arXiv subjects

Yongjin Chen

Publications and source records attributed to Yongjin Chen.

3 recordsLinked to original sources

arXiv2026

Story2Proposal: A Scaffold for Structured Scientific Paper Writing

Generating scientific manuscripts requires maintaining alignment between narrative reasoning, experimental evidence, and visual artifacts across the document lifecycle. Existing language-model generation pipelines rely on unconstrained text synthesis with validation applied only after generation, often producing structural drift, missing figures or tables, and cross-section inconsistencies. We introduce Story2Proposal, a contract-governed multi-agent framework that converts a research story into a structured manuscript through coordinated agents operating under a persistent shared visual contract. The system organizes architect, writer, refiner, and renderer agents around a contract state that tracks section structure and registered visual elements, while evaluation agents supply feedback in a generate evaluate adapt loop that updates the contract during generation. Experiments on tasks derived from the Jericho research corpus show that Story2Proposal achieved an expert evaluation score of 6.145 versus 3.963 for DirectChat (+2.182) across GPT, Claude, Gemini, and Qwen backbones. Compared with the structured generation baseline Fars, Story2Proposal obtained an average score of 5.705 versus 5.197, indicating improved structural consistency and visual alignment.

cs.CL↗

arXiv2026

Idea2Story: An Automated Pipeline for Transforming Research Concepts into Complete Scientific Narratives

Autonomous scientific discovery with large language model (LLM)-based agents has recently made substantial progress, demonstrating the ability to automate end-to-end research workflows. However, existing systems largely rely on runtime-centric execution paradigms, repeatedly reading, summarizing, and reasoning over large volumes of scientific literature online. This on-the-spot computation strategy incurs high computational cost, suffers from context window limitations, and often leads to brittle reasoning and hallucination. We propose Idea2Story, a pre-computation-driven framework for autonomous scientific discovery that shifts literature understanding from online reasoning to offline knowledge construction. Idea2Story continuously collects peer-reviewed papers together with their review feedback, extracts core methodological units, composes reusable research patterns, and organizes them into a structured methodological knowledge graph. At runtime, underspecified user research intents are aligned to established research paradigms, enabling efficient retrieval and reuse of high-quality research patterns instead of open-ended generation and trial-and-error. By grounding research planning and execution in a pre-built knowledge graph, Idea2Story alleviates the context window bottleneck of LLMs and substantially reduces repeated runtime reasoning over literature. We conduct qualitative analyses and preliminary empirical studies demonstrating that Idea2Story can generate coherent, methodologically grounded, and novel research patterns, and can produce several high-quality research demonstrations in an end-to-end setting. These results suggest that offline knowledge construction provides a practical and scalable foundation for reliable autonomous scientific discovery.

cs.CE↗

arXiv2025

Investigations of key issues on the reproducibility of high-Tc superconductivity emerging from compressed La3Ni2O7

Recently, the signatures of superconductivity near 80 K have been discovered in the single crystal of La3Ni2O7 under pressure, which makes it a new candidate of the high-temperature superconductors dominated by 3d transition elements after the cuprate and iron-pnictide superconductors. However, there are several critical questions that have been perplexing the scientific community. These questions include (1) what factors contribute to the inconsistent reproducibility of the experimental results? (2) what is the fundamental nature of pressure-induced superconductivity: bulk or non-bulk (filamentary-like)? (3) where does the superconducting phase locate within the sample if it is filamentary-like? (4) is the oxygen content important for developing and stabilizing its superconductivity? In this study, we employ comprehensive high-pressure techniques to address these crucial issues. Through our modulated ac susceptibility measurements, we are the first to find that the superconductivity in this nickelate is filamentary-like. Our scanning transmission electron microscopy (STEM) investigations suggest that the filamentary-like superconductivity most likely emerges at the interface between the La3Ni2O7 and La4Ni3O10 phases. By tuning the oxygen content on the polycrystalline La3Ni2O7, we also find that the oxygen content plays vital role for developing and stabilizing its superconductivity. The upper and lower bounds of the oxygen content are 7.35 and 6.89, respectively. Our results provide not only new insights into understanding the puzzling issues in this material, but also significant information for achieving a better understanding on the superconductivity of this material.

cond-mat.supr-con↗