135 citations · 557 across the 54 of their papers we have counts for
12 papers · 1 filter
Agentic-Ideation: Sample Efficient Agentic Trajectories Synthesis for Scientific Ideation Agents
Keyu Zhao, Lingyan Kong, Fengli Xu +1
Ideation plays a pivotal role in scientific discovery. Recent LLM, especially AI Scientist systems, show promising potential for automated ideation. However, existing approaches pr…
MirrorMind: Empowering OmniScientist with the Expert Perspectives and Collective Knowledge of Human Scientists
Qingbin Zeng, Bingbing Fan, Zhiyu Chen +7
The emergence of AI Scientists has demonstrated remarkable potential in automating scientific research. However, current approaches largely conceptualize scientific discovery as a…
Deep Ideation: Designing LLM Agents to Generate Novel Research Ideas on Scientific Concept Network
Keyu Zhao, Weiquan Lin, Qirui Zheng +2
Novel research ideas play a critical role in advancing scientific inquiries. Recent advancements in Large Language Models (LLMs) have demonstrated their potential to generate novel…
Rationality Check! Benchmarking the Rationality of Large Language Models
Zhilun Zhou, Jing Yi Wang, Nicholas Sukiennik +4
Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artifi…
CrimeMind: Simulating Urban Crime with Multi-Modal LLM Agents
Qingbin Zeng, Ruotong Zhao, Jinzhu Mao +3
Modeling urban crime is an important yet challenging task that requires understanding the subtle visual, social, and cultural cues embedded in urban environments. Previous work has…
A Survey of Large Language Model-Powered Spatial Intelligence Across Scales: Advances in Embodied Agents, Smart Cities, and Earth Science
Jie Feng, Jinwei Zeng, Qingyue Long +15
Over the past year, the development of large language models (LLMs) has brought spatial intelligence into focus, with much attention on vision-based embodied intelligence. However,…
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…
A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy
Huandong Wang, Wenjie Fu, Yingzhou Tang +7
While large language models (LLMs) present significant potential for supporting numerous real-world applications and delivering positive social impacts, they still face significant…
Perceive, Reflect, and Plan: Designing LLM Agent for Goal-Directed City Navigation without Instructions
Qingbin Zeng, Qinglong Yang, Shunan Dong +4
This paper considers a scenario in city navigation: an AI agent is provided with language descriptions of the goal location with respect to some well-known landmarks; By only obser…
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…
Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives
Chen Gao, Xiaochong Lan, Nian Li +5
Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. In…
Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment
Fengli Xu, Jun Zhang, Chen Gao +2
Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, face significant challenges in the…