{
  "metadata": {
    "source": "Kaiming He Papers Analysis",
    "date": "2026-01-26",
    "papers_analyzed": 11,
    "analysis_method": "Text extraction and pattern mining",
    "latest_addition": {
      "papers": ["Mean Flows", "ViTDet", "MoCo v2", "Deconstructing Denoising Diffusion Models", "Autoregressive Image Generation (MAR)"],
      "extraction_date": "2026-01-26",
      "new_knowledge_files": [
        "theory-driven-papers-kaiming-he.md",
        "design-simplification-papers-kaiming-he.md"
      ]
    }
  },
  "knowledge_files": {
    "structure.md": {
      "status": "updated",
      "last_update": "2026-01-26",
      "contains": "Basic structure patterns from 19 Kaiming He papers"
    },
    "writing-techniques.md": {
      "status": "needs_update",
      "last_update": "2026-01-26",
      "contains": "Basic writing techniques from 19 Kaiming He papers"
    },
    "rethinking-papers-kaiming-he.md": {
      "status": "complete",
      "focus": "Rethinking papers, challenging conventional wisdom",
      "source_paper": "Autoregressive Image Generation without Vector Quantization (NeurIPS 2024 Spotlight)"
    },
    "theory-driven-papers-kaiming-he.md": {
      "status": "new",
      "focus": "Theory-driven papers, first principles, MeanFlow Identity",
      "source_paper": "Mean Flows for One-step Generative Modeling (2025)"
    },
    "design-simplification-papers-kaiming-he.md": {
      "status": "new",
      "focus": "Design simplification, minimal adaptations, 'Surprisingly' findings",
      "source_paper": "Exploring Plain Vision Transformer Backbones for Object Detection (ViTDet, ECCV 2022)"
    }
  },
  "patterns_extracted": {
    "introduction_frameworks": {
      "principle_introduction": {
        "source": "MeanFlows",
        "pattern": "Background → Problem → Critique (Despite...) → Core Concept → Theory → Advantage → Results",
        "keywords": ["principled", "intrinsic", "well-defined", "naturally", "first principles"]
      },
      "challenge_assumptions": {
        "source": "ViTDet",
        "pattern": "Traditional → New Challenge → Common Solution → Our Direction → Philosophy → Surprisingly → Implications",
        "keywords": ["minimal adaptations", "sufficient", "decouple", "independence", "surprisingly"]
      },
      "rethinking_conventional_wisdom": {
        "source": "MAR",
        "pattern": "Conventional wisdom → Question → Analysis → Alternative → Results → Vision",
        "keywords": ["Conventional wisdom holds that", "Is it necessary", "not a necessity"]
      }
    },
    "surprisingly_findings": {
      "level_1": {
        "pattern": "Surprisingly, we observe: (i)... and (ii)...",
        "usage": "First-level surprise - basic findings",
        "example": "ViTDet Abstract"
      },
      "level_2": {
        "pattern": "More surprisingly, under some circumstances...",
        "usage": "Second-level surprise - competitive results",
        "example": "ViTDet Introduction"
      },
      "level_3": {
        "pattern": "With [condition], outperforms... gains more prominent for...",
        "usage": "Third-level surprise - superiority under conditions",
        "example": "ViTDet Introduction"
      },
      "variants": {
        "interestingly": "Observation + literature support + explanation",
        "notably": "Important detail or counter-intuitive result",
        "it_is_worth_noting": "Technical caveat or clarification"
      }
    },
    "ablation_techniques": {
      "incremental_tables": {
        "pattern": "Baseline → (a) → (b) → (c) with Δ标注",
        "source": "ViTDet Table 1"
      },
      "destructive_comparison": {
        "pattern": "Intentionally wrong values to prove necessity",
        "source": "MeanFlows Table 1b"
      },
      "narrative_structure": {
        "observation_then_explain": "Observe pattern → Provide explanation (literature/hypothesis/theory)"
      }
    },
    "theoretical_derivation": {
      "naming_identity": {
        "pattern": "Define → Derive → Name ('X Identity')",
        "source": "MeanFlows MeanFlow Identity"
      },
      "step_by_step": {
        "pattern": "Motivation → Derivation with 'Now we...' → Justification with 'where...'",
        "source": "MeanFlows Section 2"
      }
    },
    "comparison_techniques": {
      "principled_vs_heuristic": {
        "pattern": "At the core...does not depend on...In contrast, typically rely on...",
        "source": "MeanFlows"
      },
      "fair_comparison_declaration": {
        "pattern": "Admit complexity → Claim effort → Demonstrate fairness",
        "source": "ViTDet"
      },
      "multi_factor_analysis": {
        "pattern": "Factors identified → Trend behavior → Wall-clock time",
        "source": "ViTDet Results"
      }
    },
    "keyword_strategies": {
      "theory_paper": ["principled", "intrinsic", "well-defined", "naturally", "self-contained", "solely originated from"],
      "design_paper": ["minimal", "sufficient", "decouple", "independence", "surprisingly", "abandons"],
      "rethinking_paper": ["Conventional wisdom holds that", "not a necessity", "orthogonal to", "uncharted realm"]
    }
  },
  "papers_analyzed_list": [
    "Non-local Neural Networks",
    "SlowFast Networks",
    "Rethinking ImageNet Pre-training",
    "Faster R-CNN",
    "Delving Deep into Rectifiers (PReLU)",
    "Spatial Pyramid Pooling (SPP-net)",
    "Deconstructing Denoising Diffusion Models",
    "Autoregressive Image Generation without Vector Quantization (MAR)",
    "Mean Flows for One-step Generative Modeling",
    "Exploring Plain Vision Transformer Backbones for Object Detection (ViTDet)",
    "MoCo v2: Improved Baselines with Momentum Contrastive Learning"
  ],
  "integration_summary": {
    "total_papers": 11,
    "knowledge_files": 5,
    "patterns_extracted": 25,
    "paper_types_identified": [
      "Theory-driven (MeanFlows)",
      "Design simplification (ViTDet)",
      "Rethinking (MAR)",
      "Deconstruction (DDM)",
      "Milestone (PReLU)",
      "Multi-task (SPP-net)",
      "Technical note (MoCo v2)"
    ]
  }
}