7 papers
Video-Robin: Autoregressive Diffusion Planning for Intent-Grounded Video-to-Music Generation
Vaibhavi Lokegaonkar, Aryan Vijay Bhosale, Vishnu Raj +5
Video-to-music (V2M) is the fundamental task of creating background music for an input video. Recent V2M models achieve audiovisual alignment by typically relying on visual conditi…
Audio Flamingo Next: Next-Generation Open Audio-Language Models for Speech, Sound, and Music
Sreyan Ghosh, Arushi Goel, Kaousheik Jayakumar +15
We present Audio Flamingo Next (AF-Next), the next-generation and most capable large audio-language model in the Audio Flamingo series, designed to advance understanding and reason…
Do Audio-Visual Large Language Models Really See and Hear?
Ramaneswaran Selvakumar, Kaousheik Jayakumar, S Sakshi +3
Audio-Visual Large Language Models (AVLLMs) are emerging as unified interfaces to multimodal perception. We present the first mechanistic interpretability study of AVLLMs, analyzin…
Music Flamingo: Scaling Music Understanding in Audio Language Models
Sreyan Ghosh, Arushi Goel, Lasha Koroshinadze +8
We introduce Music Flamingo, a novel large audio-language model designed to advance music (including song) understanding in foundational audio models. While audio-language research…
OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM
Hanrong Ye, Chao-Han Huck Yang, Arushi Goel +29
Advancing machine intelligence requires developing the ability to perceive across multiple modalities, much as humans sense the world. We introduce OmniVinci, an initiative to buil…
UALM: Unified Audio Language Model for Understanding, Generation and Reasoning
Jinchuan Tian, Sang-gil Lee, Zhifeng Kong +11
Recent advances in the audio language modeling (ALM) domain tackle audio understanding and text-to-audio generation as separate tasks. Very few studies attempt to unify these tasks…