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本期的 5 篇论文如下:
[00:44] TOP1(🔥208) | 🤖 Feature-Level Insights into Artificial Text Detection with Sparse Autoencoders(基于稀疏自编码器的人工文本检测特征分析)
[03:15] TOP2(🔥122) | 🇷 RuCCoD: Towards Automated ICD Coding in Russian(RuCCoD:面向俄语自动化的ICD编码研究)
[05:35] TOP3(🔥104) | 🌐 Unified Reward Model for Multimodal Understanding and Generation(多模态理解和生成的统一奖励模型)
[07:58] TOP4(🔥89) | 🌏 Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia(众包、爬取还是生成?创建东南亚视觉语言数据集SEA-VL)
[10:21] TOP5(🔥73) | 🧠 LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL(LMM-R1:通过两阶段基于规则的强化学习赋予3B参数大模态模型强大的推理能力)
【关注我们】
您还可以在以下平台找到我们,获得播客内容以外更多信息
小红书: AI速递
本期的 5 篇论文如下:
[00:44] TOP1(🔥208) | 🤖 Feature-Level Insights into Artificial Text Detection with Sparse Autoencoders(基于稀疏自编码器的人工文本检测特征分析)
[03:15] TOP2(🔥122) | 🇷 RuCCoD: Towards Automated ICD Coding in Russian(RuCCoD:面向俄语自动化的ICD编码研究)
[05:35] TOP3(🔥104) | 🌐 Unified Reward Model for Multimodal Understanding and Generation(多模态理解和生成的统一奖励模型)
[07:58] TOP4(🔥89) | 🌏 Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia(众包、爬取还是生成?创建东南亚视觉语言数据集SEA-VL)
[10:21] TOP5(🔥73) | 🧠 LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL(LMM-R1:通过两阶段基于规则的强化学习赋予3B参数大模态模型强大的推理能力)
【关注我们】
您还可以在以下平台找到我们,获得播客内容以外更多信息
小红书: AI速递