Large Vision-Language Model 通常LVLM包含⼀个视觉编码器、⼀个⽂本编码器和⼀个跨模态的对⻬⽹络。 LVLMs的训练通常由三部分组成: 视觉和⽂本编码器在⼤规模单模态数据集上分别进⾏预训练。 将这两个编码器通过视觉⽂本对⻬预训练进⾏对⻬,这可以使得LLM为给定图像⽣成有意义的描述。
-【2023-9-24】腾讯、浙大论文Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models -【2023-11-9】哈工大论文A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions 对于LLMs,常见幻觉有三种:输入冲突幻觉、上下文冲突幻觉和...
文章链接:CHAIN-OF-VERIFICATION REDUCES HALLUCINATION IN LARGE LANGUAGE MODELS---MetaAI 论文介绍: 主要贡献: 通过大模型自我提问验证的“验证链”CoVe方式缓解幻觉,与“思维链”(CoT)相似的一种链式方法。区别在于,“step-by-step”的思维链COT更关注逻辑推理即让模型学习答案生成的过程,而验证链更注重事实信息验...
Hallucination is a persistent challenge in large-scale language models, manifesting at multiple stages and leadingto outputs that stray from reality and produce some content thatdoes not conform to common sense. We introduce a novel approachto alleviate hallucination by contrasting the probabilityof ...
While large language models (LLMs) have demonstrated remarkable capabilities across a range of downstream tasks, a significant concern revolves around their propensity to exhibit hallucinations: LLMs occasionally generate content that diverges from the user input, contradicts previously generated context, or...
一、解决的问题 《LONG-FORM FACTUALITY IN LARGE LANGUAGE MODELS》arxiv.org/pdf/2403.18802.pdf...
Large language models are successful in answering factoid questions but are also prone to hallucination. We investigate the phenomenon of LLMs possessing correct answer knowledge yet still hallucinating from the perspective of inference dynamics, an area not previously covered in studies on hallucinations...
1. Large Language Processing Models Although rare, if you notice a grammatical error in the content produced by a large processing model, such as ChatGPT, that should raise an eyebrow and make you suspect a hallucination. Similarly, when text-generated content doesn't sound logical, correlate ...
OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation OPERA：通过过度信任惩罚和回顾分配来缓解多模态大型语言模型中的幻觉 论文链接：https://volctracer.com/w/nDJzJ3YE 论文作者：Qidong Huang1,2,*, Xiaoyi Dong2,3, Pan Zhang2, Bin ...
The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition. Nevertheless, LLMs are prone to hallucination, generating plausible yet nonfactual content. This phenomenon raises significant co...