tiers.</strong> Adversary agent tracks investigator failure modes and adapts episode generation.</span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span>If agent <strong>over-quarantines</strong> → next episode has more safe stock (decoys, false positives). If agent <strong>under-quarantines</strong> → next episode adds more hidden relabel hops.</span> | |
| </div> | |
| <div class="item"> | |
| <span class="dot"></span> | |
| <span><strong>Recursive skill amplification:</strong> both agents improve simultaneously. The benchmark teaches itself to be harder. Neither agent was told the strategies they discover.</span> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="connector"><div class="line"></div></div> | |
| <!-- ═══ LAYER 7: What Judges See ═══ --> | |
| <div class="layer l7"> | |
| <div class="layer-header"> | |
| <span class="layer-num">LAYER 7</span> | |
| <span class="layer-title">What Judges See</span> | |
| </div> | |
| <div class="demo-grid"> | |
| <div class="demo-card"> | |
| <span class="demo-num">1</span> | |
| <div class="demo-text"> | |
| <strong>Procedural generation</strong> — <code>reset()</code> live: new graph, new hidden intervention sampled, unique topology every episode | |
| </div> | |
| </div> | |
| <div class="demo-card"> | |
| <span class="demo-num">2</span> | |
| <div class="demo-text"> | |
| <strong>World modeling visible</strong> — belief tracker panel shows P(contaminated) rising as agent inspects nodes in real time | |
| </div> | |
| </div> | |
| <div class="demo-card"> | |
| <span class="demo-num">3</span> | |
| <div class="demo-text"> | |
| <strong>Two orthogonal improvements</strong> — F1 curve 0.24→0.79 <em>and</em> belief calibration score rising together over 200 episodes | |
| </div> | |
| </div> | |
| <div class="demo-card"> | |
| <span class="demo-num">4</span> | |
| <div class="demo-text"> | |
| <strong>Learning is legible</strong> — side-by-side: untrained scattershots 6 nodes vs trained agent stops when P > 0.85 with 2 precise quarantines | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| <footer class="page-footer"> | |
| <span>RecallTrace</span> · Causal Inference Under Adversarial Self-Play · Themes 3.1 + 4 + 1 | |
| </footer> | |
| </body> | |
| </html> | |