5 papers
Internalizing Academic Writing Workflows for Introduction Generation via Struct-Aware Policy Learning
Meicong Zhang, Tiancheng Su, Jiahao Cheng +3
Generating a rigorous paper introduction with large language models (LLMs) remains challenging, since it requires coordinating background, gap identification, method and contributi…
MoRI: Learning Motivation-Grounded Reasoning for Scientific Ideation in Large Language Models
Chenyang Gu, Jiahao Cheng, Meicong Zhang +3
Scientific ideation aims to propose novel solutions within a given scientific context. Existing LLM-based agentic approaches emulate human research workflows, yet inadequately mode…
Entropy-Aware Speculative Decoding Toward Improved LLM Reasoning
Tiancheng Su, Meicong Zhang, Guoxiu He
Speculative decoding (SD) accelerates large language model (LLM) reasoning by using a small draft model to generate candidate tokens, which the target LLM either accepts directly o…
Eliminating Agentic Workflow for Introduction Generation with Parametric Stage Tokens
Meicong Zhang, Tiancheng su, Guoxiu He
In recent years, using predefined agentic workflows to guide large language models (LLMs) for literature classification and review has become a research focus. However, writing res…
Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models
Boheng Sheng, Jiacheng Yao, Meicong Zhang +1
Large language models (LLMs) often struggle to accurately read and comprehend extremely long texts. Current methods for improvement typically rely on splitting long contexts into f…