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Di Zhang

di-zhang-fdu

https://scholar.google.com/citations?user=vxAO250AAAAJ&hl=en

AI & ML interests

AI4Chem, LLM, Green LLM

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posted an update about 5 hours ago

The training dataset of ChemVLM is open-sourced now, have a check! https://huggingface.co/datasets/di-zhang-fdu/chemvlm-sft-datasets papers: https://huggingface.co/papers/2408.07246

updated a dataset about 5 hours ago

di-zhang-fdu/chemvlm-sft-datasets

liked a model 12 days ago

Qwen/Qwen3-VL-8B-Instruct

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The training dataset of ChemVLM is open-sourced now, have a check!
di-zhang-fdu/chemvlm-sft-datasets

papers: Seeing and Understanding: Bridging Vision with Chemical Knowledge Via ChemVLM (2408.07246)

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510

Our new paper Moose-chem 3 introduces experiment-guided hypothesis ranking, a novel setting where candidate hypotheses are prioritized based on experimental feedback from previously tested hypotheses.

To support research in this area, the work proposes a simulator grounded in three domain-informed assumptions that can generate simulated experimental feedback without requiring costly real-world trials.

The simulator is validated on a curated dataset of 124 chemistry hypotheses, and the resulting method outperforms strong pre-experiment baselines. This enables scalable research on feedback-driven hypothesis discovery strategies in scientific domains where empirical validation is expensive or slow.
MOOSE-Chem3: Toward Experiment-Guided Hypothesis Ranking via Simulated Experimental Feedback (2505.17873)

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