A survey on hallucination in large vision-language models
Recent development of Large Vision-Language Models (LVLMs) has attracted growing
attention within the AI landscape for its practical implementation potential. However,`` …
attention within the AI landscape for its practical implementation potential. However,`` …
Mitigating object hallucinations in large vision-language models through visual contrastive decoding
Abstract Large Vision-Language Models (LVLMs) have advanced considerably intertwining
visual recognition and language understanding to generate content that is not only coherent …
visual recognition and language understanding to generate content that is not only coherent …
Hallucination of multimodal large language models: A survey
This survey presents a comprehensive analysis of the phenomenon of hallucination in
multimodal large language models (MLLMs), also known as Large Vision-Language Models …
multimodal large language models (MLLMs), also known as Large Vision-Language Models …
Haloquest: A visual hallucination dataset for advancing multimodal reasoning
Hallucination has been a major problem for large language models and remains a critical
challenge when it comes to multimodality in which vision-language models (VLMs) have to …
challenge when it comes to multimodality in which vision-language models (VLMs) have to …
Hal-eval: A universal and fine-grained hallucination evaluation framework for large vision language models
Large Vision-Language Models (LVLMs) exhibit remarkable capabilities but struggle
with''hallucinations''-inconsistencies between images and their descriptions. Previous …
with''hallucinations''-inconsistencies between images and their descriptions. Previous …
Mitigating object hallucination in large vision-language models via classifier-free guidance
The advancement of Large Vision-Language Models (LVLMs) has increasingly highlighted
the critical issue of their tendency to hallucinate non-existing objects in the images. To …
the critical issue of their tendency to hallucinate non-existing objects in the images. To …
Logical closed loop: Uncovering object hallucinations in large vision-language models
Object hallucination has been an Achilles' heel which hinders the broader applications of
large vision-language models (LVLMs). Object hallucination refers to the phenomenon that …
large vision-language models (LVLMs). Object hallucination refers to the phenomenon that …
Multi-object hallucination in vision-language models
Large vision language models (LVLMs) often suffer from object hallucination, producing
objects not present in the given images. While current benchmarks for object hallucination …
objects not present in the given images. While current benchmarks for object hallucination …
What makes for good visual instructions? synthesizing complex visual reasoning instructions for visual instruction tuning
Visual instruction tuning is an essential approach to improving the zero-shot generalization
capability of Multi-modal Large Language Models (MLLMs). A surge of visual instruction …
capability of Multi-modal Large Language Models (MLLMs). A surge of visual instruction …
Literature Review of AI Hallucination Research Since the Advent of ChatGPT: Focusing on Papers from arXiv
DM Park, HJ Lee - Informatization Policy, 2024 - koreascience.kr
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" …
multimodal models. In this study, we collected 654 computer science papers with" …