Tag: Human-AI Interaction
All the articles with the tag "Human-AI Interaction".
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HSI: Head-Specific Intervention Can Induce Misaligned AI Coordination in Large Language Models
本文提出Head-Specific Intervention (HSI)方法,通过针对特定注意力头的激活干预,成功诱导Llama 2模型在AI协调行为上绕过安全对齐,效果优于监督微调和其它干预策略。
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Reward Guidance for Reinforcement Learning Tasks Based on Large Language Models: The LMGT Framework
本文提出了LMGT框架,通过利用大型语言模型的先验知识对强化学习的奖励进行动态调整,有效平衡了探索与利用,显著提高了样本效率并降低了训练成本,并在多种环境、算法以及机器人和推荐系统等复杂场景中验证了其有效性。
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Agentic Reasoning and Tool Integration for LLMs via Reinforcement Learning
ARTIST, a novel framework unifying agentic reasoning, reinforcement learning, and tool integration, enables LLMs to autonomously orchestrate external tools within multi-turn reasoning, achieving up to 22% accuracy gains on complex math tasks and significant improvements in multi-turn function calling over baselines.
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Beyond the Last Answer: Your Reasoning Trace Uncovers More than You Think
本文提出了一种通过分割大型语言模型推理轨迹为子思维并从中间状态生成多条推理路径、最终以众数聚合答案的方法,显著提高了数学推理任务的准确性(最高提升13%),并揭示了答案一致性与正确性的相关性。
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Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning
本文提出MINDcraft框架和MineCollab基准,评估LLM在多代理具身协作中的性能,揭示了当前模型在通信和协调方面的局限性,并呼吁开发更先进的协作方法。