16 citations · 42 across the 18 of their papers we have counts for
18 papers
AudioDER: A Deduplication-Enhanced Reasoning Dataset for Post-Training Large Audio-Language Models
Hui Geng, Yi Su, Zijian Gao +5
Recent advances in pretrained large audio-language models (LALMs) have demonstrated strong capabilities across speech, sound, and music. To adapt these models to downstream tasks w…
MAny: Merge Anything for Multimodal Continual Instruction Tuning
Zijian Gao, Wangwang Jia, Xingxing Zhang +6
Multimodal Continual Instruction Tuning (MCIT) is essential for sequential task adaptation of Multimodal Large Language Models (MLLMs) but is severely restricted by catastrophic fo…
Data-driven active learning approaches for accelerating materials discovery
Jiaxin Chen, Tianjiao Wan, Hui Geng +10
Materials discovery is a cornerstone of modern technological advancement, yet it remains constrained by traditional trial-and-error paradigms and the inherent bias of human intuiti…
NTIRE 2025 Image Shadow Removal Challenge Report
Florin-Alexandru Vasluianu, Tim Seizinger, Zhuyun Zhou +79
This work examines the findings of the NTIRE 2025 Shadow Removal Challenge. A total of 306 participants have registered, with 17 teams successfully submitting their solutions durin…
NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces
Pierluigi Zama Ramirez, Fabio Tosi, Luigi Di Stefano +36
This paper reports on the NTIRE 2025 challenge on HR Depth From images of Specular and Transparent surfaces, held in conjunction with the New Trends in Image Restoration and Enhanc…
NTIRE 2025 Challenge on Event-Based Image Deblurring: Methods and Results
Lei Sun, Andrea Alfarano, Peiqi Duan +85
This paper presents an overview of NTIRE 2025 the First Challenge on Event-Based Image Deblurring, detailing the proposed methodologies and corresponding results. The primary goal…
AudioCIL: A Python Toolbox for Audio Class-Incremental Learning with Multiple Scenes
Qisheng Xu, Yulin Sun, Yi Su +7
Deep learning, with its robust aotomatic feature extraction capabilities, has demonstrated significant success in audio signal processing. Typically, these methods rely on static,…
Exploring structure diversity in atomic resolution microscopy with graph neural networks
Zheng Luo, Ming Feng, Zijian Gao +9
The emergence of deep learning (DL) has provided great opportunities for the high-throughput analysis of atomic-resolution micrographs. However, the DL models trained by image patc…
Optimistic Model Rollouts for Pessimistic Offline Policy Optimization
Yuanzhao Zhai, Yiying Li, Zijian Gao +5
Model-based offline reinforcement learning (RL) has made remarkable progress, offering a promising avenue for improving generalization with synthetic model rollouts. Existing works…
Diversifying Message Aggregation in Multi-Agent Communication via Normalized Tensor Nuclear Norm Regularization
Yuanzhao Zhai, Kele Xu, Bo Ding +3
Aggregating messages is a key component for the communication of multi-agent reinforcement learning (Comm-MARL). Recently, it has witnessed the prevalence of graph attention networ…
Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning
Zijian Gao, Kele Xu, Yuanzhao Zhai +4
Under sparse extrinsic reward settings, reinforcement learning has remained challenging, despite surging interests in this field. Previous attempts suggest that intrinsic reward ca…
Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration
Zijian Gao, YiYing Li, Kele Xu +5
The sparsity of extrinsic rewards poses a serious challenge for reinforcement learning (RL). Currently, many efforts have been made on curiosity which can provide a representative…
Nuclear Norm Maximization Based Curiosity-Driven Learning
Chao Chen, Zijian Gao, Kele Xu +5
To handle the sparsity of the extrinsic rewards in reinforcement learning, researchers have proposed intrinsic reward which enables the agent to learn the skills that might come in…
CLIP2TV: Align, Match and Distill for Video-Text Retrieval
Zijian Gao, Jingyu Liu, Weiqi Sun +3
Modern video-text retrieval frameworks basically consist of three parts: video encoder, text encoder and the similarity head. With the success on both visual and textual representa…
Coarse to Fine: Video Retrieval before Moment Localization
Zijian Gao, Huanyu Liu, Jingyu Liu
The current state-of-the-art methods for video corpus moment retrieval (VCMR) often use similarity-based feature alignment approach for the sake of convenience and speed. However,…
KnowSR: Knowledge Sharing among Homogeneous Agents in Multi-agent Reinforcement Learning
Zijian Gao, Kele Xu, Bo Ding +3
Recently, deep reinforcement learning (RL) algorithms have made great progress in multi-agent domain. However, due to characteristics of RL, training for complex tasks would be res…
KnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning
Zijian Gao, Kele Xu, Bo Ding +3
Recently, deep Reinforcement Learning (RL) algorithms have achieved dramatically progress in the multi-agent area. However, training the increasingly complex tasks would be time-co…
Random forest model identifies serve strength as a key predictor of tennis match outcome
Zijian Gao, Amanda Kowalczyk
Tennis is a popular sport worldwide, boasting millions of fans and numerous national and international tournaments. Like many sports, tennis has benefitted from the popularity of r…