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- 🚀 AI技術の最新動向 – 2026年1月29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 stong/gradscii-art sidmohan0/tesserack pentoai/ml-ralph nhevers/neuralcfd aman179102/trust-aware 📌 関連記事もチェック 📚 最新研究論文 1. Evolutionary Strategies lead to Catastrophic Forgetting in LLMs 著者: Immanuel Abdi, Akshat Gupta, Micah Mok One of the biggest missing capabilities in current AI systems is the ability to learn continuously after deployment. Implementing such continually learning systems have several challenges, one of which is the large memory requirement of gradient-based algorithms that are used to train state-of-the-a… 論文を読む → 2. SokoBench: Evaluating Long-Horizon Planning and Reasoning in Large Language Models 著者: Sebastiano Monti, Carlo Nicolini, Gianni Pellegrini Although the capabilities of large language models have been increasingly tested on complex reasoning tasks, their long-horizon planning abilities have not yet been extensively investigated. In this work, we provide a systematic assessment of the planning and long-horizon reasoning capabilities of s… 論文を読む → 3. Exploring Transformer Placement in Variational Autoencoders for Tabular Data Generation 著者: Aníbal Silva, Moisés Santos, André Restivo Tabular data remains a challenging domain for generative models. In particular, the standard Variational Autoencoder (VAE) architecture, typically composed of multilayer perceptrons, struggles to model relationships between features, especially when handling mixed data types. In contrast, Transforme… 論文を読む → 💻 注目のGitHubプロジェクト 1. stong/gradscii-art An extremely good ASCII art generator, based on machine learning ⭐ 179 stars | 🔀 7 forks リポジトリを見る → 2. sidmohan0/tesserack Compiling strategy guides into reward functions for reinforcement learning. Uses Claude Vision to extract unit tests from game guides, then trains agents with dense, interpretable rewards. ⭐ 30 stars | 🔀 4 forks リポジトリを見る → 3. pentoai/ml-ralph Autonomous ML agent for running experiments using Claude or Codex. ⭐ 16 stars | 🔀 0 forks リポジトリを見る → 4. nhevers/neuralcfd neural network surrogate for CFD simulations ⭐ 7 stars | 🔀 0 forks リポジトリを見る → 5. aman179102/trust-aware A trust-aware, human-in-the-loop AI decision system that knows when not to trust model confidence. ⭐ 5 stars | 🔀 2 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1月29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
- stong/gradscii-art
- sidmohan0/tesserack
- pentoai/ml-ralph
- nhevers/neuralcfd
- aman179102/trust-aware
- 📌 関連記事もチェック
📚 最新研究論文
1. Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
著者: Immanuel Abdi, Akshat Gupta, Micah Mok
One of the biggest missing capabilities in current AI systems is the ability to learn continuously after deployment. Implementing such continually learning systems have several challenges, one of which is the large memory requirement of gradient-based algorithms that are used to train state-of-the-a…
2. SokoBench: Evaluating Long-Horizon Planning and Reasoning in Large Language Models
著者: Sebastiano Monti, Carlo Nicolini, Gianni Pellegrini
Although the capabilities of large language models have been increasingly tested on complex reasoning tasks, their long-horizon planning abilities have not yet been extensively investigated. In this work, we provide a systematic assessment of the planning and long-horizon reasoning capabilities of s…
3. Exploring Transformer Placement in Variational Autoencoders for Tabular Data Generation
著者: Aníbal Silva, Moisés Santos, André Restivo
Tabular data remains a challenging domain for generative models. In particular, the standard Variational Autoencoder (VAE) architecture, typically composed of multilayer perceptrons, struggles to model relationships between features, especially when handling mixed data types. In contrast, Transforme…
💻 注目のGitHubプロジェクト
1. stong/gradscii-art
An extremely good ASCII art generator, based on machine learning
⭐ 179 stars | 🔀 7 forks
2. sidmohan0/tesserack
Compiling strategy guides into reward functions for reinforcement learning. Uses Claude Vision to extract unit tests from game guides, then trains agents with dense, interpretable rewards.
⭐ 30 stars | 🔀 4 forks
3. pentoai/ml-ralph
Autonomous ML agent for running experiments using Claude or Codex.
⭐ 16 stars | 🔀 0 forks
5. aman179102/trust-aware
A trust-aware, human-in-the-loop AI decision system that knows when not to trust model confidence.
⭐ 5 stars | 🔀 2 forks
📚 あわせて読みたい
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