5 citations · 10 across the 23 of their papers we have counts for
16 papers · 1 filter
AdaVDR: Adaptive Tool Use and Reflection for Video Deep Research
Xintong Zhang, Xiaomeng Fan, Shilin Yan +7
Video deep research aims to answer questions by jointly understanding video content and retrieving external knowledge from the open Web. However, these tasks often require diverse…
Reliability-Prioritized Fine-Grained Generation in Multimodal Large
Xiaomeng Fan, Wei Wu, Yuwei Wu +9
Multimodal large language models (MLLMs) are increasingly expected to generate fine-grained descriptions of visual content. However, we observe and theoretically show that generati…
Facial Expression Generation Aligned with Human Preference for Natural Dyadic Interaction
Xu Chen, Rui Gao, Xinjie Zhang +5
Achieving natural dyadic interaction requires generating facial expressions that are emotionally appropriate and socially aligned with human preference. Human feedback offers a com…
Bridging Modality Disconnect in Self-Reflection via Closed-Loop Visually Grounded Verification
Haoyu Zhang, Yuwei Wu, Pengxiang Li +6
In the era of Vision-Language Models (VLMs), enhancing multimodal reasoning capabilities remains a critical challenge, particularly in handling ambiguous or complex visual inputs,…
AdaptMMBench: Benchmarking Adaptive Multimodal Reasoning for Mode Selection and Reasoning Process
Xintong Zhang, Xiaowen Zhang, Jingrong Wu +8
Adaptive multimodal reasoning has emerged as a promising frontier in Vision-Language Models (VLMs), aiming to dynamically modulate between tool-augmented visual reasoning and text…
Beyond the Seen: Bounded Distribution Estimation for Open-Vocabulary Learning
Xiaomeng Fan, Yuchuan Mao, Zhi Gao +3
Open-vocabulary learning requires modeling the data distribution in open environments, which consists of both seen-class and unseen-class data. Existing methods estimate the distri…
Modality Alignment across Trees on Heterogeneous Hyperbolic Manifolds
Wei Wu, Xiaomeng Fan, Yuwei Wu +4
Modality alignment is critical for vision-language models (VLMs) to effectively integrate information across modalities. However, existing methods extract hierarchical features fro…
Adaptive Model Ensemble for Continual Learning
Yuchuan Mao, Zhi Gao, Xiaomeng Fan +3
Model ensemble is an effective strategy in continual learning, which alleviates catastrophic forgetting by interpolating model parameters, achieving knowledge fusion learned from d…
MotionFlux: Efficient Text-Guided Motion Generation through Rectified Flow Matching and Preference Alignment
Zhiting Gao, Dan Song, Diqiong Jiang +2
Motion generation is essential for animating virtual characters and embodied agents. While recent text-driven methods have made significant strides, they often struggle with achiev…
Geometry-aware Distance Measure for Diverse Hierarchical Structures in Hyperbolic Spaces
Pengxiang Li, Yuwei Wu, Zhi Gao +5
Learning in hyperbolic spaces has attracted increasing attention due to its superior ability to model hierarchical structures of data. Most existing hyperbolic learning methods use…
A Set-to-Set Distance Measure in Hyperbolic Space
Pengxiang Li, Wei Wu, Zhi Gao +6
We propose a hyperbolic set-to-set distance measure for computing dissimilarity between sets in hyperbolic space. While point-to-point distances in hyperbolic space effectively cap…
Hyperbolic Dual Feature Augmentation for Open-Environment
Peilin Yu, Yuwei Wu, Zhi Gao +3
Feature augmentation generates novel samples in the feature space, providing an effective way to enhance the generalization ability of learning algorithms with hyperbolic geometry.…
Adaptive Chain-of-Focus Reasoning via Dynamic Visual Search and Zooming for Efficient VLMs
Xintong Zhang, Zhi Gao, Bofei Zhang +8
Vision language models (VLMs) have achieved impressive performance across a variety of computer vision tasks. However, the multimodal reasoning capability has not been fully explor…
FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models
Pengxiang Li, Zhi Gao, Bofei Zhang +6
Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinemen…
Exploring Data Geometry for Continual Learning
Zhi Gao, Chen Xu, Feng Li +3
Continual learning aims to efficiently learn from a non-stationary stream of data while avoiding forgetting the knowledge of old data. In many practical applications, data complies…
Learning a Robust Representation via a Deep Network on Symmetric Positive Definite Manifolds
Zhi Gao, Yuwei Wu, Xingyuan Bu +1
Recent studies have shown that aggregating convolutional features of a pre-trained Convolutional Neural Network (CNN) can obtain impressive performance for a variety of visual task…