【AI最新動向 2026年3月23日】論文5件・GitHub5件

2026年3月23日2026年3月27日

📝 この記事のポイント

🚀 AI技術の最新動向 – 2026年3月23日世界中から収集したAI・機械学習の最新情報をお届けします 📑 目次 💻 注目のGitHubプロジェクト rohitg00/ai-engineering-from-scratch dubermandeer/Worm-GPT-LLM-2026 matt-k-wong/mlx-flash pharaongayd/Album-Formula-Ai-2026-Update hanxiao/flash-kmeans-mlx 📌 関連記事もチェック 📚 最新研究論文 1. From Masks to Pixels and Meaning: A New Taxonomy, Benchmark, and Metrics for VLM Image Tampering 著者: Xinyi Shang, Yi Tang, Jiacheng Cui Existing tampering detection benchmarks largely rely on object masks, which severely misalign with the true edit signal: many pixels inside a mask are untouched or only trivially modified, while subtle yet consequential edits outside the mask are treated as natural. We reformulate VLM image tamperin… 論文を読む → 2. LumosX: Relate Any Identities with Their Attributes for Personalized Video Generation 著者: Jiazheng Xing, Fei Du, Hangjie Yuan Recent advances in diffusion models have significantly improved text-to-video generation, enabling personalized content creation with fine-grained control over both foreground and background elements. However, precise face-attribute alignment across subjects remains challenging, as existing methods … 論文を読む → 3. MeanFlow Meets Control: Scaling Sampled-Data Control for Swarms 著者: Anqi Dong, Yongxin Chen, Karl H. Johansson Steering large-scale swarms in only a few control updates is challenging because real systems operate in sampled-data form: control inputs are updated intermittently and applied over finite intervals. In this regime, the natural object is not an instantaneous velocity field, but a finite-window cont… 論文を読む → 💻 注目のGitHubプロジェクト 1. rohitg00/ai-engineering-from-scratch Learn it. Build it. Ship it for others. ⭐ 355 stars | 🔀 58 forks リポジトリを見る → 2. dubermandeer/Worm-GPT-LLM-2026 High-performance C++ execution engine for LLM red-teaming and prompt engineering. Deploy dynamic jailbreak payloads, bypass alignment guardrails, and utilize free autonomous uncensored conversational logic locally. ⭐ 75 stars | 🔀 0 forks リポジトリを見る → 3. matt-k-wong/mlx-flash Flash weight streaming for MLX: run massive models larger than your RAM on Apple Silicon. ⭐ 45 stars | 🔀 3 forks リポジトリを見る → 4. pharaongayd/Album-Formula-Ai-2026-Update Album | Formula | Ai | Photo | Artivicial Intelligence | Creative | Tools | Generation | ⭐ 40 stars | 🔀 0 forks リポジトリを見る → 5. hanxiao/flash-kmeans-mlx IO-aware batched K-Means for Apple Silicon, ported from Flash-KMeans (Triton/CUDA) to pure MLX. Up to 94x faster than sklearn. ⭐ 13 stars | 🔀 0 forks リポジトリを見る → 📚 あわせて読みたい「プロンプトは戦略だ！」と学んで劇的効率UP！私のAI活用術私が実感！AIで物流の悩み解消、時間もコストも浮いた話 AI三つ巴！Geminiと私が出会って、ストーリー作りは変わった？。

🚀 AI技術の最新動向 – 2026年3月23日

世界中から収集したAI・機械学習の最新情報をお届けします

📑 目次

💻 注目のGitHubプロジェクト
1. rohitg00/ai-engineering-from-scratch
2. dubermandeer/Worm-GPT-LLM-2026
3. matt-k-wong/mlx-flash
4. pharaongayd/Album-Formula-Ai-2026-Update
5. hanxiao/flash-kmeans-mlx
📌 関連記事もチェック

📚 最新研究論文

1. From Masks to Pixels and Meaning: A New Taxonomy, Benchmark, and Metrics for VLM Image Tampering

著者: Xinyi Shang, Yi Tang, Jiacheng Cui

Existing tampering detection benchmarks largely rely on object masks, which severely misalign with the true edit signal: many pixels inside a mask are untouched or only trivially modified, while subtle yet consequential edits outside the mask are treated as natural. We reformulate VLM image tamperin…

論文を読む →

2. LumosX: Relate Any Identities with Their Attributes for Personalized Video Generation

著者: Jiazheng Xing, Fei Du, Hangjie Yuan

Recent advances in diffusion models have significantly improved text-to-video generation, enabling personalized content creation with fine-grained control over both foreground and background elements. However, precise face-attribute alignment across subjects remains challenging, as existing methods …

論文を読む →

3. MeanFlow Meets Control: Scaling Sampled-Data Control for Swarms

著者: Anqi Dong, Yongxin Chen, Karl H. Johansson

Steering large-scale swarms in only a few control updates is challenging because real systems operate in sampled-data form: control inputs are updated intermittently and applied over finite intervals. In this regime, the natural object is not an instantaneous velocity field, but a finite-window cont…

論文を読む →

💻 注目のGitHubプロジェクト

1. rohitg00/ai-engineering-from-scratch

Learn it. Build it. Ship it for others.

⭐ 355 stars | 🔀 58 forks

リポジトリを見る →

2. dubermandeer/Worm-GPT-LLM-2026

High-performance C++ execution engine for LLM red-teaming and prompt engineering. Deploy dynamic jailbreak payloads, bypass alignment guardrails, and utilize free autonomous uncensored conversational logic locally.

⭐ 75 stars | 🔀 0 forks

リポジトリを見る →