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 …

Causal inference has shown potential in enhancing the predictive accuracy, fairness,
robustness, and explainability of Natural Language Processing (NLP) models by capturing …

Despite the promising progress in multi-modal tasks, current large multi-modal models
(LMM) are prone to hallucinating inconsistent descriptions with respect to the associated …

We introduce" HallusionBench" a comprehensive benchmark designed for the evaluation of
image-context reasoning. This benchmark presents significant challenges to advanced large …

Large language models (LLMs), after being aligned with vision models and integrated into
vision-language models (VLMs), can bring impressive improvement in image reasoning …

Despite the promising progress in multi-modal tasks, current large multi-modal models
(LMMs) are prone to hallucinating inconsistent descriptions with respect to the associated …

Misinformation has become a pressing issue. Fake media, in both visual and textual forms,
is widespread on the web. While various deepfake detection and text fake news detection …

Existing information retrieval (IR) models often assume a homogeneous format, limiting their
applicability to diverse user needs, such as searching for images with text descriptions …

With the rapid development of large language models (LLMs) and their integration into large
multimodal models (LMMs), there has been impressive progress in zero-shot completion of …

Large-scale multi-modal pre-training models such as CLIP and PaLI exhibit strong
generalization on various visual domains and tasks. However, existing image classification …