1 citations · 1 across the 8 of their papers we have counts for
14 papers
CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad
Yongqiang Chen, Chenxi Liu, Zhenhao Chen +3
Evolve-based agent such as AlphaEvolve is one of the notable successes in using Large Language Models (LLMs) to build AI Scientists. These agents tackle open-ended scientific probl…
Unsupervised Synthetic Image Attribution: Alignment and Disentanglement
Zongfang Liu, Guangyi Chen, Boyang Sun +2
As the quality of synthetic images improves, identifying the underlying concepts of model-generated images is becoming increasingly crucial for copyright protection and ensuring mo…
Mirage2Matter: A Physically Grounded Gaussian World Model from Video
Zhengqing Gao, Ziwen Li, Xin Wang +12
The scalability of embodied intelligence is fundamentally constrained by the scarcity of real-world interaction data. While simulation platforms provide a promising alternative, ex…
Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering
Tianjun Yao, Haoxuan Li, Zhiqiang Shen +3
Large Language Models (LLMs) have shown strong inductive reasoning ability across various domains, but their reliability is hindered by the outdated knowledge and hallucinations. R…
Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
Tianjun Yao, Haoxuan Li, Yongqiang Chen +4
Graph Neural Networks (GNNs) often encounter significant performance degradation under distribution shifts between training and test data, hindering their applicability in real-wor…
Concept Concentration for Faithful Representation Intervention
Hongzheng Yang, Yongqiang Chen, Zeyu Qin +4
Representation intervention aims to localize and modify the representations that encode the underlying concepts in large language models (LLMs) to elicit the aligned and expected b…