다양한 언어 및 지역의 사회적 편견을 반영하는 SeeGULL Multilingual 다국어 스테레오타입 데이터셋을 구축하고 모델 평가에 활용한다.
다양한 도메인에 대한 도메인별 프롬프트 튜닝을 통한 다중 모달 가짜 뉴스 감지
Introducing Relevant Evidence Detection in Multimodal Fact-Checking to improve accuracy and performance.
Large language models can be empowered with graph understanding and reasoning capabilities through the GraphInstruct benchmark.
Reinforcement learning offers efficient solutions for spatial resource allocation problems by optimizing decision-making processes.
LLP-Bench is the first large scale tabular LLP benchmark with diverse datasets, enabling systematic study and design of new LLP techniques.
MMoFusion proposes a Multi-modal Co-Speech Motion Generation Framework based on a Diffusion Model, ensuring authenticity and diversity in motion generation.
Personality traits significantly affect ToM reasoning in LLMs, with the Dark Triad showing a larger impact than the Big Five OCEAN traits.
AS-ES learning maximizes small models' potential in CoT-intensive tasks by segmenting CoT data for iterative generation.
Proposing the OVEL task for linking entities in online videos, utilizing a memory block managed by a Large Language Model for efficient entity linking.