18 citations · 22 across the 10 of their papers we have counts for
11 papers
AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery
Yu Li, Chenyang Shao, Xinyang Liu +13
Artificial intelligence research increasingly depends on prolonged cycles of reproduction, debugging, and iterative refinement to achieve State-Of-The-Art (SOTA) performance, creat…
LiveFigure: Generating Editable Scientific Illustration with VLM Agents
Chenyang Shao, Jiahe Liu, Fengli Xu +1
Scientific illustrations are essential for depicting conceptual designs, methodologies, and experimental workflows in research, playing a pivotal role in communicating complex acad…
SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval
Chenyang Shao, Fengli Xu, Yong Li
AI agents have seen widespread adoption in information retrieval for scientific research, giving rise to tools such as Deep Research. However, existing retrieval agents mainly rely…
Diffuse Thinking: Exploring Diffusion Language Models as Efficient Thought Proposers for Reasoning
Chenyang Shao, Sijian Ren, Fengli Xu +1
In recent years, large language models (LLMs) have witnessed remarkable advancements, with the test-time scaling law consistently enhancing the reasoning capabilities. Through syst…
Simulating Generative Social Agents via Theory-Informed Workflow Design
Yuwei Yan, Jinghua Piao, Xiaochong Lan +3
Recent advances in large language models have demonstrated strong reasoning and role-playing capabilities, opening new opportunities for agent-based social simulations. However, mo…
AgentStealth: Reinforcing Large Language Model for Anonymizing User-generated Text
Chenyang Shao, Tianxing Li, Chenhao Pu +2
In today's digital world, casual user-generated content often contains subtle cues that may inadvertently expose sensitive personal attributes. Such risks underscore the growing im…
Route-and-Reason: Scaling Large Language Model Reasoning with Reinforced Model Router
Chenyang Shao, Xinyang Liu, Yutang Lin +2
Chain-of-thought has been proven essential for enhancing the complex reasoning abilities of Large Language Models (LLMs), but it also leads to high computational costs. Recent adva…
Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents
Chenyang Shao, Xinyuan Hu, Yutang Lin +1
The rapid expansion of web content has made on-device AI assistants indispensable for helping users manage the increasing complexity of online tasks. The emergent reasoning ability…
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Fengli Xu, Qianyue Hao, Zefang Zong +17
Language has long been conceived as an essential tool for human reasoning. The breakthrough of Large Language Models (LLMs) has sparked significant research interest in leveraging…
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation
Yuan Yuan, Chenyang Shao, Jingtao Ding +2
Spatio-temporal modeling is foundational for smart city applications, yet it is often hindered by data scarcity in many cities and regions. To bridge this gap, we propose a novel g…
Chain-of-Planned-Behaviour Workflow Elicits Few-Shot Mobility Generation in LLMs
Chenyang Shao, Fengli Xu, Bingbing Fan +4
The powerful reasoning capabilities of large language models (LLMs) have brought revolutionary changes to many fields, but their performance in human behaviour generation has not y…