📝 この記事のポイント
- 🚀 AI技術の最新動向 – 2026年1月27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 fangchenantek/Psychosis-of-AI sidmohan0/tesserack Colev2/Neural-Networks yaelelmatad/RunTime-Public 📌 関連記事もチェック 📚 最新研究論文 1. ctELM: Decoding and Manipulating Embeddings of Clinical Trials with Embedding Language Models 著者: Brian Ondov, Chia-Hsuan Chang, Yujia Zhou Text embeddings have become an essential part of a variety of language applications. However, methods for interpreting, exploring and reversing embedding spaces are limited, reducing transparency and precluding potentially valuable generative use cases. In this work, we align Large Language Models t… 論文を読む → 2. Reuse your FLOPs: Scaling RL on Hard Problems by Conditioning on Very Off-Policy Prefixes 著者: Amrith Setlur, Zijian Wang, Andrew Cohen Typical reinforcement learning (RL) methods for LLM reasoning waste compute on hard problems, where correct on-policy traces are rare, policy gradients vanish, and learning stalls. To bootstrap more efficient RL, we consider reusing old sampling FLOPs (from prior inference or RL training) in the for… 論文を読む → 3. MEGnifying Emotion: Sentiment Analysis from Annotated Brain Data 著者: Brian Liu, Oiwi Parker Jones Decoding emotion from brain activity could unlock a deeper understanding of the human experience. While a number of existing datasets align brain data with speech and with speech transcripts, no datasets have annotated brain data with sentiment. To bridge this gap, we explore the use of pre-trained … 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 ⭐ 171 stars | 🔀 4 forks リポジトリを見る → 2. fangchenantek/Psychosis-of-AI 一份来自2026年的AI精神病理学诊断报告 / A Pathological Diagnosis of AI Civilization ⭐ 36 stars | 🔀 0 forks リポジトリを見る → 3. sidmohan0/tesserack LLM + RL agent to beat Pokemon Red ⭐ 27 stars | 🔀 3 forks リポジトリを見る → 4. Colev2/Neural-Networks Assignments on Neural Networks course at CSD AUTH ⭐ 7 stars | 🔀 0 forks リポジトリを見る → 5. yaelelmatad/RunTime-Public RunTime: intensity-free, TPP-aligned Transformer for probabilistic forecasting on irregular event streams, regular event streams, or general regression tasks. ⭐ 5 stars | 🔀 0 forks リポジトリを見る → 📚 あわせて読みたい 【AI最新動向】一歩先の未来へ！私が触れた最先端AIの世界 「プロンプトは戦略だ！」と学んで劇的効率UP！私のAI活用術 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27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
- fangchenantek/Psychosis-of-AI
- sidmohan0/tesserack
- Colev2/Neural-Networks
- yaelelmatad/RunTime-Public
- 📌 関連記事もチェック
📚 最新研究論文
1. ctELM: Decoding and Manipulating Embeddings of Clinical Trials with Embedding Language Models
著者: Brian Ondov, Chia-Hsuan Chang, Yujia Zhou
Text embeddings have become an essential part of a variety of language applications. However, methods for interpreting, exploring and reversing embedding spaces are limited, reducing transparency and precluding potentially valuable generative use cases. In this work, we align Large Language Models t…
2. Reuse your FLOPs: Scaling RL on Hard Problems by Conditioning on Very Off-Policy Prefixes
著者: Amrith Setlur, Zijian Wang, Andrew Cohen
Typical reinforcement learning (RL) methods for LLM reasoning waste compute on hard problems, where correct on-policy traces are rare, policy gradients vanish, and learning stalls. To bootstrap more efficient RL, we consider reusing old sampling FLOPs (from prior inference or RL training) in the for…
3. MEGnifying Emotion: Sentiment Analysis from Annotated Brain Data
著者: Brian Liu, Oiwi Parker Jones
Decoding emotion from brain activity could unlock a deeper understanding of the human experience. While a number of existing datasets align brain data with speech and with speech transcripts, no datasets have annotated brain data with sentiment. To bridge this gap, we explore the use of pre-trained …
💻 注目のGitHubプロジェクト
1. stong/gradscii-art
An extremely good ASCII art generator, based on machine learning
⭐ 171 stars | 🔀 4 forks
2. fangchenantek/Psychosis-of-AI
一份来自2026年的AI精神病理学诊断报告 / A Pathological Diagnosis of AI Civilization
⭐ 36 stars | 🔀 0 forks
4. Colev2/Neural-Networks
Assignments on Neural Networks course at CSD AUTH
⭐ 7 stars | 🔀 0 forks
5. yaelelmatad/RunTime-Public
RunTime: intensity-free, TPP-aligned Transformer for probabilistic forecasting on irregular event streams, regular event streams, or general regression tasks.
⭐ 5 stars | 🔀 0 forks
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