arXiv AI
Jul 31
UrbanDS: A Graph-Guided LLM Multi-Agent System for Data-Intensive Urban Tasks
arXiv:2607. 26724v1 Announce Type: new Abstract: Large language model (LLM) agents have been widely applied in automating data science tasks.
DUDA-Bench: Benchmarking LLM Agents on Multimodal Data-Driven Urban Diagnosis
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arXiv AI
Aug 5
UrbanAgent: A Tool-Augmented Agent for Cross-System Urban Tasks
arXiv:2608. 03018v1 Announce Type: new Abstract: Modern cities rely on an increasing number of digital services to operate, but residents' daily needs are still difficult to meet.
arXiv AI
Jun 15
SANA: What Matters for QA Agents over Massive Data Lakes?
arXiv:2606. 13904v1 Announce Type: cross Abstract: Exploratory question answering (EQA) over data lakes requires an LLM agent to discover relevant sources, analyze retrieved data, and adapt its actions based on intermediate results.
arXiv AI
Jul 7
HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis
arXiv:2603. 01121v2 Announce Type: replace Abstract: While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable challenge.
arXiv AI
Jun 8
DuMate-DeepResearch: An Auditable Multi-Agent System with Recursive Search and Rubric-Grounded Reasoning
arXiv:2606. 07299v1 Announce Type: new Abstract: Deep Research (DR) has emerged as a new agentic paradigm to tackle complex, open-ended research tasks, demanding systems that can iteratively frame problems, acquire evidence, verify sources, and synthesize long-form reports.
arXiv AI
Jul 16
Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling
arXiv:2607. 13558v1 Announce Type: new Abstract: Urban region profiling constitutes a core problem in urban computing, supporting applications such as population estimation, economic assessment, and environmental monitoring.
arXiv AI
Aug 19
AdaLens: Interactive Storyline for Monitoring and Steering Long-Running Agentic Data Analysis
AdaLens is an interactive system designed to monitor and steer long-running, autonomous data analysis workflows powered by large language models. It provides a storyline-based interface that unifies analytical plans, execution progress, intermediate findings, and data-column involvement, enabling analysts to observe evolving reasoning and evidence. The system also offers steering interactions that allow users to redirect low-value directions or deepen promising ones during execution.
arXiv AI
Jul 17
CXRAgent: Director-Orchestrated Multi-Stage Reasoning for Chest X-Ray Interpretation
arXiv:2510. 21324v2 Announce Type: replace Abstract: Chest X-ray (CXR) plays a pivotal role in clinical diagnosis, and a variety of task-specific and foundation models have been developed for automatic CXR interpretation.
arXiv AI
Aug 11
Lingjing: A Simulation Testbed for Multi-Agent Embodied Tasks in Open-Ended Cities
arXiv:2608. 08045v1 Announce Type: new Abstract: Urban embodied intelligence requires coordination among heterogeneous agents (e.
Hugging Face Trending Papers
Aug 3
GISAgentBench: A Practitioner-Sourced Benchmark for Evaluating LLM Agents on GIS Tasks
Geographic Information System (GIS) professionals rely on multi-step spatial analysis workflows to support decision-making in urban planning, disaster response, and environmental monitoring. The process is tedious, time-consuming, and error-prone.
arXiv AI
Jul 28
SIREN: Towards End-to-End Extreme-Weather Early Warning with Experience-Grounded LLM Agents
arXiv:2607. 24588v1 Announce Type: new Abstract: Early warning of extreme weather is essential for mitigating the societal, economic, and environmental risks posed by hazardous weather events.
arXiv AI
Oct 2
LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios
The article surveys LLM-based agentic reasoning frameworks, presenting a unified formal language that categorizes them into single-agent, tool-based, and multi-agent methods. It reviews application scenarios in scientific discovery, healthcare, software engineering, society, economics, and general-purpose tasks, and compares the distinct features and evaluation strategies of each category. The survey highlights the rapid development of complex agentic systems in real-world contexts.