arXiv (OAI Expanded)
open access
Learning to Refer from Estimated Listener Gaze
We propose to finetune vision-language models to generate more pragmatically optimal referring expressions by transforming observations of incremental listener comprehension, in the form of gaze scanpaths, into learning signals. During training, referring expressions are sampled from the speaker pol
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