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Xiao-Youth
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Model Details
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Xiao-Youth
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Input Modalities
Output Modalities
Supported Functionality
python
from transformers import AutoModelForCausalLM, AutoTokenizermodel_id = "Xiao-Youth/LECTOR-4B"tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained(model_id,torch_dtype="auto",device_map="auto",)
For the full LECTOR prompting, rollout, and evaluation pipeline, see the project repository.
This model is intended for research on scientific reasoning graph extraction, logic-aware scientific writing, and content-conditional introduction generation.
The model may produce incorrect reasoning graphs, unsupported claims, or citation errors. Generated text should be manually checked against the source paper content and references before use.
bibtex
@misc{xiao2026lector,title={LECTOR: Joint Optimization of Scientific Reasoning Graphs and Introduction Generation},author={Jiabei Xiao and Yizhou Wang and Chen Tang and Pengze Li and Wanli Ouyang and Shixiang Tang},year={2026},eprint={2605.25964},archivePrefix={arXiv},primaryClass={cs.AI},url={https://arxiv.org/abs/2605.25964},}