NS-IL: Neuro-Symbolic Visual Question Answering Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes.
Penny JohnstonKeiller NogueiraKevin SwinglerPublished in: IEEE Access (2023)
Keyphrases
- question answering
- sample size
- probabilistic model
- natural language processing
- natural language
- information extraction
- graphical models
- random sample
- qa clef
- cross language
- model selection
- question answering systems
- information retrieval
- question classification
- high level
- passage retrieval
- confidence intervals
- visual information
- named entities
- conditional random fields
- document retrieval
- expectation maximization
- upper bound
- low level
- natural language questions
- machine translation
- query expansion
- semantic roles
- qa systems
- candidate answers
- expert systems
- bayesian networks
- sentence retrieval
- open domain question answering