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- 🚀 AI技術の最新動向 – 2026年3月16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 wanshuiyin/Auto-claude-code-research-in-sleep sstklen/trump-code matteorigodanza/cryto-trading-ai-assistant asonglin/crypto-liquidity-ai-trading-bot ranausmanai/tinyforge 📌 関連記事もチェック 📚 最新研究論文 1. PhysMoDPO: Physically-Plausible Humanoid Motion with Preference Optimization 著者: Yangsong Zhang, Anujith Muraleedharan, Rikhat Akizhanov Recent progress in text-conditioned human motion generation has been largely driven by diffusion models trained on large-scale human motion data. Building on this progress, recent methods attempt to transfer such models for character animation and real robot control by applying a Whole-Body Controll… 論文を読む → 2. Representation Learning for Spatiotemporal Physical Systems 著者: Helen Qu, Rudy Morel, Michael McCabe Machine learning approaches to spatiotemporal physical systems have primarily focused on next-frame prediction, with the goal of learning an accurate emulator for the system's evolution in time. However, these emulators are computationally expensive to train and are subject to performance pitfalls, … 論文を読む → 3. Visual-ERM: Reward Modeling for Visual Equivalence 著者: Ziyu Liu, Shengyuan Ding, Xinyu Fang Vision-to-code tasks require models to reconstruct structured visual inputs, such as charts, tables, and SVGs, into executable or structured representations with high visual fidelity. While recent Large Vision Language Models (LVLMs) achieve strong results via supervised fine-tuning, reinforcement l… 論文を読む → 💻 注目のGitHubプロジェクト 1. wanshuiyin/Auto-claude-code-research-in-sleep ARIS ⚔️ (Auto-Research-In-Sleep) — Claude Code skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation via Codex MCP ⭐ 1,523 stars | 🔀 145 forks リポジトリを見る → 2. sstklen/trump-code 🔐 AI decoding Trump's posts × stock market | AI 解碼川普推文 × 美股 | AIでトランプ投稿×株式市場を解読 — 31.5M models, 61.3% hit rate, open source ⭐ 288 stars | 🔀 27 forks リポジトリを見る → 3. matteorigodanza/cryto-trading-ai-assistant AI guardian for manual crypto traders — risk monitoring, strategy validation & emotional trading detection. No trade execution. ⭐ 109 stars | 🔀 107 forks リポジトリを見る → 4. asonglin/crypto-liquidity-ai-trading-bot Crypto liquidity detection & algorithmic trading bot. Order book analysis, stop-loss clusters, liquidity sweeps. Multi-exchange (Binance, Bybit, Kraken, OKX). Trading signals, quant research, market microstructure. ⭐ 104 stars | 🔀 100 forks リポジトリを見る → 5. ranausmanai/tinyforge A tiny model that teaches itself to code better. On your laptop. No cloud. No teacher model. No human feedback. ⭐ 55 stars | 🔀 6 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16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
- wanshuiyin/Auto-claude-code-research-in-sleep
- sstklen/trump-code
- matteorigodanza/cryto-trading-ai-assistant
- asonglin/crypto-liquidity-ai-trading-bot
- ranausmanai/tinyforge
- 📌 関連記事もチェック
📚 最新研究論文
1. PhysMoDPO: Physically-Plausible Humanoid Motion with Preference Optimization
著者: Yangsong Zhang, Anujith Muraleedharan, Rikhat Akizhanov
Recent progress in text-conditioned human motion generation has been largely driven by diffusion models trained on large-scale human motion data. Building on this progress, recent methods attempt to transfer such models for character animation and real robot control by applying a Whole-Body Controll…
2. Representation Learning for Spatiotemporal Physical Systems
著者: Helen Qu, Rudy Morel, Michael McCabe
Machine learning approaches to spatiotemporal physical systems have primarily focused on next-frame prediction, with the goal of learning an accurate emulator for the system's evolution in time. However, these emulators are computationally expensive to train and are subject to performance pitfalls, …
3. Visual-ERM: Reward Modeling for Visual Equivalence
著者: Ziyu Liu, Shengyuan Ding, Xinyu Fang
Vision-to-code tasks require models to reconstruct structured visual inputs, such as charts, tables, and SVGs, into executable or structured representations with high visual fidelity. While recent Large Vision Language Models (LVLMs) achieve strong results via supervised fine-tuning, reinforcement l…
💻 注目のGitHubプロジェクト
1. wanshuiyin/Auto-claude-code-research-in-sleep
ARIS ⚔️ (Auto-Research-In-Sleep) — Claude Code skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation via Codex MCP
⭐ 1,523 stars | 🔀 145 forks
2. sstklen/trump-code
🔐 AI decoding Trump's posts × stock market | AI 解碼川普推文 × 美股 | AIでトランプ投稿×株式市場を解読 — 31.5M models, 61.3% hit rate, open source
⭐ 288 stars | 🔀 27 forks
3. matteorigodanza/cryto-trading-ai-assistant
AI guardian for manual crypto traders — risk monitoring, strategy validation & emotional trading detection. No trade execution.
⭐ 109 stars | 🔀 107 forks
4. asonglin/crypto-liquidity-ai-trading-bot
Crypto liquidity detection & algorithmic trading bot. Order book analysis, stop-loss clusters, liquidity sweeps. Multi-exchange (Binance, Bybit, Kraken, OKX). Trading signals, quant research, market microstructure.
⭐ 104 stars | 🔀 100 forks
5. ranausmanai/tinyforge
A tiny model that teaches itself to code better. On your laptop. No cloud. No teacher model. No human feedback.
⭐ 55 stars | 🔀 6 forks
📚 あわせて読みたい
