2025.09.26 | SciReasoner八项全能；MMR1模糊区炼出开源多模态

本期的 15 篇论文如下：

[00:20] 🔬 SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines（SciReasoner：跨学科夯实科学推理基石）

[01:00] 🧠 MMR1: Enhancing Multimodal Reasoning with Variance-Aware Sampling and Open Resources（MMR1：基于方差感知采样与开放资源的多模态推理增强）

[01:41] 📈 VCRL: Variance-based Curriculum Reinforcement Learning for Large Language Models（VCRL：面向大语言模型的方差驱动课程强化学习）

[02:26] 🌳 Tree Search for LLM Agent Reinforcement Learning（基于树搜索的大语言模型智能体强化学习）

[03:06] 🖼 Seedream 4.0: Toward Next-generation Multimodal Image Generation（Seedream 4.0：面向下一代多模态图像生成）

[03:40] 🎯 Hunyuan3D-Omni: A Unified Framework for Controllable Generation of 3D Assets（Hunyuan3D-Omni：统一可控3D资产生成框架）

[04:29] 🤖 AutoIntent: AutoML for Text Classification（AutoIntent：面向文本分类任务的自动化机器学习框架）

[05:10] ⚖ TrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them（TrustJudge：LLM-as-a-Judge的评分不一致性及缓解之道）

[05:43] 🎢 CE-GPPO: Controlling Entropy via Gradient-Preserving Clipping Policy Optimization in Reinforcement Learning（CE-GPPO：通过梯度保留裁剪策略优化控制强化学习中的熵）

[06:30] 🖼 Does FLUX Already Know How to Perform Physically Plausible Image Composition?（FLUX已掌握物理可信图像合成？）

[07:31] ✂ CHARM: Control-point-based 3D Anime Hairstyle Auto-Regressive Modeling（CHARM：基于控制点的3D动漫发型自回归建模）

[08:26] 🧠 Recon-Act: A Self-Evolving Multi-Agent Browser-Use System via Web Reconnaissance, Tool Generation, and Task Execution（Recon-Act：基于网络侦察、工具生成与任务执行的自我演化多智能体浏览器操作系统）

[09:12] 🎮 V-GameGym: Visual Game Generation for Code Large Language Models（V-GameGym：面向代码大模型的视觉游戏生成基准）

[09:49] 🗣 Interactive Recommendation Agent with Active User Commands（支持主动用户指令的交互式推荐智能体）

[10:22] 🔍 BESPOKE: Benchmark for Search-Augmented Large Language Model Personalization via Diagnostic Feedback（BESPOKE：基于诊断反馈的搜索增强大模型个性化评测基准）

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