Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification.
Ekaterina FadeevaAleksandr RubashevskiiArtem ShelmanovSergey PetrakovHaonan LiHamdy MubarakEvgenii TsymbalovGleb KuzminAlexander PanchenkoTimothy BaldwinPreslav NakovMaxim PanovPublished in: ACL (Findings) (2024)
Keyphrases
- language model
- language modeling
- probabilistic model
- n gram
- speech recognition
- document retrieval
- language modelling
- information retrieval
- document level
- retrieval model
- query expansion
- statistical language models
- test collection
- context sensitive
- language models for information retrieval
- smoothing methods
- pseudo relevance feedback
- ad hoc information retrieval
- uncertain data
- retrieval effectiveness
- word error rate
- query terms
- translation model
- text retrieval
- document length
- active learning