Papers by Chun Zhou
Aerial Vision-and-Dialog Navigation (2023.findings-acl)
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| Challenge: | Aerial visionand-dialling navigation (AVDN) is a new approach to autonomous drones that can converse with humans and follow natural language commands to complete tasks. |
| Approach: | They propose to use Aerial Visionand-Dialog Navigation (AVDN) to navigate a drone via natural language conversation by collecting a dataset of over 3k recorded navigation trajectories with asynchronous human-human dialogs between commanders and followers. |
| Outcome: | The proposed system can converse with humans and follow natural language commands to fly to the expected destination. |
COAS2W: A Chinese Older-Adults Spoken-to-Written Transformation Corpus with Context Awareness (2025.emnlp-main)
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| Challenge: | Existing work on spoken-to-written transformations from older adults' language is limited by omission, disordered syntax, constituent errors, and redundancy. |
| Approach: | They propose to combine a spoken-to-written corpus of 10,004 utterances from older adults with a written version, fine-grained error labels, and four-sentence context. |
| Outcome: | The proposed model outperforms closed-source models on Chinese spoken-to-written corpus and shows that multi-sentence input is more efficient. |
Probabilistic Graph Reasoning for Natural Proof Generation (2021.findings-acl)
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| Challenge: | Existing approaches to reasoning over formal representations do not explicitly consider inter-dependency between answers and proofs. |
| Approach: | They propose a novel approach for joint answer prediction and proof generation using an induced graphical model. |
| Outcome: | The proposed approach achieves 10%-30% improvement on QA accuracy in evaluations under diverse conditions. |
Vocabulary Learning via Optimal Transport for Neural Machine Translation (2021.acl-long)
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| Challenge: | Empirical results show that VOLT beats widely-used vocabularies in diverse scenarios, including WMT-14 English-German translation, TED bilingual translation, and TED multilingual translation. |
| Approach: | They propose a token dictionary solution that can be used without trial training to find the best dictionary with a proper size. |
| Outcome: | The proposed solution beats widely-used vocabularies in English-German translation, TED bilingual translation, and TED multilingual translation. |