Shengjie Li
2021
Neural Anaphora Resolution in Dialogue
Hideo Kobayashi
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Shengjie Li
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Vincent Ng
Proceedings of the CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue
The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis Resolution in Dialogue: A Cross-Team Analysis
Shengjie Li
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Hideo Kobayashi
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Vincent Ng
Proceedings of the CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue
2020
Cross-modal Coherence Modeling for Caption Generation
Malihe Alikhani
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Piyush Sharma
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Shengjie Li
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Radu Soricut
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Matthew Stone
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
We use coherence relations inspired by computational models of discourse to study the information needs and goals of image captioning. Using an annotation protocol specifically devised for capturing image–caption coherence relations, we annotate 10,000 instances from publicly-available image–caption pairs. We introduce a new task for learning inferences in imagery and text, coherence relation prediction, and show that these coherence annotations can be exploited to learn relation classifiers as an intermediary step, and also train coherence-aware, controllable image captioning models. The results show a dramatic improvement in the consistency and quality of the generated captions with respect to information needs specified via coherence relations.
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Co-authors
- Hideo Kobayashi 2
- Vincent Ng 2
- Malihe Alikhani 1
- Piyush Sharma 1
- Radu Soricut 1
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