Wecome to the HUMANE Lab 😎

Human-Centered Language & Information Technologies (HUMANE) Lab at Soongsil University studies deep learning-based language technologies and vision-language multimodal methods. Our research aims to tackle social problems in online platforms (e.g., misinformation, hate speech) by developing LLM-based methods centered around human values.

성과

  • 국제 저명 학술대회 논문 발표: ACL, EMNLP 등
  • 논문상 수상: 한국인공지능학회 최우수논문상, 한국정보과학회 우수논문상 등
  • 2nd place at the AVeriTeC shared task hosted by the FEVER workshop

참여 과제

  • IITP 정보통신방송혁신인재양성 지역지능화혁신인재양성 (세부책임)
  • NRF 4단계 BK21 지능형반도체 교육연구단 (참여)
  • IITP 정보통신방송혁신인재양성 메타버스융합대학원 (참여)

Contact

Kunwoo Park / 박 건우 (kunwoo.park at ssu dot ac dot kr)

  • 연구 협업, 산학 협력 등 다양한 형태의 협업을 환영합니다.
  • Open Positions

News

May 16th, 2024

A joint work with Adobe Research has been accepted to ACL 2024.

Mar 8th, 2024

A paper is accepted for publication in IEEE Access. We introduced QuoteCSE++, a data-centric contrastive embedding framework for contextomy detection.

Feb 20th, 2024

A collaborative work with IU has been accepted to LREC-COLING 2024. We investigated how ChatGPT is aligned with human's views on explanation quality.

Dec 21th, 2023

A study on the LLM's ability of mathematical reasoning won the Outstanding Paper award at KSC 2023 (정보과학회 동계학술대회).

Oct 17th, 2023

A paper is accepted to EMNLP 2023 (Findings) based on collaboration with TUNiB. We introduce K-HATERS, the largest hate speech detection corpus in Korean.

July 17th, 2023

Our collaborative study with Adobe Research won the Hyundai Motors Best Paper Award at CKAIA (한국인공지능학회).

July 6th, 2023

A joint work with UCLA is accepted for publication in EPJ Data Science (Title: Perceived Gender Cues from Social Media Photographs and its Relations to Electoral Success).

June 20th, 2023

Yejun gave a poster presentation at KCC 2023 (정보과학회 하계학술대회) about cross-lingual experiments using vision language models.

June 5th, 2023

A paper is accepted for publication in JOK (정보과학회논문지). We propose a contrastive learning method for automated fact-checking.

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