kib/examples/ml-research/.kb/manifest.json at 71f0688f16953bdd5cf676e4fc14dd5f2735e289 · keeganthomp/kib · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
{
  "version": "1",
  "vault": {
    "name": "ml-research",
    "created": "2026-03-01T09:00:00.000Z",
    "lastCompiled": "2026-03-15T14:30:00.000Z",
    "provider": "anthropic",
    "model": "claude-sonnet-4-20250514"
  },
  "sources": {
    "src_att001": {
      "hash": "a1b2c3d4e5f60001",
      "ingestedAt": "2026-03-01T09:05:00.000Z",
      "lastCompiled": "2026-03-15T14:30:00.000Z",
      "sourceType": "web",
      "originalUrl": "https://arxiv.org/abs/1706.03762",
      "producedArticles": ["attention-mechanism", "transformer-architecture", "vaswani-et-al"],
      "metadata": {
        "title": "Attention Is All You Need",
        "author": "Vaswani et al.",
        "date": "2017-06-12",
        "wordCount": 9200
      }
    },
    "src_rl002": {
      "hash": "a1b2c3d4e5f60002",
      "ingestedAt": "2026-03-05T11:00:00.000Z",
      "lastCompiled": "2026-03-15T14:30:00.000Z",
      "sourceType": "web",
      "originalUrl": "https://lilianweng.github.io/posts/2018-02-19-rl-overview/",
      "producedArticles": ["reinforcement-learning", "markov-decision-process"],
      "metadata": {
        "title": "A (Long) Peek into Reinforcement Learning",
        "author": "Lilian Weng",
        "date": "2018-02-19",
        "wordCount": 12000
      }
    },
    "src_bp003": {
      "hash": "a1b2c3d4e5f60003",
      "ingestedAt": "2026-03-10T08:30:00.000Z",
      "lastCompiled": "2026-03-15T14:30:00.000Z",
      "sourceType": "pdf",
      "originalUrl": "https://www.nature.com/articles/323533a0",
      "producedArticles": ["backpropagation", "gradient-descent"],
      "metadata": {
        "title": "Learning representations by back-propagating errors",
        "author": "Rumelhart, Hinton, Williams",
        "date": "1986-10-09",
        "wordCount": 4500
      }
    }
  },
  "articles": {
    "attention-mechanism": {
      "hash": "wiki_hash_0001",
      "createdAt": "2026-03-15T14:30:00.000Z",
      "lastUpdated": "2026-03-15T14:30:00.000Z",
      "derivedFrom": ["src_att001"],
      "backlinks": ["transformer-architecture"],
      "forwardLinks": ["transformer-architecture", "backpropagation"],
      "tags": ["deep-learning", "nlp", "attention"],
      "summary": "Mechanism that lets models dynamically focus on relevant parts of the input",
      "wordCount": 380,
      "category": "concept"
    },
    "backpropagation": {
      "hash": "wiki_hash_0002",
      "createdAt": "2026-03-15T14:30:00.000Z",
      "lastUpdated": "2026-03-15T14:30:00.000Z",
      "derivedFrom": ["src_bp003"],
      "backlinks": ["attention-mechanism", "gradient-descent"],
      "forwardLinks": ["gradient-descent"],
      "tags": ["optimization", "neural-networks", "training"],
      "summary": "Algorithm for computing gradients in neural networks via the chain rule",
      "wordCount": 350,
      "category": "concept"
    },
    "gradient-descent": {
      "hash": "wiki_hash_0003",
      "createdAt": "2026-03-15T14:30:00.000Z",
      "lastUpdated": "2026-03-15T14:30:00.000Z",
      "derivedFrom": ["src_bp003"],
      "backlinks": ["backpropagation"],
      "forwardLinks": ["backpropagation"],
      "tags": ["optimization", "training"],
      "summary": "Iterative optimization algorithm that follows the negative gradient to minimize loss",
      "wordCount": 290,
      "category": "concept"
    },
    "transformer-architecture": {
      "hash": "wiki_hash_0004",
      "createdAt": "2026-03-15T14:30:00.000Z",
      "lastUpdated": "2026-03-15T14:30:00.000Z",
      "derivedFrom": ["src_att001"],
      "backlinks": ["attention-mechanism"],
      "forwardLinks": ["attention-mechanism", "reinforcement-learning"],
      "tags": ["deep-learning", "nlp", "architecture"],
      "summary": "Neural network architecture based entirely on self-attention, replacing recurrence and convolutions",
      "wordCount": 520,
      "category": "topic"
    },
    "reinforcement-learning": {
      "hash": "wiki_hash_0005",
      "createdAt": "2026-03-15T14:30:00.000Z",
      "lastUpdated": "2026-03-15T14:30:00.000Z",
      "derivedFrom": ["src_rl002"],
      "backlinks": ["transformer-architecture"],
      "forwardLinks": ["markov-decision-process"],
      "tags": ["reinforcement-learning", "agents", "rewards"],
      "summary": "Learning paradigm where agents learn optimal behavior through trial-and-error interaction with an environment",
      "wordCount": 480,
      "category": "topic"
    },
    "markov-decision-process": {
      "hash": "wiki_hash_0006",
      "createdAt": "2026-03-15T14:30:00.000Z",
      "lastUpdated": "2026-03-15T14:30:00.000Z",
      "derivedFrom": ["src_rl002"],
      "backlinks": ["reinforcement-learning"],
      "forwardLinks": ["reinforcement-learning"],
      "tags": ["reinforcement-learning", "math", "probability"],
      "summary": "Mathematical framework for modeling sequential decision-making under uncertainty",
      "wordCount": 310,
      "category": "concept"
    },
    "vaswani-et-al": {
      "hash": "wiki_hash_0007",
      "createdAt": "2026-03-15T14:30:00.000Z",
      "lastUpdated": "2026-03-15T14:30:00.000Z",
      "derivedFrom": ["src_att001"],
      "backlinks": [],
      "forwardLinks": ["attention-mechanism", "transformer-architecture"],
      "tags": ["researchers", "google-brain"],
      "summary": "Authors of the 2017 'Attention Is All You Need' paper that introduced the transformer",
      "wordCount": 200,
      "category": "reference"
    }
  },
  "stats": {
    "totalSources": 3,
    "totalArticles": 7,
    "totalWords": 2530,
    "lastLintAt": "2026-03-15T15:00:00.000Z"
  }
}