연세대 인공지능학과, EMNLP 2024에서 12편의 논문 채택

연세대학교 인공지능학과 소속 연구자들의 논문 12편이 EMNLP 2024 (The 2024 Conference on Empirical Methods in Natural Language Processing) 학회에 채택되었다. EMNLP는 ACL, NAACL과 더불어 자연어 처리 분야에서 세계적으로 권위 있는 3대 학술대회 중 하나로, 2024년에는 미국 마이애미에서 개최될 예정이다.

이번 성과 중 다수는 초거대언어모델(LLM) 관련 연구로, 연세대 연구진이 LLM의 효율성, 성능 향상, 및 실제 응용에 대한 혁신적인 접근법을 제시하였다. 이는 연세대 인공지능학과의 연구 역량을 한층 강화하는 결과로 이어졌다.

채택된 논문 리스트:

(Main)

1. Can visual language models resolve textual ambiguity with visual cues? Let visual puns tell you!

Jiwan Chung, Seungwon Lim, Jaehyun Jeon, Seungbeen Lee, Youngjae Yu

2. Coffee-Gym: An Environment for Evaluating and Improving Natural Language Feedback on Erroneous Code

{Hyungjoo Chae, Taeyoon Kwon, Seungjun Moon}, Yongho Song, Dongjin Kang, Kai Tzu-iunn Ong, Beong-woo Kwak, Seonghyeon Bae, Seung-won Hwang, Jinyoung Yeo

3. Evidence-Focused Fact Summarization for Knowledge-Augmented Zero-Shot Question Answering

{Sungho Ko, Hyunjin Cho}, Hyungjoo Chae, Jinyoung Yeo, Dongha Lee

4. Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Hyungjoo Chae, Yeonghyeon Kim, Seungone Kim, Kai Tzu-iunn Ong, Beong-woo Kwak, Seonghwan Kim, Taeyoon Kwon, Jiwan Chung, Youngjae Yu, Jinyoung Yeo

5. Learning to Correct for QA Reasoning with Black-box LLMs

Jaehyung Kim, Dongyoung Kim, Yiming Yang

6. Selective Vision is the Challenge for Visual Reasoning: A Benchmark for Visual Argument Understanding

Jiwan Chung, Sungjae Lee, Minseo Kim, Seungju Han, Ashkan Yousefpour, Jack Hessel, Youngjae Yu

7. Taxonomy-guided Semantic Indexing for Academic Paper Search

SeongKu Kang, Yunyi Zhang, Pengcheng Jiang, Dongha Lee, Jiawei Han, Hwanjo Yu

(Findings)

8. CACTUS: Towards Psychological Counseling Conversations using Cognitive Behavioral Theory

{Suyeon Lee, Sunghwan Kim, Minju Kim}, Dongjin Kang, Dongil Yang, Harim Kim, Minseok Kang, Dayi Jung, Min Hee Kim, Seungbeen Lee, Kyoung-Mee Chung, Youngjae Yu, Dongha Lee, Jinyoung Yeo

9. Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation

Seonghyeon Lee, Suyeon Kim, Joonwon Jang, HeeJae Chon, Dongha Lee, Hwanjo Yu

10. How to Train Your Fact Verifier: Knowledge Transfer with Multimodal Open Models

Jaeyoung Lee, Ximing Lu, Jack Hessel, Faeze Brahman, Youngjae Yu, Yonatan Bisk, Yejin Choi, Saadia Gabriel

11. Make Compound Sentences Simple to Analyze: Learning to Split Sentences for Aspect-based Sentiment Analysis

{Yongsik Seo, Sungwon Song, Ryang Heo}, Jieyong Kim, Dongha Lee

12. Unveiling Implicit Table Knowledge with Question-Then-Pinpoint Reasoner for Insightful Table Summarization

Kwangwook Seo, Jinyoung Yeo, Dongha Lee