arXiv AI By Yiyang Li, Weixiang Sun, Tianyi Ma, Kaiwen Shi, Zheyuan Zhang, Yanfang Ye

HoosierHelp: Benchmarking LLM Agents for Social Service Navigation

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arXiv:2608. 09946v1 Announce Type: cross Abstract: Social service navigation requires connecting help-seeking individuals to resources that satisfy their needs and specific constraints.

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arXiv AI
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MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios

arXiv:2602. 22638v2 Announce Type: replace Abstract: Route-planning agents powered by large language models (LLMs) have emerged as a promising paradigm for supporting everyday human mobility through natural language interaction and tool-mediated decision making.

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MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation

arXiv:2606. 02470v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has emerged as a transformative standard for connecting large language models (LLMs) with external data sources and tools, and has been rapidly adopted across personal applications and development platforms.

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T1-Bench: Benchmarking Multi-Scenario Agents in Real-World Domains

arXiv:2606. 11070v1 Announce Type: cross Abstract: Recent advances in reasoning and tool-calling capabilities of large language models (LLMs) have enabled increasingly capable agentic systems.

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