Upload Taxonomy4CL_v1.0.1.json
Browse files- Taxonomy4CL_v1.0.1.json +401 -0
Taxonomy4CL_v1.0.1.json
ADDED
@@ -0,0 +1,401 @@
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1 |
+
{
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2 |
+
"name": "NLP",
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3 |
+
"children": [
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4 |
+
{
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5 |
+
"name": "Image and Video Processing",
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6 |
+
"children": [
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7 |
+
{"name": "Image Captioning"},
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8 |
+
{"name": "Video Captioning"},
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9 |
+
{"name": "Optical Character Recognition (OCR)"},
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10 |
+
{"name": "Sign Language and Fingerspelling Recognition"},
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11 |
+
{"name": "Document Layout Analysis (DLA)"}
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12 |
+
]
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13 |
+
},
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14 |
+
{
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15 |
+
"name": "Machine Translation (MT)",
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16 |
+
"children": [
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17 |
+
{"name": "Rule-based MT (RBMT)"},
|
18 |
+
{"name": "Statistical MT (SMT)"},
|
19 |
+
{"name": "Neural MT (NMT)"}
|
20 |
+
]
|
21 |
+
},
|
22 |
+
{
|
23 |
+
"name": "Learning Paradigms",
|
24 |
+
"children": [
|
25 |
+
{"name": "Multimodal Learning"},
|
26 |
+
{"name": "Transfer Learning"},
|
27 |
+
{"name": "Few-shot Learning"},
|
28 |
+
{"name": "Reinforcement Learning"},
|
29 |
+
{"name": "Supervised Learning"},
|
30 |
+
{"name": "Unsupervised Learning"},
|
31 |
+
{"name": "Active Learning"},
|
32 |
+
{"name": "Adversarial Learning"}
|
33 |
+
]
|
34 |
+
},
|
35 |
+
{
|
36 |
+
"name": "Model Architectures",
|
37 |
+
"children": [
|
38 |
+
{"name": "Transformer Models"},
|
39 |
+
{
|
40 |
+
"name": "Recurrent Neural Networks (RNNs)",
|
41 |
+
"children": [
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42 |
+
{"name": "Long Short-Term Memory (LSTM) Models"}
|
43 |
+
]
|
44 |
+
},
|
45 |
+
{"name": "Large Language Models (LLMs)"},
|
46 |
+
{"name": "Graph Neural Networks (GNNs)"},
|
47 |
+
{"name": "Latent Dirichlet Allocation (LDA)"}
|
48 |
+
]
|
49 |
+
},
|
50 |
+
{
|
51 |
+
"name": "Multi-agent Communication Systems",
|
52 |
+
"children": [
|
53 |
+
{"name": "Intelligent Agents"}
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54 |
+
]
|
55 |
+
},
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56 |
+
{
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57 |
+
"name": "Finite State Machines"
|
58 |
+
},
|
59 |
+
|
60 |
+
{
|
61 |
+
"name": "Multilingual NLP"
|
62 |
+
},
|
63 |
+
|
64 |
+
{
|
65 |
+
"name": "Cross-lingual Application"
|
66 |
+
},
|
67 |
+
|
68 |
+
{
|
69 |
+
"name": "Bilingual Lexicon Induction (BLI)"
|
70 |
+
},
|
71 |
+
|
72 |
+
{
|
73 |
+
"name": "Low-resource Languages"
|
74 |
+
},
|
75 |
+
|
76 |
+
{
|
77 |
+
"name": "Classification Applications",
|
78 |
+
"children": [
|
79 |
+
{"name": "Multilabel Text Classification"},
|
80 |
+
{"name": "Hate and Offensive Speech Detection"},
|
81 |
+
{"name": "Intent Detection"},
|
82 |
+
{"name": "Email Spam and Phishing Detection"},
|
83 |
+
{"name": "Plagiarism Detection"},
|
84 |
+
{"name": "Disfluency Detection"},
|
85 |
+
{
|
86 |
+
"name": "Misinformation Detection",
|
87 |
+
"children": [
|
88 |
+
{"name": "Fake News Detection"},
|
89 |
+
{"name": "Fake Review Detection"}
|
90 |
+
]
|
91 |
+
},
|
92 |
+
{"name": "Rumor Detection"},
|
93 |
+
{"name": "Claim Verification"},
|
94 |
+
{"name": "Emotion Detection"},
|
95 |
+
{"name": "Sarcasm Detection"},
|
96 |
+
{"name": "Humor Detection"},
|
97 |
+
{"name": "Stance Detection"},
|
98 |
+
{"name": "Personality Trait Prediction"},
|
99 |
+
{"name": "Author Detection"},
|
100 |
+
{"name": "Irony Detection"},
|
101 |
+
{
|
102 |
+
"name": "Sentiment Analysis (SA)",
|
103 |
+
"children": [
|
104 |
+
{"name": "Aspect-Based SA (ABSA)"}
|
105 |
+
]
|
106 |
+
},
|
107 |
+
{"name": "Hope Speech Detection"}
|
108 |
+
]
|
109 |
+
},
|
110 |
+
{
|
111 |
+
"name": "Dialogue Systems",
|
112 |
+
"children": [
|
113 |
+
{"name": "Open Domain Dialogue Systems"},
|
114 |
+
{"name": "Chatbots"},
|
115 |
+
{"name": "Dialogue State Tracking (DST)"},
|
116 |
+
{"name": "Response Generation"}
|
117 |
+
]
|
118 |
+
},
|
119 |
+
{
|
120 |
+
"name": "Question Answering (QA)",
|
121 |
+
"children": [
|
122 |
+
{"name": "Visual QA (VQA)"},
|
123 |
+
{"name": "Open-Domain QA"},
|
124 |
+
{"name": "Multiple Choice QA (MCQA)"},
|
125 |
+
{"name": "Community QA"},
|
126 |
+
{"name": "Mathematical QA"},
|
127 |
+
{"name": "Knowledge Base QA"},
|
128 |
+
{"name": "Long Form QA"}
|
129 |
+
]
|
130 |
+
},
|
131 |
+
{
|
132 |
+
"name": "Domain-specific NLP",
|
133 |
+
"children": [
|
134 |
+
{
|
135 |
+
"name": "Medical and Clinical NLP",
|
136 |
+
"children": [
|
137 |
+
{"name": "NLP for Mental Health"},
|
138 |
+
{"name": "Biomedical NLP"}
|
139 |
+
]
|
140 |
+
},
|
141 |
+
{
|
142 |
+
"name": "NLP for News and Media",
|
143 |
+
"children":[
|
144 |
+
{"name": "NLP for Social Media"}
|
145 |
+
]
|
146 |
+
},
|
147 |
+
{"name": "NLP for Climate"},
|
148 |
+
{"name": "NLP for the Legal Domain"},
|
149 |
+
{"name": "NLP for Finance"},
|
150 |
+
{"name": "NLP for Arts",
|
151 |
+
"children": [
|
152 |
+
{"name": "NLP for Music"},
|
153 |
+
{"name": "NLP for Literature"}
|
154 |
+
]},
|
155 |
+
{"name": "NLP for Politics"},
|
156 |
+
{"name": "NLP for Education"},
|
157 |
+
{
|
158 |
+
"name": "NLP for Bibliometrics and Scientometrics",
|
159 |
+
"children": [
|
160 |
+
{"name": "Citation Analysis"}
|
161 |
+
]
|
162 |
+
}
|
163 |
+
]
|
164 |
+
},
|
165 |
+
{
|
166 |
+
"name": "Adversarial Attacks and Robustness",
|
167 |
+
"children": [
|
168 |
+
{"name": "Backdoor Attacks"}
|
169 |
+
]
|
170 |
+
},
|
171 |
+
|
172 |
+
{
|
173 |
+
"name": "Commonsense Reasoning"
|
174 |
+
},
|
175 |
+
{
|
176 |
+
"name": "Automated Essay Scoring"
|
177 |
+
},
|
178 |
+
{
|
179 |
+
"name": "Discourse Analysis"
|
180 |
+
},
|
181 |
+
{
|
182 |
+
"name": "Audio Generation and Processing",
|
183 |
+
"children":[
|
184 |
+
{"name": "Automatic Speech Recognition (ASR)"},
|
185 |
+
{"name": "Speech Synthesis"}
|
186 |
+
]
|
187 |
+
},
|
188 |
+
{
|
189 |
+
"name": "Prompt Engineering"
|
190 |
+
},
|
191 |
+
{
|
192 |
+
"name": "Authorship Verification"
|
193 |
+
},
|
194 |
+
{
|
195 |
+
"name": "Acronyms and Abbreviations Detection and Expansion"
|
196 |
+
},
|
197 |
+
{
|
198 |
+
"name": "Text Clustering"
|
199 |
+
},
|
200 |
+
{
|
201 |
+
"name": "Topic Modeling"
|
202 |
+
},
|
203 |
+
{
|
204 |
+
"name": "Evaluation Techniques"
|
205 |
+
},
|
206 |
+
{
|
207 |
+
"name": "Ethics"
|
208 |
+
},
|
209 |
+
|
210 |
+
|
211 |
+
{"name": "Biases in NLP",
|
212 |
+
"children": [
|
213 |
+
{"name": "Gender Bias"},
|
214 |
+
{"name": "Bias Detection"}
|
215 |
+
]
|
216 |
+
},
|
217 |
+
{
|
218 |
+
"name": "Argument Mining"
|
219 |
+
},
|
220 |
+
{
|
221 |
+
"name": "Embeddings",
|
222 |
+
"children": [
|
223 |
+
{"name": "Word Embeddings"},
|
224 |
+
{"name": "Sentence Embeddings"}
|
225 |
+
]
|
226 |
+
},
|
227 |
+
{
|
228 |
+
"name": "Parsing",
|
229 |
+
"children": [
|
230 |
+
{"name": "Discourse Parsing"},
|
231 |
+
{"name": "Semantic Parsing",
|
232 |
+
"children": [
|
233 |
+
{"name": "Semantic Role Labeling"}
|
234 |
+
]
|
235 |
+
},
|
236 |
+
{"name": "Morphological Parsing"},
|
237 |
+
{"name": "Syntactic Parsing",
|
238 |
+
"children": [
|
239 |
+
{"name": "Constituency Parsing"},
|
240 |
+
{"name": "Dependency Parsing"}
|
241 |
+
]
|
242 |
+
}
|
243 |
+
]
|
244 |
+
},
|
245 |
+
{
|
246 |
+
"name": "Text Preprocessing",
|
247 |
+
"children": [
|
248 |
+
{"name": "Text Segmentation",
|
249 |
+
"children": [
|
250 |
+
{"name": "Word Segmentation"},
|
251 |
+
{"name": "Sentence Segmentation"}
|
252 |
+
]
|
253 |
+
},
|
254 |
+
{"name": "Part-of-Speech (POS) Tagging"}
|
255 |
+
]
|
256 |
+
},
|
257 |
+
{
|
258 |
+
"name": "Text Generation",
|
259 |
+
"children": [
|
260 |
+
{"name": " Text-to-SQL"},
|
261 |
+
{"name": "Story Generation",
|
262 |
+
"children": [
|
263 |
+
{"name": "Narrative Plot in Storytelling"}
|
264 |
+
]
|
265 |
+
},
|
266 |
+
{"name": "Paraphrase and Rephrase Generation"},
|
267 |
+
{"name": "Lyrics Generation"},
|
268 |
+
{"name": "Poetry Generation"},
|
269 |
+
{"name": "Text Style Transfer"},
|
270 |
+
{"name": "Text Simplification"},
|
271 |
+
{"name": "Data-to-Text Generation",
|
272 |
+
"children": [
|
273 |
+
{"name": "Table-to-Text Generation"}
|
274 |
+
]
|
275 |
+
}
|
276 |
+
]
|
277 |
+
},
|
278 |
+
{
|
279 |
+
"name": "Data Management and Generation",
|
280 |
+
"children": [
|
281 |
+
{"name": "Data Analysis"},
|
282 |
+
{"name": "Data Preparation",
|
283 |
+
"children": [
|
284 |
+
{"name": "Annotation Processes"}
|
285 |
+
]
|
286 |
+
},
|
287 |
+
{"name": "Data Augmentation"}
|
288 |
+
]
|
289 |
+
},
|
290 |
+
|
291 |
+
{
|
292 |
+
"name": "Information Retrieval",
|
293 |
+
"children": [
|
294 |
+
{"name": "Information Filtering",
|
295 |
+
"children":[
|
296 |
+
{"name": "Recommender Systems"}
|
297 |
+
]
|
298 |
+
},
|
299 |
+
{"name": "Search Engines"}
|
300 |
+
]
|
301 |
+
},
|
302 |
+
|
303 |
+
{
|
304 |
+
"name": "Language Change Analysis",
|
305 |
+
"children": [
|
306 |
+
{"name": "Semantic Change Analysis"}
|
307 |
+
]
|
308 |
+
},
|
309 |
+
{
|
310 |
+
"name": "Automatic Text Summarization",
|
311 |
+
"children": [
|
312 |
+
{"name": "Abstractive Text Summarization"},
|
313 |
+
{"name": "Extractive Text Summarization"},
|
314 |
+
{"name": "Document Summarization",
|
315 |
+
"children": [
|
316 |
+
{"name": "Multi-document Summarization"},
|
317 |
+
{"name": "Scientific Document Summarization"}
|
318 |
+
]
|
319 |
+
}
|
320 |
+
]
|
321 |
+
},
|
322 |
+
{
|
323 |
+
"name": "Information Extraction",
|
324 |
+
"children": [
|
325 |
+
{"name": "Named Entity Recognition (NER)",
|
326 |
+
"children": [
|
327 |
+
{"name": "NER for Nested Entities"}
|
328 |
+
]
|
329 |
+
},
|
330 |
+
{"name": "Entity Linking"},
|
331 |
+
{"name": "Event Extraction"},
|
332 |
+
{"name": "Temporal Event Understanding"},
|
333 |
+
{"name": "Coreference Resolution"},
|
334 |
+
{"name": "Anaphora Resolution"},
|
335 |
+
{"name": "Word Sense Disambiguation (WSD)"},
|
336 |
+
{"name": "Relation Extraction",
|
337 |
+
"children": [
|
338 |
+
{"name": "Causality Relations Extraction"}
|
339 |
+
]
|
340 |
+
},
|
341 |
+
{"name": "Hypernymy Extraction"}
|
342 |
+
]
|
343 |
+
},
|
344 |
+
{
|
345 |
+
"name": "Error Detection and Correction",
|
346 |
+
"children": [
|
347 |
+
{"name": "Grammatical Error Correction (GEC)"}
|
348 |
+
]
|
349 |
+
},
|
350 |
+
{
|
351 |
+
"name": "Knowledge Representation and Reasoning",
|
352 |
+
"children": [
|
353 |
+
{"name": "Semantic Web"},
|
354 |
+
{"name": "Knowledge Graphs"},
|
355 |
+
{"name": "Taxonomy Construction"},
|
356 |
+
{"name": "Ontologies",
|
357 |
+
"children": [
|
358 |
+
{"name": "Ontology Construction"},
|
359 |
+
{"name": "Ontology Matching"},
|
360 |
+
{"name": "Ontology Extension "}
|
361 |
+
]
|
362 |
+
},
|
363 |
+
{"name": "Multihop Reasoning"},
|
364 |
+
{"name": "Link Prediction"},
|
365 |
+
{"name": "Abstract Meaning Representation (AMR)"}
|
366 |
+
]
|
367 |
+
},
|
368 |
+
{
|
369 |
+
"name": "Figurative Language",
|
370 |
+
"children": [
|
371 |
+
{"name": "Idiomatic Expressions"},
|
372 |
+
{"name": "Metaphors"}
|
373 |
+
]
|
374 |
+
},
|
375 |
+
|
376 |
+
{
|
377 |
+
"name": "Software Development"
|
378 |
+
},
|
379 |
+
|
380 |
+
{
|
381 |
+
"name": "Infrastructure or Platform Development"
|
382 |
+
},
|
383 |
+
|
384 |
+
{
|
385 |
+
"name": "Explainability and Interpretability"
|
386 |
+
},
|
387 |
+
|
388 |
+
{
|
389 |
+
"name": "Natural Language Inference (NLI)"
|
390 |
+
},
|
391 |
+
|
392 |
+
{
|
393 |
+
"name": "Human-machine Interaction"
|
394 |
+
},
|
395 |
+
|
396 |
+
{
|
397 |
+
"name": "Robotics"
|
398 |
+
}
|
399 |
+
|
400 |
+
]
|
401 |
+
}
|