13 citations · 16 across the 14 of their papers we have counts for
6 papers · 1 filter
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…