7 papers · 1 filter
Measuring Epistemic Humility in Multimodal Large Language Models
Bingkui Tong, Jiaer Xia, Sifeng Shang +1
Hallucinations in multimodal large language models (MLLMs) -- where the model generates content inconsistent with the input image -- pose significant risks in real-world applicatio…
Streaming Video Instruction Tuning
Jiaer Xia, Peixian Chen, Mengdan Zhang +2
We present Streamo, a real-time streaming video LLM that serves as a general-purpose interactive assistant. Unlike existing online video models that focus narrowly on question answ…
Learning to Think Fast and Slow for Visual Language Models
Chenyu Lin, Cheng Chi, Jinlin Wu +2
When faced with complex problems, we tend to engage in slower, more deliberate thinking. In contrast, for simple questions we give quick, intuitive responses. This dual-system thin…
Visionary-R1: Mitigating Shortcuts in Visual Reasoning with Reinforcement Learning
Jiaer Xia, Yuhang Zang, Peng Gao +2
Learning general-purpose reasoning capabilities has long been a challenging problem in AI. Recent research in large language models (LLMs), such as DeepSeek-R1, has shown that rein…
Mitigating Hallucination in Multimodal LLMs with Layer Contrastive Decoding
Bingkui Tong, Jiaer Xia, Kaiyang Zhou
Multimodal Large Language Models (MLLMs) have shown impressive perception and reasoning capabilities, yet they often suffer from hallucinations -- generating outputs that are lingu…
Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models
Hao Dong, Moru Liu, Kaiyang Zhou +4
In real-world scenarios, achieving domain adaptation and generalization poses significant challenges, as models must adapt to or generalize across unknown target distributions. Ext…