Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

Multimodal Large Language Model (MLLM) recently has been a new rising research
hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform …

With the widespread application of the Transformer architecture in various modalities,
including vision, the technology of large language models is evolving from a single modality …

In the domain of audio processing, Transfer Learning has facilitated the rise of Self-
Supervised Learning and Zero-Shot Learning techniques. These approaches have led to …

Vision and text have been fully explored in contemporary video-text foundational models,
while other modalities such as audio and subtitles in videos have not received sufficient …

Although audio generation shares commonalities across different types of audio, such as
speech, music, and sound effects, designing models for each type requires careful …

Recent advancements in Multimodal Large Language Models (MLLMs) underscore the
significance of scalable models and data to boost performance, yet this often incurs …

Language-queried audio source separation (LASS) is a new paradigm for computational
auditory scene analysis (CASA). LASS aims to separate a target sound from an audio …

This paper focuses on the challenge of answering questions in scenarios that are composed
of rich and complex dynamic audio-visual components. Although existing Multimodal Large …