2026.07.27 | 技能自我对弈推动模型能力前沿;智能体上下文管理优化成本与推理。

2026.07.27 | 技能自我对弈推动模型能力前沿;智能体上下文管理优化成本与推理。

14分钟 ·
播放数50
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【目录】
本期的 14 篇论文如下:

[00:32] 🔄 Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills(技能自我对弈:通过协同进化技能推动大语言模型能力前沿)
[01:22] 🧠 Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems(智能体上下文管理:将代理记忆与成本视为生命周期与架构问题)
[02:18] 🤖 Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning(Molt:一个可扩展的、原生PyTorch的智能体强化学习训练框架)
[03:07] 🧪 DataPrep-Bench: Benchmarking LLMs as Training Data Preparators(数据准备基准:将大语言模型作为训练数据准备工具的基准测试)
[04:04] 📊 Scaling Native Multimodal Pre-Training From Scratch(从头开始扩展原生多模态预训练)
[04:54] 🎯 Three-Body Scattering for Generative Modeling(用于生成建模的三体散射)
[05:48] 🌐 LAMAR: An Open Language-Aware Multilingual Alignment Reranker(LAMAR:一种开放的语言感知多语言对齐重排序器)
[06:46] 🧠 Multi-Head Latent Control: A Unified Interface for LLM Agent Decision Making(多头潜在控制:大语言模型智能体决策的统一接口)
[07:43] 🎛 Spectral Prior for Reducing Exposure Bias in Diffusion Models(用于减少扩散模型曝光偏差的频谱先验)
[08:34] 🧠 IDEAgent: Agentic Quality-Diversity Search for Research Idea Generation(IDEAgent:面向研究创意生成的主体性质量-多样性搜索)
[09:27] 🎯 SceneActBench: Can Agents Act on the 3D Scenes They See?(场景动作基准:智能体能否对所见的三维场景采取行动?)
[10:37] 🔄 Closing the Loop: Training-Free Revisit Consistency for Autoregressive Generative Rendering(闭环:无需训练的循环一致性自回归生成渲染)
[11:31] 🔊 Multimodal Speaker Verification as a Threat to Speaker Anonymization(多模态说话人验证对说话人匿名化的威胁)
[12:26] 🧠 VisCo: Leveraging Large Language Models as Intrinsic Encoders for Visual Token Compression(VisCo:利用大语言模型作为视觉标记压缩的内在编码器)

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