githubGitHubあり2026-11-03
shap — A game theoretic approach to explain the output of any machine learning model.
機械学習モデルの出力を説明するゲーム理論的手法を取ったライブラリ。
説明可能機械学習アンサンブル学習
- 用途
- 機械学習モデルの解釈
- 難易度
- Easy
- コスト
- Medium
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「SHAP」の検索結果
12 件arxivGitHubあり2026-11-02
Not All Reasoning Generalizes: A Case Study on Learning Generalizable Reasoning Strategies in RLVR
Reinforcement learning with verifiable rewards (RLVR) can enable generalizable improvement for large language
自然言語処理大規模言語モデル異常検知テキスト強化学習
- 用途
- 異常検知
- 難易度
- Hard
- コスト
- High
→
arxivGitHubあり2026-11-02
An Axiomatic Framework for Reinforcement Learning in Open Multi-Agent Systems
Open multi-agent systems, where only a subset of agents are controllable, are central to real-world domains su
強化学習方策勾配 (PPO / A3C)
- 用途
- 技術検証・論文読解補助
- 難易度
- Hard
- コスト
- Medium
→
arxivGitHubあり2026-11-02
VisCodeBench: a new benchmark dataset for Text-to-Vis reflecting real-world practice
Generating visualisations from natural language requests (text-to-vis) enables users to explore data more effi
品質予測/異常検知深層学習軽量化・量子化画像テキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Hard
- コスト
- High
→
arxivGitHubあり2026-11-02
Intent2CAD: How Semantic-Parametric Supervision Shapes Text-to-CAD Generation
Text-to-CAD generation aims to make CAD modeling more accessible by generating executable CAD programs from na
深層学習軽量化・量子化生成テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- Medium
→
huggingfaceHugging Faceあり2026-11-01
SWE-Trail: History-Guided Trajectory Collection for Coding Agent Training
Coding agents solve repository issues through long sequences of exploration, editing, and validation. These tr
自然言語処理ファインチューニングテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-10-30
DAMI: Dual-Axis Memory Initialization for Enhanced Long-Context Retrieval in Gated Linear Attention
Linear attention scales linearly with sequence length, but its finite-state memory can limit long-context retr
深層学習Transformerテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-10-29
No Channels Left Behind: Understanding Diffusion Acceleration through Residual Gates
Training acceleration methods for diffusion transformers, such as REPA and dispersive regularization, are comm
品質予測/異常検知深層学習Transformer生成画像
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-10-27
GEPA-Curator: Curated Learning for Self Improving Agents
Large Language Models (LLMs) are increasingly used in multi-turn agentic workloads that require sustained inte
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-10-26
Instruction Capacity: Behavior and Degradation of Language Models under Controlled Load
The quality with which language models follow instructions falls as the load grows, yet there is still no quan
品質予測/異常検知自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-10-25
Matched Capabilities, Different Behaviors: A Controlled Study of MCP and CLI Interfaces for Language Agents
Language agents increasingly act through external tools and interactive environments, making the interface bet
深層学習Transformerテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- Medium
→
arxivGitHubあり2026-10-08
A Closer Look at Agentic BBO: Benchmarking LLM Agents for Black-Box Optimization
Black-box optimization (BBO) arises in many scientific and engineering problems where objective evaluations ar
条件最適化自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Hard
- コスト
- High
→