From show to tell: A survey on deep learning-based image captioning
Connecting Vision and Language plays an essential role in Generative Intelligence. For this
reason, large research efforts have been devoted to image captioning, ie describing images …
reason, large research efforts have been devoted to image captioning, ie describing images …
Multimodal research in vision and language: A review of current and emerging trends
Deep Learning and its applications have cascaded impactful research and development
with a diverse range of modalities present in the real-world data. More recently, this has …
with a diverse range of modalities present in the real-world data. More recently, this has …
HallusionBench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models
We introduce" HallusionBench" a comprehensive benchmark designed for the evaluation of
image-context reasoning. This benchmark presents significant challenges to advanced large …
image-context reasoning. This benchmark presents significant challenges to advanced large …
Multi-modal knowledge graph construction and application: A survey
Recent years have witnessed the resurgence of knowledge engineering which is featured
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
Hallusionbench: You see what you think? or you think what you see? an image-context reasoning benchmark challenging for gpt-4v (ision), llava-1.5, and other multi …
Large language models (LLMs), after being aligned with vision models and integrated into
vision-language models (VLMs), can bring impressive improvement in image reasoning …
vision-language models (VLMs), can bring impressive improvement in image reasoning …
Exploiting BERT for multimodal target sentiment classification through input space translation
Multimodal target/aspect sentiment classification combines multimodal sentiment analysis
and aspect/target sentiment classification. The goal of the task is to combine vision and …
and aspect/target sentiment classification. The goal of the task is to combine vision and …
Ei-clip: Entity-aware interventional contrastive learning for e-commerce cross-modal retrieval
Abstract recommendation, and marketing services. Extensive efforts have been made to
conquer the cross-modal retrieval problem in the general domain. When it comes to E …
conquer the cross-modal retrieval problem in the general domain. When it comes to E …
Visual news: Benchmark and challenges in news image captioning
We propose Visual News Captioner, an entity-aware model for the task of news image
captioning. We also introduce Visual News, a large-scale benchmark consisting of more …
captioning. We also introduce Visual News, a large-scale benchmark consisting of more …
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 …
Let there be a clock on the beach: Reducing object hallucination in image captioning
Explaining an image with missing or non-existent objects is known as object bias
(hallucination) in image captioning. This behaviour is quite common in the state-of-the-art …
(hallucination) in image captioning. This behaviour is quite common in the state-of-the-art …