Computer Science
Language Modeling
100%
Large Language Model
57%
Reproducibility
57%
Natural Language Generation
42%
Correlation Analysis
35%
Evaluation Result
35%
New-State
28%
Experimental Result
28%
de-noising
28%
Parsing
28%
Textual Semantic Similarity
28%
Questionnaire Study
28%
Autoencoder
28%
Raise Awareness
28%
Abstract Concept
28%
Rapid Development
28%
Generation Language
28%
Parallel Corpus
28%
Human Perception
28%
Linguistic Analysis
28%
Target Language
28%
Discourse Representation Structure
28%
Perceived Level
28%
Natural Language Processing
28%
Language Understanding
28%
Language Specific
28%
Target Audience
28%
Relative Performance
28%
Understandability
28%
Missing Information
28%
Open Source
19%
Neural Network
14%
Modeling Framework
14%
Knowledge Transfer
14%
Pre-Trained Language Models
14%
Automatic Generation
14%
Human Intervention
11%
Training Data
11%
Parameter Model
9%
Multiple Language
9%
Lower Performance
9%
Transfer Learning
7%
Parameter Size
5%
Perceived Quality
5%
Keyphrases
Text Style Transfer
42%
Text Rewriting
28%
Language Detection
28%
Language Generation
28%
NLP.
28%
Formality
28%
Human Judgment
28%
Multilingual Generation
28%
Multilingual Parsing
28%
Automatic Metrics
28%
Content Preservation
28%
Reproduction Study
28%
Plausibility Judgements
28%
Human Evaluation
28%
Instruction Tuning
28%
Chain-of-Thought
19%
Figures of Speech
14%
Fluency
14%
Common Metrics
14%
Denoising Autoencoder Model
14%
Informality
14%
Sentence Transformers
14%
Non-parallel Corpus
14%
Pseudo-parallel
14%
Metric Evaluation
14%
New Metric
14%
Correlation Analysis
14%
Quasi-parallel
14%
Human-based
14%
Seq2Seq Model
14%
Model Fine-tuning
14%
Rapid Development
14%
Generalisability
14%
GPT2 Model
14%
Simplified Text
9%
Clinical Letters
9%
Text Simplification
9%
Text Style
7%
Unified Modeling
7%
Stylized Text Generation
7%
Textual Attribute
7%
Multilingual Discourse
7%
Fine-tuning Language Models
7%
Low Barrier
5%
Rethink
5%
Negative Findings
5%
Prompt Learning
5%
