1 citations · 1 across the 8 of their papers we have counts for
9 papers
Dr.Credit: Rubric-Grounded Process Credit Assignment for Deep Research Agents
Yingjian Zhu, Zhenyi Wang, Jiaxin Guo +6
Rubric-based tasks are increasingly addressed through reinforcement learning (RL), with rubric scores used as training rewards. However, these rewards typically supervise final ans…
WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering
Yingjian Zhu, Xinming Wang, Kun Ding +3
Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-VQA). Despite recent advancements, pre…
SeaVIS: Sound-Enhanced Association for Online Audio-Visual Instance Segmentation
Yingjian Zhu, Ying Wang, Yuyang Hong +5
Recently, an audio-visual instance segmentation (AVIS) task has been introduced, aiming to identify, segment and track individual sounding instances in videos. However, prevailing…
SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM
Lin Chen, Yingjian Zhu, Qi Yang +3
Open-vocabulary semantic segmentation (OVSS) aims to segment and recognize objects universally. Trained on extensive high-quality segmentation data, the segment anything model (SAM…
MR-Align: Meta-Reasoning Informed Factuality Alignment for Large Reasoning Models
Xinming Wang, Jian Xu, Bin Yu +9
Large reasoning models (LRMs) show strong capabilities in complex reasoning, yet their marginal gains on evidence-dependent factual questions are limited. We find this limitation i…
More Is Better: A MoE-Based Emotion Recognition Framework with Human Preference Alignment
Jun Xie, Yingjian Zhu, Feng Chen +9
In this paper, we present our solution for the semi-supervised learning track (MER-SEMI) in MER2025. We propose a comprehensive framework, grounded in the principle that "more is b…
Multimodal Video Emotion Recognition with Reliable Reasoning Priors
Zhepeng Wang, Yingjian Zhu, Guanghao Dong +4
This study investigates the integration of trustworthy prior reasoning knowledge from MLLMs into multimodal emotion recognition. We employ Gemini to generate fine-grained, modality…
Team of One: Cracking Complex Video QA with Model Synergy
Jun Xie, Zhaoran Zhao, Xiongjun Guan +5
We propose a novel framework for open-ended video question answering that enhances reasoning depth and robustness in complex real-world scenarios, as benchmarked on the CVRR-ES dat…
Four Eyes Are Better Than Two: Harnessing the Collaborative Potential of Large Models via Differentiated Thinking and Complementary Ensembles
Jun Xie, Xiongjun Guan, Yingjian Zhu +5
In this paper, we present the runner-up solution for the Ego4D EgoSchema Challenge at CVPR 2025 (Confirmed on May 20, 2025). Inspired by the success of large models, we evaluate an…