Papers with HOLM

1 papers
HOLM: Hallucinating Objects with Language Models for Referring Expression Recognition in Partially-Observed Scenes (2022.acl-long)

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Challenge: a challenge in building AI systems physically present in the world is partial observability, a problem that exists when the entire state of the environment is not known or available to the system.
Approach: They propose a method to infer object hallucinations for the unobserved part of the environment using large pre-trained language models.
Outcome: The proposed method performs better than state-of-the-art approaches on two datasets for dRER.

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