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20232026
most citedEvolutionary Retrosynthetic Route Planning

5 citations · 10 across the 18 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.LG2025

AutoSynth: Automated Workflow Optimization for High-Quality Synthetic Dataset Generation via Monte Carlo Tree Search

Shuzhen Bi, Chang Song, Siyu Song +5

Supervised fine-tuning (SFT) of large language models (LLMs) for specialized tasks requires high-quality datasets, but manual curation is prohibitively expensive. Synthetic data ge…

cs.AI2025

EA4LLM: A Gradient-Free Approach to Large Language Model Optimization via Evolutionary Algorithms

WenTao Liu, Siyu Song, Hao Hao +1

In recent years, large language models (LLMs) have made remarkable progress, with model optimization primarily relying on gradient-based optimizers such as Adam. However, these gra…

cs.AI2025

SID: Benchmarking Guided Instruction Capabilities in STEM Education with a Socratic Interdisciplinary Dialogues Dataset

Mei Jiang, Houping Yue, Bingdong Li +4

Fostering students' abilities for knowledge integration and transfer in complex problem-solving scenarios is a core objective of modern education, and interdisciplinary STEM is a k…

cs.CY2025

ELMES: An Automated Framework for Evaluating Large Language Models in Educational Scenarios

Shou'ang Wei, Xinyun Wang, Shuzhen Bi +9

The emergence of Large Language Models (LLMs) presents transformative opportunities for education, generating numerous novel application scenarios. However, significant challenges…

cs.LG2025

EduAlign: Aligning Educational LLMs for Helpfulness, Personalization, and Creativity

Siyu Song, Wentao Liu, Ye Lu +8

Educational language models should pursue three complementary objectives: helpfulness through responsible guidance, personalization to learner needs, and creativity that supports e…

physics.chem-ph2025

A Large Language Model for Chemistry and Retrosynthesis Predictions

Yueqing Zhang, Wentao Liu, Yan Zhang +9

Large language models (LLM) have achieved impressive progress across a broad range of general-purpose tasks, but their effectiveness in chemistry remains limited due to scarce doma…

cs.CL2025

Echo: A Large Language Model with Temporal Episodic Memory

WenTao Liu, Ruohua Zhang, Aimin Zhou +2

Research on large language models (LLMs) has shown remarkable performance in domains such as mathematics, programming, and literary creation. However, most studies have focused on…