Sora: A review on background, technology, limitations, and opportunities of large vision models
Sora is a text-to-video generative AI model, released by OpenAI in February 2024. The
model is trained to generate videos of realistic or imaginative scenes from text instructions …
model is trained to generate videos of realistic or imaginative scenes from text instructions …
Knowledge graphs meet multi-modal learning: A comprehensive survey
Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
Robustness of Structured Data Extraction from In-Plane Rotated Documents Using Multi-Modal Large Language Models (LLM)
A Biswas, W Talukdar - Journal of Artificial Intelligence Research, 2024 - arxiv.org
Multi-modal large language models (LLMs) have shown remarkable performance in various
natural language processing tasks, including data extraction from documents. However, the …
natural language processing tasks, including data extraction from documents. However, the …
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 …
Rlaif-v: Aligning mllms through open-source ai feedback for super gpt-4v trustworthiness
Learning from feedback reduces the hallucination of multimodal large language models
(MLLMs) by aligning them with human preferences. While traditional methods rely on labor …
(MLLMs) by aligning them with human preferences. While traditional methods rely on labor …
Visual hallucinations of multi-modal large language models
Visual hallucination (VH) means that a multi-modal LLM (MLLM) imagines incorrect details
about an image in visual question answering. Existing studies find VH instances only in …
about an image in visual question answering. Existing studies find VH instances only in …
Less is more: Mitigating multimodal hallucination from an eos decision perspective
Large Multimodal Models (LMMs) often suffer from multimodal hallucinations, wherein they
may create content that is not present in the visual inputs. In this paper, we explore a new …
may create content that is not present in the visual inputs. In this paper, we explore a new …
What if...?: Counterfactual inception to mitigate hallucination effects in large multimodal models
This paper presents a way of enhancing the reliability of Large Multimodal Models (LMMs) in
addressing hallucination effects, where models generate incorrect or unrelated responses …
addressing hallucination effects, where models generate incorrect or unrelated responses …
LightHouse: A Survey of AGI Hallucination
F Wang - arXiv preprint arXiv:2401.06792, 2024 - arxiv.org
With the development of artificial intelligence, large-scale models have become increasingly
intelligent. However, numerous studies indicate that hallucinations within these large …
intelligent. However, numerous studies indicate that hallucinations within these large …
Seeing Clearly, Answering Incorrectly: A Multimodal Robustness Benchmark for Evaluating MLLMs on Leading Questions
Multimodal Large Language Models (MLLMs) have exhibited impressive capabilities in
visual understanding and reasoning, providing sightly reasonable answers, such as image …
visual understanding and reasoning, providing sightly reasonable answers, such as image …