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Found 8 papers, 3 papers with code
Is Information Density Uniform in Task-Oriented Dialogues?
The Uniform Information Density principle states that speakers plan their utterances to reduce fluctuations in the density of the information transmitted.
AnaLog: Testing Analytical and Deductive Logic Learnability in Language Models
We investigate the extent to which pre-trained language models acquire analytical and deductive logical reasoning capabilities as a side effect of learning word prediction.
Attribution and Alignment: Effects of Local Context Repetition on Utterance Production and Comprehension in Dialogue
Language models are often used as the backbone of modern dialogue systems.
Construction Repetition Reduces Information Rate in Dialogue
We hypothesise that speakers use construction repetition to mitigate information rate, leading to an overall decrease in utterance information content over the course of a dialogue.
State-of-the-art generalisation research in NLP: A taxonomy and review
We present a taxonomy for characterising and understanding generalisation research in NLP.
Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations
We investigate the extent to which modern, neural language models are susceptible to structural priming, the phenomenon whereby the structure of a sentence makes the same structure more probable in a follow-up sentence.
Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts
We propose a generation model that produces referring utterances grounded in both the visual and the conversational context.
Does Ability Affect Alignment in Second Language Tutorial Dialogue?
We find that lexical priming in learner-tutor dialogues differs from that in conversational and task-based dialogues, and we find evidence that alignment increases with ability and with word complexity.
