54 citations · 83 across the 57 of their papers we have counts for
11 papers · 1 filter
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…
SPUR: A Plug-and-Play Framework for Integrating Spatial Audio Understanding and Reasoning into Large Audio-Language Models
S Sakshi, Vaibhavi Lokegaonkar, Neil Zhang +4
Spatial perception is central to auditory intelligence, enabling accurate understanding of real-world acoustic scenes and advancing human-level perception of the world around us. W…
EGOILLUSION: Benchmarking Hallucinations in Egocentric Video Understanding
Ashish Seth, Utkarsh Tyagi, Ramaneswaran Selvakumar +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in complex multimodal tasks. While MLLMs excel at visual perception and reasoning in third-person…
MMAU-Pro: A Challenging and Comprehensive Benchmark for Holistic Evaluation of Audio General Intelligence
Sonal Kumar, Šimon Sedláček, Vaibhavi Lokegaonkar +31
Audio comprehension-including speech, non-speech sounds, and music-is essential for achieving human-level intelligence. Consequently, AI agents must demonstrate holistic audio unde…
Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Models
Arushi Goel, Sreyan Ghosh, Jaehyeon Kim +8
We present Audio Flamingo 3 (AF3), a fully open state-of-the-art (SOTA) large audio-language model that advances reasoning and understanding across speech, sound, and music. AF3 in…
MultiVox: A Benchmark for Evaluating Voice Assistants for Multimodal Interactions
Ramaneswaran Selvakumar, Ashish Seth, Nishit Anand +4
The rapid progress of Large Language Models (LLMs) has empowered omni models to act as voice assistants capable of understanding spoken dialogues. These models can process multimod…
Multi-Domain Audio Question Answering Benchmark Toward Acoustic Content Reasoning
Chao-Han Huck Yang, Sreyan Ghosh, Qing Wang +14
We present Task 5 of the DCASE 2025 Challenge: an Audio Question Answering (AQA) benchmark spanning multiple domains of sound understanding. This task defines three QA subsets (Bio…
Learning Multi-Robot Coordination through Locality-Based Factorized Multi-Agent Actor-Critic Algorithm
Chak Lam Shek, Amrit Singh Bedi, Anjon Basak +5
In this work, we present a novel cooperative multi-agent reinforcement learning method called \textbf{Loc}ality based \textbf{Fac}torized \textbf{M}ulti-Agent \textbf{A}ctor-\textb…
ProSE: Diffusion Priors for Speech Enhancement
Sonal Kumar, Sreyan Ghosh, Utkarsh Tyagi +4
Speech enhancement (SE) is the foundational task of enhancing the clarity and quality of speech in the presence of non-stationary additive noise. While deterministic deep learning…
Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities
Sreyan Ghosh, Zhifeng Kong, Sonal Kumar +6
Understanding and reasoning over non-speech sounds and music are crucial for both humans and AI agents to interact effectively with their environments. In this paper, we introduce…
TSPE: Task-Specific Prompt Ensemble for Improved Zero-Shot Audio Classification
Nishit Anand, Ashish Seth, Ramani Duraiswami +1
Audio-language models (ALMs) excel in zero-shot audio classification, a task where models classify previously unseen audio clips at test time by leveraging descriptive natural lang…