DuetDA, a decomposed and dynamic DA framework with model-state gating that assigns each sample two complementary values, and uses a lightweight gate conditioned on the current model state to adaptively integrate them across training, is proposed.
Jianpeng Chen, Wang-Zhi Zhan, Hao-Hui Wang et al.· Proceedings of the 32nd ACM...· 0 citations
REGDIFF is proposed, a generative framework that couples voxel representation with latent space regulation and guided diffusion that outperforms voxel-based generative baselines in geometric plausibility, novelty, and diversity and is suggested to be a strong geometry candidate generator for downstream evaluation.
Wang-Zhi Zhan, Jian-Peng Chen, Dong-Qi Fu et al.· 0 citations
Scientific datasets, such as materials and molecular datasets, are often large, complex, and open-ended, posing a core challenge for data efficiency and model training. While data attribution (DA) offers a principled way to score and select samples for efficient learning, we identify a fundamental misalignment between...
Jianpeng Chen, Wangzhi Zhan, Haohui Wang et al.· Proceedings of the 32nd ACM...· 0 citations
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