1 citations · 1 across the 8 of their papers we have counts for
9 papers
Fair Allocation of Divisible Goods under Non-Linear Valuations
Haris Aziz, Zixu He, Xinhang Lu +1
We study the problem of dividing homogeneous divisible goods among agents with non-linear valuations. Specifically, the value that an agent gains from a given good depends only on…
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…
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…
Measuring Epistemic Humility in Multimodal Large Language Models
Bingkui Tong, Jiaer Xia, Sifeng Shang +1
Hallucinations in multimodal large language models (MLLMs), where a model generates content inconsistent with the input image, pose significant risks in real-world applications. Ex…
Bootstrapping Grounded Chain-of-Thought in Multimodal LLMs for Data-Efficient Model Adaptation
Jiaer Xia, Bingkui Tong, Yuhang Zang +2
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in interpreting images using natural language. However, without using large-scale datasets for re…
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…
Fine-tuning Quantized Neural Networks with Zeroth-order Optimization
Sifeng Shang, Jiayi Zhou, Chenyu Lin +2
As the size of large language models grows exponentially, GPU memory has become a bottleneck for adapting these models to downstream tasks. In this paper, we aim to push the limits…
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…