2 citations · 4 across the 6 of their papers we have counts for
6 papers
DPWriter: Reinforcement Learning with Diverse Planning Branching for Creative Writing
Qian Cao, Yahui Liu, Wei Bi +6
Reinforcement learning (RL)-based enhancement of large language models (LLMs) often leads to reduced output diversity, undermining their utility in open-ended tasks like creative w…
Select, Read, and Write: A Multi-Agent Framework of Full-Text-based Related Work Generation
Xiaochuan Liu, Ruihua Song, Xiting Wang +1
Automatic related work generation (RWG) can save people's time and effort when writing a draft of related work section (RWS) for further revision. However, existing methods for RWG…
Evaluating Text Creativity across Diverse Domains: A Dataset and Large Language Model Evaluator
Qian Cao, Xiting Wang, Yuzhuo Yuan +3
Creativity evaluation remains a challenging frontier for large language models (LLMs). Current evaluations heavily rely on inefficient and costly human judgments, hindering progres…
See or Guess: Counterfactually Regularized Image Captioning
Qian Cao, Xu Chen, Ruihua Song +3
Image captioning, which generates natural language descriptions of the visual information in an image, is a crucial task in vision-language research. Previous models have typically…
Towards Effective and Efficient Continual Pre-training of Large Language Models
Jie Chen, Zhipeng Chen, Jiapeng Wang +16
Continual pre-training (CPT) has been an important approach for adapting language models to specific domains or tasks. To make the CPT approach more traceable, this paper presents…
YuLan: An Open-source Large Language Model
Yutao Zhu, Kun Zhou, Kelong Mao +35
Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many o…