• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.461-464
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• 2023

최근 GPT-3 와 LLaMa 같은 생성형 거대 언어모델을 활용한 서비스가 공개되었고, 실제로 많은 사람들이 사용하고 있다. 해당 모델들은 사용자들의 다양한 질문에 대해 유창한 답변을 한다는 이유로 주목받고 있다. 하지만 LLMs 의 답변에는 종종 Inconsistent content 와 non-factual statement 가 존재하며, 이는 사용자들로 하여금 잘못된 정보의 전파 등의 문제를 야기할 수 있다. 이에 논문에서는 동일한 질문에 대한 LLM 의 답변 샘플과 외부 지식을 활용한 Hallucination Detection 방법을 제안한다. 제안한 방법은 동일한 질문에 대한 LLM 의 답변들을 이용해 일관성 점수(Consistency score)를 계산한다. 거기에 외부 지식을 이용한 사실검증을 통해 사실성 점수(Factuality score)를 계산한다. 계산된 일관성 점수와 사실성 점수를 활용하여 문장 수준의 Hallucination Detection 을 가능하게 했다. 실험에는 GPT-3 를 이용하여 WikiBio dataset 에 있는 인물에 대한 passage 를 생성한 데이터셋을 사용하였으며, 우리는 해당 방법을 통해 문장 수준에서의 Hallucination Detection 성능이 baseline 보다 AUC-PR scores 에서 향상됨을 보였다.

• Informatization Policy
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• v.31 no.2
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• pp.3-38
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• 2024

Hallucination is a significant barrier to the utilization of large-scale language models or multimodal models. In this study, we collected 654 computer science papers with "hallucination" in the abstract from arXiv from December 2022 to January 2024 following the advent of Chat GPT and conducted frequency analysis, knowledge network analysis, and literature review to explore the latest trends in hallucination research. The results showed that research in the fields of "Computation and Language," "Artificial Intelligence," "Computer Vision and Pattern Recognition," and "Machine Learning" were active. We then analyzed the research trends in the four major fields by focusing on the main authors and dividing them into data, hallucination detection, and hallucination mitigation. The main research trends included hallucination mitigation through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF), inference enhancement via "chain of thought" (CoT), and growing interest in hallucination mitigation within the domain of multimodal AI. This study provides insights into the latest developments in hallucination research through a technology-oriented literature review. This study is expected to help subsequent research in both engineering and humanities and social sciences fields by understanding the latest trends in hallucination research.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.2
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• pp.200-207
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• 2016

Objectives : Alzheimer's disease(AD) is characterized by progressive decline of cognitive function and also by various behavioral psychological symptoms of dementia(BPSD) which causes distress to their caregivers. The purpose of this study was to investigate association between each AD patients' behavioral psychological symptoms and their caregivers' burden. Methods : Participants were 80 AD patients and their caregivers. We used Korean neuropsychiatric inventory (K-NPI) to assess the symptoms of patients and Korean version of Zarit Burden Interview(ZBI) to evaluate caregivers' burden. Results : The results showed ZBI score, which is the index for caregivers' burden, had a statistically significant positive correlation with the frequency of delusion, hallucination, agitation/aggression, depression, anxiety, disinhibition and irritability, the severity of hallucination, agitation/aggression, anxiety, disinhibition, aberrant motor, and sleep, and the global score(frequency${\times}$severity) for delusion, hallucination, agitation/aggression, depression, anxiety, disinhibition, aberrant motor, and sleep. There were significant correlations between each scale for cognitive function(i.e. MMSE-KC, CDR, GDS) and ZBI scale. Correlations between each scale for activity of daily living(i.e. Barthel -ADL, K-ADL) and ZBI scale were also significant. Conclusions : There were a significant correlation between BPSD and caregiver burden. Caregiver burden was also correlated with cognitive function and activity of daily living. Early detection and preventive treatment of these symptoms in BPSD might make improvement of caregivers' quality of life as well as AD patients'.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1257-1264
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• 2011

Delirium is a neuropsychiatric disorder accompanying symptoms of hallucination, drowsiness, and tremors. It has high occurrence rates among elders, heart disease patients, and burn patients. It is a medical emergency associated with increased morbidity and mortality rates. That s why early detection and prevention of delirium ar significantly important. And This mental illness like delirium occurred by complex interaction between risk factors. In this paper, we identify risk factors and interactions between these factors for delirium using multi-factor dimensionality reduction (MDR) method.