103 citations · 556 across the 52 of their papers we have counts for
52 papers
Channel-wise Dynamic Knowledge Distillation via Adaptive Sample Generation for Action Recognition
Ping Li, Chenhao Ping, Jie Song +1
Knowledge Distillation (KD) offers a promising yet underexplored path for compressing large action recognition models. However, existing KD methods suffer from two key limitations:…
RS3DBench: A Comprehensive Benchmark for 3D Spatial Perception in Remote Sensing
Jiayu Wang, Ruizhi Wang, Jie Song +4
In this paper, we introduce a novel benchmark designed to propel the advancement of general-purpose, large-scale 3D vision models for remote sensing imagery. While several datasets…
Training Data Provenance Verification: Did Your Model Use Synthetic Data from My Generative Model for Training?
Yuechen Xie, Jie Song, Huiqiong Wang +1
High-quality open-source text-to-image models have lowered the threshold for obtaining photorealistic images significantly, but also face potential risks of misuse. Specifically, s…
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue +5
High-quality open-source datasets, which necessitate substantial efforts for curation, has become the primary catalyst for the swift progress of deep learning. Concurrently, protec…
Training-free Heterogeneous Model Merging
Zhengqi Xu, Han Zheng, Jie Song +2
Model merging has attracted significant attention as a powerful paradigm for model reuse, facilitating the integration of task-specific models into a singular, versatile framework…
On the Evaluation Consistency of Attribution-based Explanations
Jiarui Duan, Haoling Li, Haofei Zhang +5
Attribution-based explanations are garnering increasing attention recently and have emerged as the predominant approach towards \textit{eXplanable Artificial Intelligence}~(XAI). H…
A Large-scale Universal Evaluation Benchmark For Face Forgery Detection
Yijun Bei, Hengrui Lou, Jinsong Geng +5
With the rapid development of AI-generated content (AIGC) technology, the production of realistic fake facial images and videos that deceive human visual perception has become poss…
A Comprehensive Study of Structural Pruning for Vision Models
Changhao Li, Haoling Li, Mengqi Xue +6
Structural pruning has emerged as a promising approach for producing more efficient models. Nevertheless, the community suffers from a lack of standardized benchmarks and metrics,…
On the Concept Trustworthiness in Concept Bottleneck Models
Qihan Huang, Jie Song, Jingwen Hu +3
Concept Bottleneck Models (CBMs), which break down the reasoning process into the input-to-concept mapping and the concept-to-label prediction, have garnered significant attention…
Training-Free Pretrained Model Merging
Zhengqi Xu, Ke Yuan, Huiqiong Wang +3
Recently, model merging techniques have surfaced as a solution to combine multiple single-talent models into a single multi-talent model. However, previous endeavors in this field…
Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning
Yaoquan Wei, Shunyu Liu, Jie Song +4
Action advising endeavors to leverage supplementary guidance from expert teachers to alleviate the issue of sampling inefficiency in Deep Reinforcement Learning (DRL). Previous age…
ModelGiF: Gradient Fields for Model Functional Distance
Jie Song, Zhengqi Xu, Sai Wu +2
The last decade has witnessed the success of deep learning and the surge of publicly released trained models, which necessitates the quantification of the model functional distance…
Lookaround Optimizer: steps around, 1 step average
Jiangtao Zhang, Shunyu Liu, Jie Song +3
Weight Average (WA) is an active research topic due to its simplicity in ensembling deep networks and the effectiveness in promoting generalization. Existing weight average approac…
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?
Yihe Zhou, Shunyu Liu, Yunpeng Qing +4
Centralized Training with Decentralized Execution (CTDE) has recently emerged as a popular framework for cooperative Multi-Agent Reinforcement Learning (MARL), where agents can use…
Temporal Aggregation and Propagation Graph Neural Networks for Dynamic Representation
Tongya Zheng, Xinchao Wang, Zunlei Feng +6
Temporal graphs exhibit dynamic interactions between nodes over continuous time, whose topologies evolve with time elapsing. The whole temporal neighborhood of nodes reveals the va…
Generalization Matters: Loss Minima Flattening via Parameter Hybridization for Efficient Online Knowledge Distillation
Tianli Zhang, Mengqi Xue, Jiangtao Zhang +5
Most existing online knowledge distillation(OKD) techniques typically require sophisticated modules to produce diverse knowledge for improving students' generalization ability. In…
Schema Inference for Interpretable Image Classification
Haofei Zhang, Mengqi Xue, Xiaokang Liu +3
In this paper, we study a novel inference paradigm, termed as schema inference, that learns to deductively infer the explainable predictions by rebuilding the prior deep neural net…
Recent advances in artificial intelligence for retrosynthesis
Zipeng Zhong, Jie Song, Zunlei Feng +5
Retrosynthesis is the cornerstone of organic chemistry, providing chemists in material and drug manufacturing access to poorly available and brand-new molecules. Conventional rule-…
Evaluation and Improvement of Interpretability for Self-Explainable Part-Prototype Networks
Qihan Huang, Mengqi Xue, Wenqi Huang +4
Part-prototype networks (e.g., ProtoPNet, ProtoTree, and ProtoPool) have attracted broad research interest for their intrinsic interpretability and comparable accuracy to non-inter…
Contrastive Identity-Aware Learning for Multi-Agent Value Decomposition
Shunyu Liu, Yihe Zhou, Jie Song +5
Value Decomposition (VD) aims to deduce the contributions of agents for decentralized policies in the presence of only global rewards, and has recently emerged as a powerful credit…
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges
Yunpeng Qing, Shunyu Liu, Jie Song +4
Reinforcement Learning (RL) is a popular machine learning paradigm where intelligent agents interact with the environment to fulfill a long-term goal. Driven by the resurgence of d…
Attention Diversification for Domain Generalization
Rang Meng, Xianfeng Li, Weijie Chen +7
Convolutional neural networks (CNNs) have demonstrated gratifying results at learning discriminative features. However, when applied to unseen domains, state-of-the-art models are…
A Survey of Neural Trees
Haoling Li, Jie Song, Mengqi Xue +4
Neural networks (NNs) and decision trees (DTs) are both popular models of machine learning, yet coming with mutually exclusive advantages and limitations. To bring the best of the…
ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition
Mengqi Xue, Qihan Huang, Haofei Zhang +4
Prototypical part network (ProtoPNet) has drawn wide attention and boosted many follow-up studies due to its self-explanatory property for explainable artificial intelligence (XAI)…