Language & Intelligence Lab

언어지능 연구실

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Since most worldly phenomena can be expressed via language, language is a crucial medium for transferring information and integrating multiple information sources. For example, humans can describe what they see, hear and feel with words. Reversely, they can imagine scenes, sounds and feelings from what they read. Therefore, language plays an important role in solving machine learning (ML) and artificial intelligence (AI) problems with multimodal input sources. In our Language & Intelligence Lab, we study various topics on AI problems regarding NLP and multimodal learning. By addressing the different problems, we aim to build integrated systems that understand language, vision, action, etc.

관심분야

Natural Language Processing, Multimodal Learning

희망분야

Explainable/Interpretable AI

Research Keywords and Topics

텍스트 생성, 텍스트기반 이미지 생성
체현화된(Embodied) 인공지능 (네비게이션, 물체 조작 등)
대화형 인공지능 시스템
상식기반 추론
해석/설명가능한 인공지능

Research Publications

- CoSIm: Commonsense Reasoning for Counterfactual Scene Imagination, Hyounghun Kim*, Abhay Zala*, and Mohit Bansal. Proceedings of NAACL 2022.
- CAISE: Conversational Agent for Image Search and Editing, Hyounghun Kim, Doo Soon Kim, Seunghyun Yoon, Franck Dernoncourt, Trung Bui, and Mohit Bansal. Proceedings of AAAI 2022.
- NDH-Full: Learning and Evaluating Navigational Agents on Full-Length Dialogue, Hyounghun Kim, Jialu Li, and Mohit Bansal. Proceedings of EMNLP 2021.
- FixMyPose: Pose Correctional Captioning and Retrieval, Hyounghun Kim*, Abhay Zala*, Graham Burri, and Mohit Bansal. Proceedings of AAAI 2021.
- ArraMon: A Joint Navigation-Assembly Instruction Interpretation Task in Dynamic Environments, Hyounghun Kim, Abhay Zala, Graham Burri, Hao Tan, and Mohit Bansal. Findings of EMNLP 2020.
- Improving Visual Question Answering by Referring to Generated Paragraph Captions, Hyounghun Kim, and Mohit Bansal. Proceedings of ACL 2019 (short paper).

국가과학기술표준분류

  • EE. 정보/통신
  • EE01. 정보이론
  • EE0108. 인공지능