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
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2025, 심현정 연구실
- Accelerated Test-Time Scaling with Model-Free Speculative Sampling
2025, AGI-LAB, KAIST
- Agent-as-Judge for Factual Summarization of Long Narratives
2025, 언어 및 데이터지능 연구실
- AmpleHate: Amplifying the Attention for Versatile Implicit Hate Detection
2025, 계산이론
- AMQ: Enabling AutoML for Mixed-precision Weight-Only Quantization of Large Language Models
2025, Machine Learning Lab
- Are Vision-Language Models Safe in the Wild? A Meme-Based Benchmark Study
2025, Data Intelligence Lab
- Assessing LLM Reasoning Steps via Principal Knowledge Grounding
2025, 데이터마이닝 및 인포메이션시스템 연구실
- Assessing Socio-Cultural Alignment and Technical Safety of Sovereign LLMs
2025, Learning and Adaptation Algorithms Lab, 천둥 연구실
- Avoidance Decoding for Diverse Multi-Branch Story Generation
2025, 머신 인텔리전스 연구실
- Beneath the Facade: Probing Safety Vulnerabilities in LLMs via Auto-Generated Jailbreak Prompts
2025, 빅데이터 지능 연구실
- Beyond Task-Oriented and Chitchat Dialogues: Proactive and Transition-Aware Conversational Agents
2025, 자연어처리 연구실
- Bridging the Gap Between Molecule and Textual Descriptions via Substructure-aware Alignment
2025, 데이터 인텔리전스
- Building Resource-Constrained Language Agents: A Korean Case Study on Chemical Toxicity Information
2025, 주재걸 연구실
- Can Code-Switched Texts Activate a Knowledge Switch in LLMs? A Case Study on English-Korean Code-Switching
2025, 언어 및 범용인공지능, 데이터인텔리전스
- Can Large Language Models be Effective Online Opinion Miners?
2025, 데이터인텔리전스
- Can You Trick the Grader? Adversarial Persuasion of LLM Judges
2025, 머신 인텔리전스 연구실
- Captioning for Text-Video Retrieval via Dual-Group Direct Preference Optimization
2025, 기계학습 및 비전 연구실
- ChronoBias: A Benchmark for Evaluating Temporal Group Bias in the Time-sensitive Knowledge of Large Language Models
2025, Natural Language Processing Lab, Machine Learning Lab
- CodeComplex: Dataset for Worst-Case Time Complexity Prediction
2025, 계산이론
- CoEx - Co-evolving World-model and Exploration
2025, 언어 및 데이터지능 연구실