3 papers
cs.LG2026
Unlocking the Potentials of Retrieval-Augmented Generation for Diffusion Language Models
Chuanyue Yu, Jiahui Wang, Yuhan Li +6
Diffusion Language Models (DLMs) have recently demonstrated remarkable capabilities in natural language processing tasks. However, the potential of Retrieval-Augmented Generation (…
cs.SD2025
Pushing the Frontier of Audiovisual Perception with Large-Scale Multimodal Correspondence Learning
Apoorv Vyas, Heng-Jui Chang, Cheng-Fu Yang +9
We introduce Perception Encoder Audiovisual, PE-AV, a new family of encoders for audio and video understanding trained with scaled contrastive learning. Built on PE, PE-AV makes se…
cs.AI2024
From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities
Shixin Jiang, Jiafeng Liang, Jiyuan Wang +6
To tackle complex tasks in real-world scenarios, more researchers are focusing on Omni-MLLMs, which aim to achieve omni-modal understanding and generation. Beyond the constraints o…