11 citations · 20 across the 18 of their papers we have counts for
10 papers · 1 filter
H-OPD: Confidence Aware Heterogeneous Multi-Teacher Multimodal On-policy Distillation
Qixiang Yin, Huanjin Yao, Yuchen Cai +5
On-policy distillation (OPD) has recently emerged as an effective post-training paradigm by providing supervision on student-generated trajectories. However, existing OPD methods f…
MM-DeepResearch: A Simple and Effective Multimodal Agentic Search Baseline
Huanjin Yao, Qixiang Yin, Min Yang +5
We aim to develop a multimodal research agent capable of explicit reasoning and planning, multi-tool invocation, and cross-modal information synthesis, enabling it to conduct deep…
CoLoGen: Progressive Learning of Concept-Localization Duality for Unified Image Generation
YuXin Song, Yu Lu, Haoyuan Sun +6
Unified conditional image generation remains difficult because different tasks depend on fundamentally different internal representations. Some require conceptual understanding for…
A Survey on Agentic Multimodal Large Language Models
Huanjin Yao, Ruifei Zhang, Jiaxing Huang +8
With the recent emergence of revolutionary autonomous agentic systems, research community is witnessing a significant shift from traditional static, passive, and domain-specific AI…
R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO
Huanjin Yao, Qixiang Yin, Jingyi Zhang +8
In this work, we aim to incentivize the reasoning ability of Multimodal Large Language Models (MLLMs) via reinforcement learning (RL) and develop an effective approach that mitigat…
Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Huanjin Yao, Jiaxing Huang, Wenhao Wu +8
In this work, we aim to develop an MLLM that understands and solves questions by learning to create each intermediate step of the reasoning involved till the final answer. To this…
Automated Multi-level Preference for MLLMs
Mengxi Zhang, Wenhao Wu, Yu Lu +8
Current multimodal Large Language Models (MLLMs) suffer from ``hallucination'', occasionally generating responses that are not grounded in the input images. To tackle this challeng…
Dense Connector for MLLMs
Huanjin Yao, Wenhao Wu, Taojiannan Yang +7
Do we fully leverage the potential of visual encoder in Multimodal Large Language Models (MLLMs)? The recent outstanding performance of MLLMs in multimodal understanding has garner…
Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
Huanjin Yao, Wenhao Wu, Zhiheng Li
Large pre-trained vision models achieve impressive success in computer vision. However, fully fine-tuning large models for downstream tasks, particularly in video understanding, ca…
GPT4Vis: What Can GPT-4 Do for Zero-shot Visual Recognition?
Wenhao Wu, Huanjin Yao, Mengxi Zhang +3
This paper does not present a novel method. Instead, it delves into an essential, yet must-know baseline in light of the latest advancements in Generative Artificial Intelligence (…