4 papers
Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding
Leilei Guo, Antonio Carlos Rivera, Peiyu Tang +2
Large Language Models (LLMs) and Vision-Language Large Models (LVLMs) have achieved remarkable progress in natural language processing and multimodal understanding. Despite their i…
Contextual Candor: Enhancing LLM Trustworthiness Through Hierarchical Unanswerability Detection
Steven Robinson, Antonio Carlos Rivera
The pervasive deployment of large language models (LLMs) in conversational AI systems has revolutionized information access, yet their propensity for generating factually unsupport…
Leveraging Retrieval-Augmented Tags for Large Vision-Language Understanding in Complex Scenes
Antonio Carlos Rivera, Anthony Moore, Steven Robinson
Object-aware reasoning in vision-language tasks poses significant challenges for current models, particularly in handling unseen objects, reducing hallucinations, and capturing fin…
Coal Mining Question Answering with LLMs
Antonio Carlos Rivera, Anthony Moore, Steven Robinson
In this paper, we present a novel approach to coal mining question answering (QA) using large language models (LLMs) combined with tailored prompt engineering techniques. Coal mini…