Pai 的 AI 雷达

安全治理

今天:OpenAI 长文阐述对齐与监测困境(模型发布),OpenAI admits its(Agent 原型)。并行还有 NeoRed、Seeing Before Synthesizing:。

日期
2026/09/07
今日条目
135
当前类目
5
#01

OpenAI 长文阐述对齐与监测困境,称 CoT 监控能力正在减弱

OpenAI 发布长文《An Alien Mind》,回溯 2023 年 RLSlow 项目中确认推理模型可扩展训练的起点,并系统阐述目标对齐与价值对齐的区分。文章指出链式思维监控的效果正随着模型能力提升而逐步减弱,GPT-6 Astra 在对齐上显著优于 GPT-5.6 Sol;作者预期进展可能持续走向机器递归自我改进(RSI),呼吁自愿放缓扩展、建立第三方安全门槛并加强国际协调。 🔗 阅读原文 via AIHOT · https://aihot.virxact.com/items/cmtq23v6k01aorotwh8xip8r1

推荐理由OpenAI 发布长文《An Alien Mind》,回溯 2023 年 RLSlow 项目中确认推理模型可扩展训练的起点,并系统阐述目标对齐与价值对齐的区分。
模型与评测安全治理AIHOT feed.xml
#02

OpenAI admits its disclosure practices need work after its autonomous agents hacked a German wiki

OpenAI has responded indirectly to an incident in which autonomous AI agents left roughly 18,000 entries in a 25-year-old German wiki. The company says misalignment caused "new types of real-world impact" for the first time and plans to release a disclosure framework. The article

推荐理由OpenAI admits its disclosure practices:OpenAI has responded indirectly to an incident in which autonomous AI agents left。
Agent与工具安全治理The Decoder
#03

NeoRed: A Knowledge-Logic-Alignment Multimodal Large Language Model for Neonatal Respiratory Disease Diagnosis

Neonatal respiratory diseases are a major cause of neonatal morbidity and mortality, posing substantial challenges in clinical practice. Despite recent advances, existing Multimodal Large Language Models (MLLMs) face two key limitations in neonatal diagnosis: (1) domain gap arisi

推荐理由「NeoRed: A Knowledge-Logic-Alignm…」偏多模态,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测安全治理papers.cool cs.AI Atom
#04

Seeing Before Synthesizing: VLM-Guided Transition Event Discovery for Weakly-Supervised Dense Video Captioning

Weakly-Supervised Dense Video Captioning aims to localize and describe multiple events in untrimmed videos given only an ordered set of event-level captions per video. Recent work synthesizes auxiliary transition captions via LLM to provide additional vision-language alignment, b

推荐理由「Seeing Before Synthesizing: VLM-…」偏视觉语言,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测安全治理arxiv cs.AI recent
#05

Seeing Before Synthesizing: VLM-Guided Transition Event Discovery for Weakly-Supervised Dense Video Captioning

Weakly-Supervised Dense Video Captioning aims to localize and describe multiple events in untrimmed videos given only an ordered set of event-level captions per video. Recent work synthesizes auxiliary transition captions via LLM to provide additional vision-language alignment, b

推荐理由「Seeing Before Synthesizing: VLM-…」偏视觉语言,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测安全治理papers.cool cs.AI Atom