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 …

An emerging area of research in situated and multimodal interactive conversations (SIMMC)
includes interactions in scientific papers. Since scientific papers are primarily composed of …

With the rapid growth in sensor data, effectively interpreting and interfacing with these data
in a human-understandable way has become crucial. While existing research primarily …

In many language processing tasks including most notably Large Language Modeling
(LLM), retrieval augmentation improves the performance of the models by adding …

Modern optimizers such as AdamW, equipped with momentum and adaptive learning rate,
are designed to escape local minima and explore the vast parameter space. This …

This paper presents a new approach to form-filling by reformulating the task as multimodal
natural language Question Answering (QA). The reformulation is achieved by first translating …

Integrated with multi-modal learning, knowledge graphs (KGs) as structured knowledge
repositories, can enhance AI for processing and understanding complex, real-world data …

Robust fine-tuning aims to adapt large foundation models to downstream tasks while
preserving their robustness to distribution shifts. Existing methods primarily focus on …