103 citations · 556 across the 52 of their papers we have counts for
12 papers · 1 filter
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…
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…
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…
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-…
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…
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…
Interaction Pattern Disentangling for Multi-Agent Reinforcement Learning
Shunyu Liu, Jie Song, Yihe Zhou +4
Deep cooperative multi-agent reinforcement learning has demonstrated its remarkable success over a wide spectrum of complex control tasks. However, recent advances in multi-agent l…
Ask-AC: An Initiative Advisor-in-the-Loop Actor-Critic Framework
Shunyu Liu, Kaixuan Chen, Na Yu +3
Despite the promising results achieved, state-of-the-art interactive reinforcement learning schemes rely on passively receiving supervision signals from advisor experts, in the for…
Root-aligned SMILES: A Tight Representation for Chemical Reaction Prediction
Zipeng Zhong, Jie Song, Zunlei Feng +6
Chemical reaction prediction, involving forward synthesis and retrosynthesis prediction, is a fundamental problem in organic synthesis. A popular computational paradigm formulates…
Data-Free Adversarial Distillation
Gongfan Fang, Jie Song, Chengchao Shen +3
Knowledge Distillation (KD) has made remarkable progress in the last few years and become a popular paradigm for model compression and knowledge transfer. However, almost all exist…