Fine-tuning language models to find agreement among humans with diverse preferences.
Michiel A. BakkerMartin J. ChadwickHannah R. SheahanMichael Henry TesslerLucy Campbell-GillinghamJan BalaguerNat McAleeseAmelia GlaeseJohn AslanidesMatthew M. BotvinickChristopher SummerfieldPublished in: CoRR (2022)
Keyphrases
- language model
- fine tuning
- language modeling
- n gram
- query expansion
- probabilistic model
- fine tune
- information retrieval
- document retrieval
- viable alternative
- language modelling
- retrieval model
- speech recognition
- context sensitive
- test collection
- query terms
- smoothing methods
- fine tuned
- ad hoc information retrieval
- translation model
- vector space model
- pseudo relevance feedback
- user preferences
- retrieval effectiveness
- statistical language models
- document ranking
- negotiation strategies
- relevance model
- text retrieval
- language models for information retrieval
- language model for information retrieval