2025.03.31 | 减少token使用,提升领域效率。

2025.03.31 | 减少token使用,提升领域效率。

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本期的 15 篇论文如下:

00:22 💡 AdaptiVocab: Enhancing LLM Efficiency in Focused Domains through Lightweight Vocabulary Adaptation(AdaptiVocab:通过轻量级词汇自适应增强LLM在特定领域的效率)

01:01 🤖 Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback(探索人类反馈强化学习中的数据缩放趋势与影响)

01:41 🤔 Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation(推荐之前先思考:释放序列推荐中的潜在推理能力)

02:19 💡 A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond(大型推理模型高效推理综述:语言、多模态及其他)

02:58 🖼 ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation(ORIGEN:文本到图像生成中零样本三维方向定位)

03:44 🧠 OThink-MR1: Stimulating multimodal generalized reasoning capabilities via dynamic reinforcement learning(OThink-MR1:通过动态强化学习激发多模态通用推理能力)

04:25 🔄 ReFeed: Multi-dimensional Summarization Refinement with Reflective Reasoning on Feedback(ReFeed:基于反馈反射推理的多维度摘要改进)

04:59 🎬 Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal Consistency(Free4D:无需微调的具有时空一致性的4D场景生成)

05:37 🧪 PHYSICS: Benchmarking Foundation Models on University-Level Physics Problem Solving(物理学:在大学水平物理问题求解中对基础模型进行基准测试)

06:24 🗣 Perceptually Accurate 3D Talking Head Generation: New Definitions, Speech-Mesh Representation, and Evaluation Metrics(感知准确的3D说话头生成:新定义、语音-网格表示和评估指标)

07:03 🎬 Segment Any Motion in Videos(视频中的任意运动对象分割)

07:42 🖼 Hi3DGen: High-fidelity 3D Geometry Generation from Images via Normal Bridging(Hi3DGen:基于法线桥接的图像高保真3D几何体生成)

08:28 🖼 Your ViT is Secretly an Image Segmentation Model(你的ViT竟然是图像分割模型)

09:04 🤔 4D-Bench: Benchmarking Multi-modal Large Language Models for 4D Object Understanding(4D-Bench:用于4D对象理解的多模态大型语言模型基准测试)

09:48 💡 A Refined Analysis of Massive Activations in LLMs(LLM中大规模激活的精细化分析)

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