For artificial intelligence to be beneficial to humans the behaviour of AI agents needs to be aligned with what humans want. In this paper we discuss some behavioural issues for language agents, arising from accidental misspecification by the system designer. We highlight some ways that ...
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLM https://arxiv.org/abs/2406.18629 https://github.com/dvlab-research/Step-DPO DMPO 在开发 language agents 时,将大型语言模型(LLM)调整为 agents 任务至关重要。直接偏好优化(DPO)是一种很有前途的适应技术,可以减轻复合错误,提...
在开发 language agents 时,将大型语言模型(LLM)调整为 agents 任务至关重要。直接偏好优化(DPO)是一种很有前途的适应技术,可以减轻复合错误,提供一种直接优化强化学习(RL)目标的方法。 然而,由于无法取消分区函数,将 DPO 应用于多轮任务会带来挑战。克服这一障碍需要使分区函数独立于当前状态,并解决首选和不首选轨...
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLM https://arxiv.org/abs/2406.18629 https://github.com/dvlab-research/Step-DPO DMPO 在开发 language agents 时,将大型语言模型(LLM)调整为 agents 任务至关重要。直接偏好优化(DPO)是一种很有前途的适应技术,可以减轻复合错误,提...
【RLChina论文研讨会】第14期 王戎骁 When Should Agents Explore 26:21 【RLChina论文研讨会】第13期 郑学敬 Lifelong RL with Temporal Logic Formulas and Reward Machi 21:19 【RLChina论文研讨会】第13期 李斯源 Active Hierarchical Exploration with Stable Subgoal Rep-L 16:12 【RLChina论文研讨会】第...
Language agentsCatastrophic riskX-riskYum (2024) argues that the widespread adoption of language agent architectures would likely increase the risk posed by AI by simplifying the process of aligning artificial systems with human values and thereby making it easier for malicious actors to use them to...
To address these challenges, we propose ALI-Agent, an evaluation framework that leverages the autonomous abilities of LLM-powered agents to conduct in-depth and adaptive alignment assessments. ALI-Agent operates through two principal stages: Emulation and Refinement. During the Emulation stage, ALI-...
The model embraces the emergent behaviors shaped by the interactions of business and IS agents, and guides the coevolution of alignment driven by the external changes. The development of this model forms a necessary step towards suggesting guidance how to analyze and implement coevolution in ...
This repository contains the code and data accompanying the paper "Chat Bankman-Fried: An Exploration of LLM Alignment in Finance"[1].The paper presents a simulation environment with seven pressure variables designed to test the alignment of large language models (LLMs) in high-stakes financial ...
Meet CoAgents: A Frontend Framework Reshaping Human-in-the-Loop AI Agents for Building Next-Generation Interactive Applications with Agent UI and LangGraph Integration (Promoted) A team of researchers from University of ...