2025.07.17 | RAG提升LLM推理;PhysX生成物理3D资产

HuggingFace 每日AI论文速递

本期的 13 篇论文如下:

[00:26] 🧠 Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs(具身智能RAG与深度推理:LLM中RAG推理系统综述)

[01:17] 🧱 PhysX: Physical-Grounded 3D Asset Generation(PhysX:基于物理的3D资产生成)

[02:04] 🚗 MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding(MMHU:一个用于人类行为理解的大规模多模态基准)

[03:05] 🚀 SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories?(SWE-Perf:语言模型能否优化真实世界代码仓库的性能?)

[04:00] 💃 MOSPA: Human Motion Generation Driven by Spatial Audio(MOSPA:空间音频驱动的人体动作生成)

[04:57] 🏗 DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil Engineering(DrafterBench:用于土木工程中任务自动化的LLM基准测试)

[05:58] 🤖 Seq vs Seq: An Open Suite of Paired Encoders and Decoders(序列模型对比:一个开放的配对编码器与解码器套件)

[06:38] 🎬 AnyI2V: Animating Any Conditional Image with Motion Control(AnyI2V:通过运动控制动画化任何条件图像)

[07:34] 🎯 SpatialTrackerV2: 3D Point Tracking Made Easy(SpatialTrackerV2:化繁为简的3D点追踪)

[08:27] 🦎 Lizard: An Efficient Linearization Framework for Large Language Models(Lizard:一种用于大型语言模型的高效线性化框架)

[09:14] 🧰 Replacing thinking with tool usage enables reasoning in small language models(以工具使用代替思考:小语言模型中的推理能力提升)

[10:05] 🧙 AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles(CheckThat! 2025 挑战赛中的 AI 巫师:利用情感增强的 Transformer 嵌入改进新闻文章中的主观性检测)

[10:51] 🧠 RLEP: Reinforcement Learning with Experience Replay for LLM Reasoning(RLEP:基于经验回放的强化学习用于LLM推理)

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