13 citations · 16 across the 14 of their papers we have counts for
16 papers
LifeSearch: Benchmarking Deep Research Agents for Real-World Life and Productivity
Yibo Wang, Senjie Jin, Yansong Ning +6
Deep research (DR) agents address open-ended information needs through multi-step reasoning, long-horizon web search, and evidence synthesis. However, existing benchmarks primarily…
VibeWorlding: Can Multimodal Agents Construct 3D Open Worlds End-to-End?
Yansong Ning, Jingwen Ye, Zhongkai Wu +5
Constructing an interactive 3D open world from a user query is important. However, existing methods are primarily evaluated on idealized, simple queries, making it difficult to sys…
EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management
Zherui Yang, Fan Liu, Yansong Ning +1
Recent progress in Large Language Model (LLM) agents has enabled promising advances in automated data science. However, existing approaches remain fundamentally limited by their st…
TrafficClaw: A Generalizable LLM Agent in the Unified Physical Environment for Urban Traffic Control
Siqi Lai, Pan Zhang, Yuping Zhou +3
Large language model (LLM) agents have shown strong capabilities in long-horizon reasoning, tool use, and decision-making in digital environments, yet extending them to physically…
HRBench: Benchmarking and Understanding Thinking-Mode Switch Strategies in Hybrid-Reasoning LLMs
Yansong Ning, Mianpeng Liu, Jingwen Ye +2
Hybrid-reasoning large language models (LLMs) expose explicit controls over reasoning effort, allowing users or systems to trade off answer quality against inference cost. However,…
Agent-Omit: Adaptive Context Omission for Efficient LLM Agents
Yansong Ning, Jun Fang, Naiqiang Tan +1
Managing agent context (e.g., thought and observation) during multi-turn agent-environment interactions is an emerging strategy to improve agent efficiency. However, existing studi…
AgentBalance: Backbone-then-Topology Design for Cost-Effective Multi-Agent Systems under Budget Constraints
Shuowei Cai, Yansong Ning, Hao Liu
Large Language Model (LLM)-based multi-agent systems (MAS) are becoming indispensable building blocks for web-scale applications such as web search, social network analytics, and o…
DeepTravel: An End-to-End Agentic Reinforcement Learning Framework for Autonomous Travel Planning Agents
Yansong Ning, Rui Liu, Jun Wang +6
Travel planning (TP) agent has recently worked as an emerging building block to interact with external tools/resources for travel itinerary generation, ensuring an enjoyable user e…
FedSODA: Federated Fine-tuning of LLMs via Similarity Group Pruning and Orchestrated Distillation Alignment
Manning Zhu, Songtao Guo, Pengzhan Zhou +3
Federated fine-tuning (FFT) of large language models (LLMs) has recently emerged as a promising solution to enable domain-specific adaptation while preserving data privacy. Despite…
Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications
Jindong Han, Yansong Ning, Zirui Yuan +4
The long-standing vision of intelligent cities is to create efficient, livable, and sustainable urban environments using big data and artificial intelligence technologies. Recently…
Not All Thoughts are Generated Equal: Efficient LLM Reasoning via Multi-Turn Reinforcement Learning
Yansong Ning, Wei Li, Jun Fang +2
Compressing long chain-of-thought (CoT) from large language models (LLMs) is an emerging strategy to improve the reasoning efficiency of LLMs. Despite its promising benefits, exist…
USTBench: Benchmarking and Dissecting Spatiotemporal Reasoning of LLMs as Urban Agents
Siqi Lai, Yansong Ning, Zirui Yuan +2
Large language models (LLMs) have shown emerging potential in spatiotemporal reasoning, making them promising candidates for building urban agents that support diverse urban downst…
DiMA: An LLM-Powered Ride-Hailing Assistant at DiDi
Yansong Ning, Shuowei Cai, Wei Li +4
On-demand ride-hailing services like DiDi, Uber, and Lyft have transformed urban transportation, offering unmatched convenience and flexibility. In this paper, we introduce DiMA, a…
UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction
Yansong Ning, Hao Liu
Urban knowledge graph has recently worked as an emerging building block to distill critical knowledge from multi-sourced urban data for diverse urban application scenarios. Despite…
Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network
Fan Liu, Siqi Lai, Yansong Ning +1
Federated Graph Neural Network (FedGNN) has recently emerged as a rapidly growing research topic, as it integrates the strengths of graph neural networks and federated learning to…
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
Yansong Ning, Hao Liu, Hao Wang +2
Accurate Urban SpatioTemporal Prediction (USTP) is of great importance to the development and operation of the smart city. As an emerging building block, multi-sourced urban data a…