3 papers
cs.AI2026
Clearing the Fog: Towards Installing and Refining Proactive Exploration Capabilities in LLM Agents
Zhizhao Guan, Chen Huang, Ziming Liu +5
We study proactive exploration in LLM agents, i.e., the ability to explore an environment to acquire information that improves future decision-making. In this regard, we first iden…
cs.CL2025
BAR: A Backward Reasoning based Agent for Complex Minecraft Tasks
Weihong Du, Wenrui Liao, Binyu Yan +3
Large language model (LLM) based agents have shown great potential in following human instructions and automatically completing various tasks. To complete a task, the agent needs t…
cs.CL2024
Dishonesty in Helpful and Harmless Alignment
Youcheng Huang, Jingkun Tang, Duanyu Feng +4
People tell lies when seeking rewards. Large language models (LLMs) are aligned to human values with reinforcement learning where they get rewards if they satisfy human preference.…