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#transformer - page 3 | AI Briefing

MemoryLLM: A Plug-and-Play Interpretable Feed-Forward Memory for Transformers

·2026.07.02 09:00

Learning Unmasking Policies for Diffusion Language Models

·2026.07.02 09:00

Google DeepMind Releases Tracr

·2026.06.30 12:00

DiScoFormer: A Transformer That Estimates Density and Score Simultaneously

·2026.06.30 03:00

The Economics of Tokens (10-minute read)

·2026.06.29 10:00

Analysis of Token Prediction Characteristics in Hybrid Models

·2026.06.26 01:00

Analysis of Structural Flaws in the Attention Mechanism

·2026.06.25 23:00

Nvidia Acquihires Essential AI Team

·2·2026.06.24 04:00

Changes in an LLM's internal state determine its answering tendencies

·2026.06.24 01:00

Alibaba's AI Video Model Leaps to Global No. 2, Overtaking OpenAI Sora and ByteDance Seedance

·2026.06.23 09:00

LLMs Have Become Complex Now

·2026.06.22 09:00

A Benchmarking Methodology for Agent-Optimized Software

·2026.06.18 09:00

Microsoft Publishes NextLat Research

·2026.06.17 17:00

Missing Executive Control in Transformer Attention

·2026.06.11 08:00

[2026/06/01 ~ 07] AI/ML Papers Worth Reading This Week

·2026.06.09 08:00

Transformers Are Inherently Succinct

·2026.06.06 03:00

Arithmetic Without Numbers – How LLMs Perform Math

·2026.06.05 19:00

Does a Transformer really need three projections? A systematic study of QKV variants

·2026.06.05 08:00

OCTOPUS: Optimizing Transformer KV Cache via Optimal Squared-Error Quantization and Octahedral Parameterization

·2026.06.04 01:00

Why Financial Institutions Are Turning to 'Transaction Foundation Models' to Build Their Own Intelligence

·2026.06.02 15:00

CS336: Language Modeling from Scratch

·2026.06.02 12:00

CS336: Language Modeling from Scratch

·1·2026.06.01 23:00

Risk of Training Errors in AI-Generated CUDA Kernels

·2026.05.28 01:00

Native Multimodal Modeling (GitHub Repository)

·2026.05.27 09:00

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