4 papers
MoD-DPO: Towards Mitigating Cross-modal Hallucinations in Omni LLMs using Modality Decoupled Preference Optimization
Ashutosh Chaubey, Jiacheng Pang, Mohammad Soleymani
Omni-modal large language models (omni LLMs) have recently achieved strong performance across audiovisual understanding tasks, yet they remain highly susceptible to cross-modal hal…
Adaptive Collaboration with Humans: Metacognitive Policy Optimization for Multi-Agent LLMs with Continual Learning
Wei Yang, Defu Cao, Jiacheng Pang +2
While scaling individual Large Language Models (LLMs) has delivered remarkable progress, the next frontier lies in scaling collaboration through multi-agent systems (MAS). However,…
AVERE: Improving Audiovisual Emotion Reasoning with Preference Optimization
Ashutosh Chaubey, Jiacheng Pang, Maksim Siniukov +1
Emotion understanding is essential for building socially intelligent agents. Although recent multimodal large language models have shown strong performance on this task, two key ch…
Maestro: Learning to Collaborate via Conditional Listwise Policy Optimization for Multi-Agent LLMs
Wei Yang, Jiacheng Pang, Shixuan Li +3
Multi-agent systems (MAS) built on Large Language Models (LLMs) are being used to approach complex problems and can surpass single model inference. However, their success hinges on…