자연어처리·LLM, 학회
EMNLP 논문을 낸 국내 연구실
탑티어Empirical Methods in Natural Language Processing. 2023년 이후 논문 301편, 연구실 110곳
이 학회에 논문을 낸 연구실
고려대 장부루 교수신생 랩모집 안내
탑티어 10전체 13구성원 12
대규모 언어 모델AI 안전·정렬
최근 논문
- HEAR: Hearing Enhanced Audio Response for Video-grounded Dialogue
2023, 인공지능 및 머신러닝 연구실
- Impact of Co-occurrence on Factual Knowledge of Large Language Models
2023, Statistical Artificial Intelligence Lab
- Improving Bias Mitigation through Bias Experts in Natural Language Understanding
2023, 데이터 인텔리전스
- Improving Transformer-based Program Repair Model through False Behavior Diagnosis
2023, 이은석 연구실
- Intervention-Based Alignment of Code Search with Execution Feedback
2023, 언어 및 데이터지능 연구실
- Intuitive Multilingual Audio-Visual Speech Recognition with a Single-Trained Model
2023, IVY Lab & IVL Lab
- It Ain't Over: A Multi-aspect Diverse Math Word Problem Dataset
2023, 데이터지능 및 학습 연구실, HLILab
- KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models
2023, 조요한 연구실, 최윤재 연구실
- Knowledge-Augmented Language Model Verification
2023, 황성주 연구실
- Large Language Models are Temporal and Causal Reasoners for Video Question Answering
2023, 기계학습 및 비전 연구실
- Leap-of-Thought: Accelerating Transformers via Dynamic Token Routing
2023, 데이터 인텔리전스
- Learning Co-Speech Gesture for Multimodal Aphasia Type Detection
2023, Data Science and Artificial Intelligence Lab
- Learning to Rank Generation with Pairwise Partial Rewards
2023, 언어 및 데이터지능 연구실
- Machine Reading Comprehension using Case-based Reasoning
2023, 이재윤 연구실
- MEGClass: Extremely Weakly Supervised Text Classification via Mutually-Enhancing Text Granularities
2023, Data and Adaptive Intelligence Systems Lab
- Meta-Learning of Prompt Generation for Lightweight Prompt Engineering on Language-Model-as-a-Service
2023, 소프트웨어 플랫폼 연구실
- mRedditSum: A Multimodal Abstractive Summarization Dataset of Reddit Threads with Images
2023, 시각 및 학습 연구실
- Multilingual Lottery Tickets to Pretrain Language Models
2023, 언어 및 데이터지능 연구실
- Multi-User MultiWOZ: Task-Oriented Dialogues among Multiple Users
2023, 조요한 연구실
- NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models
2023, 윤세영 연구실