AI Alignment: A Comprehensive Survey, arXiv 2024.02 [Paper] Large Language Model Alignment: A Survey, arXiv 2023.09 [Paper] From Instructions to Intrinsic Human Values -- A Survey of Alignment Goals for Big Mod
Digital Forgetting in Large Language Models: A Survey of Unlearning Methods arXiv 2024 Rethinking Machine Unlearning for Large Language Models arXiv 2024 Threats, Attacks, and Defenses in Machine Unlearning: A Survey arXiv 2024 Machine Unlearning: Solutions and Challenges TETCI 2024 A Survey on Feder...
large language model alignment a survey 1. 引言 1.1 概述 大型语言模型是当前自然语言处理领域的热点研究方向,这些模型能够通过学习海量的语料库数据来生成连贯和有逻辑的文本。近年来,随着深度学习技术的快速发展,大型语言模型在机器翻译、文本摘要生成、对话系统等各个领域取得了卓越的进展。 然而,尽管大型语言模型...
Alignment(对齐),意为使模型的表现和人们的意图保持一致。Alignment在大语言模型(LLMs)的应用中非常重要,因为在使用LLMs时,人们需要确保LLMs是可信的,不可信的LLMs如果被广泛应用于社会,会带来巨大的损失。例如:在进行医疗诊断时,假如LLM误诊,或是输出了错误的治疗方法,就会耽误病人的治疗,甚至是威胁到病人的生命安...
A McKinsey survey revealed that Chinese firms in Africa recruited 89 percent of their employees locally, contributing to local employment in an effective way. The World Bank has estimated that by 2030, BRI-related investments could lift 7.6 million out of extreme poverty and 32 million out of ...
AI Alignmentalignmentsurvey.com/ (可获取中文版论文和其它相关资料) 对齐失败(Misalignment) 定义:人工智能系统出现不符合人类意图的不良或有害行为 风险规模相当庞大原因 (1) 构建超智能人工智能系统 (2) 这些人工智能系统追求大规模目标 (3) 这些目标与人类意图和价值观不对齐 (4) 以及这种对齐失败导致人...
Big data Cloud services SDGs Monitoring 1. Introduction The United Nations (UN) released “Transforming our World: The 2030 agenda for Sustainable Development”, which included 17Sustainable Development Goals(SDGs) and 169 specific targets (United Nations, 2015,United Nations, 2019), presenting an op...
Prompted by the developments in the Python scientific environment and in collaborative development tools, we developed AlphaPept, a Python-based open-source framework for the efficient processing of large amounts of high-resolution MS data. Our main design goals were accessibility, analysis speed, and...
In alignment with the aforementioned goals we formulate the research questions of this survey as follows: The remainder of this paper is structured as follows. Section 2 first explains the terms deep learning, log data, and anomaly detection, and then provides an overview of common challenges. ...
This work focuses on the aspect of facial manipulation in Deepfake, encompassing Face Swapping, Face Reenactment, Talking Face Generation, Face Attribute Editing and Forgery Detection. We believe this will be the most comprehensive survey to date on facial manipulation and detection technologies. Please...