Papers by Aude Oliva
Cross-Modal Discrete Representation Learning (2022.acl-long)
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| Challenge: | a new framework for learning representations from multimodal data is proposed . the proposed framework uses discretized embedding vectors to capture finer levels of granularity . |
| Approach: | They propose a self-supervised representation learning framework that captures finer levels of granularity across different modalities. |
| Outcome: | The proposed representation can capture finer levels of granularity across different modalities . it can be used on cross-modal retrieval tasks without direct supervision . |
LangNav: Language as a Perceptual Representation for Navigation (2024.findings-naacl)
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| Challenge: | Existing approaches to vision-and-language navigation use visual features as the perceptual representation of a visual representation of an agent's egocentric panoramic view. |
| Approach: | They propose to use off-the-shelf vision systems to convert an agent’s egocentric panoramic view into natural language descriptions. |
| Outcome: | The proposed approach improves on the R2R VLN benchmark by using synthetic trajectories from a prompted language model and domain transfer where a policy learned on one simulated environment (ALFRED) is transferred to another (more realistic) environment and combining both vision- and language-based representations. |