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20212026
most citedIgniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents

11 citations · 18 across the 19 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Plan-MCTS: Plan Exploration for Action Exploitation in Web Navigation

Weiming Zhang, Jihong Wang, Jiamu Zhou +9

Large Language Models (LLMs) have empowered autonomous agents to handle complex web navigation tasks. While recent studies integrate tree search to enhance long-horizon reasoning,…

cs.AI2025

Chain-of-Trigger: An Agentic Backdoor that Paradoxically Enhances Agentic Robustness

Jiyang Qiu, Xinbei Ma, Yunqing Xu +2

The rapid deployment of large language model (LLM)-based agents in real-world applications has raised serious concerns about their trustworthiness. In this work, we reveal the secu…

cs.AI2025

ParaCook: On Time-Efficient Planning for Multi-Agent Systems

Shiqi Zhang, Xinbei Ma, Yunqing Xu +7

Large Language Models (LLMs) exhibit strong reasoning abilities for planning long-horizon, real-world tasks, yet existing agent benchmarks focus on task completion while neglecting…

cs.AI2025

PGPO: Enhancing Agent Reasoning via Pseudocode-style Planning Guided Preference Optimization

Zouying Cao, Runze Wang, Yifei Yang +4

Large Language Model (LLM) agents have demonstrated impressive capabilities in handling complex interactive problems. Existing LLM agents mainly generate natural language plans to…

cs.AI2025

Wide-Horizon Thinking and Simulation-Based Evaluation for Real-World LLM Planning with Multifaceted Constraints

Dongjie Yang, Chengqiang Lu, Qimeng Wang +4

Unlike reasoning, which often entails a deep sequence of deductive steps, complex real-world planning is characterized by the need to synthesize a broad spectrum of parallel and po…

cs.AI2025

Plan-over-Graph: Towards Parallelable LLM Agent Schedule

Shiqi Zhang, Xinbei Ma, Zouying Cao +2

Large Language Models (LLMs) have demonstrated exceptional abilities in reasoning for task planning. However, challenges remain under-explored for parallel schedules. This paper in…