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Daily AI Papers Briefing (2026-09-29)
Published 2 weeks, 3 days ago
Description
【本日の論文】
1. FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders
https://huggingface.co/papers/2609.31620
2. Disaggregated Quantization: Specializing LLM Prefill and Decode
https://huggingface.co/papers/2609.26333
3. RayOrch: Programming and Executing Lineage-Controlled Multi-Grain Dataflows for Foundation-Model Data Preparation
https://huggingface.co/papers/2609.18703
4. Block Sparse Attention with Log-Linear Complexity
https://huggingface.co/papers/2609.31093
5. InternW0-Δ: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data
https://huggingface.co/papers/2609.31394
1. FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders
https://huggingface.co/papers/2609.31620
2. Disaggregated Quantization: Specializing LLM Prefill and Decode
https://huggingface.co/papers/2609.26333
3. RayOrch: Programming and Executing Lineage-Controlled Multi-Grain Dataflows for Foundation-Model Data Preparation
https://huggingface.co/papers/2609.18703
4. Block Sparse Attention with Log-Linear Complexity
https://huggingface.co/papers/2609.31093
5. InternW0-Δ: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data
https://huggingface.co/papers/2609.31394