huggingfaceHugging Faceあり2026-07-21
ISO: An RLVR-Native Optimization Stack
Reinforcement learning with verifiable rewards (RLVR) is rapidly advancing the reasoning capabilities of langu
深層学習正規化・最適化手法テキスト強化学習
- 用途
- 技術検証・論文読解補助
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「reinforcement」の検索結果
19 件huggingfaceGitHubありHugging Faceあり2026-07-20
Differentiable Logic Gate Networks for Low-Latency EEG Classification on Edge Devices
Real-time EEG classification on edge devices is bottlenecked by the floating-point arithmetic of conventional
CPUで試しやすい強化学習マルチエージェント分類検出
- 用途
- 分類
- 難易度
- Easy
- コスト
- Low
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huggingfaceHugging Faceあり2026-07-20
ConsiSpace: Learning Geometric Consistency Matters for Video Spatial Reasoning
Video spatial reasoning is essential for navigation-oriented perception and long-video question answering, whe
深層学習軽量化・量子化QAテキスト動画
- 用途
- QA
- 難易度
- Easy
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- High
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huggingfaceHugging Faceあり2026-07-19
TimeLens2: Generalist Video Temporal Grounding with Multimodal LLMs
Video multimodal large language models (MLLMs) can describe what happens in a video, but rarely identify when
自然言語処理大規模言語モデル検出テキスト動画
- 用途
- 検出
- 難易度
- Easy
- コスト
- High
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huggingfaceGitHubありHugging Faceあり2026-07-19
Distilled Reinforcement Learning for LLM Post-training
Large language model (LLM) post-training is essential for improving reasoning, adaptation, and alignment. Exis
説明可能品質予測/異常検知深層学習軽量化・量子化テキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-18
Group Entropy-Controlled Policy Optimization
Entropy control has become an effective tool in reinforcement learning (RL) of large language models (LLMs), h
深層学習軽量化・量子化生成テキスト強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-17
SeerGuard: A Safety Framework for Mobile GUI Agents via World Model Prediction
Mobile graphical user interface (GUI) agents have demonstrated remarkable capabilities in automating complex t
強化学習モデルベース
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- Medium
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huggingfaceHugging Faceあり2026-07-17
JoyNexus: Service-Oriented Multi-Tenant Post-Training for VLA Models
The post-training of Vision-Language-Action (VLA) models is essential due to the diversity of simulators, robo
CPUで試しやすい深層学習軽量化・量子化マルチモーダル強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-17
Understanding Reasoning from Pretraining to Post-Training
Reinforcement learning (RL) has become central to improving large language models (LLMs) on complex reasoning
自然言語処理大規模言語モデルテキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-17
When Does Muon Help Agentic Reinforcement Learning?
Muon is competitive with AdamW in large-scale pre-training, but its value for reinforcement-learning (RL) post
深層学習正規化・最適化手法強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-17
DSWorld: A Data Science World Model for Efficient Autonomous Agents
Despite strong capabilities in data understanding and decision-making, autonomous data science agents still he
深層学習軽量化・量子化強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceGitHubありHugging Faceあり2026-07-16
On-Policy Delta Distillation
On-policy distillation is an alternative post-training method in reinforcement learning that alleviates the co
深層学習軽量化・量子化強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-16
Beyond Entropy: Correctness-Aware Advantage Shaping via Contrastive Policy Optimization
Reinforcement learning with verifiable rewards (RLVR) commonly uses entropy for advantage shaping. However, en
深層学習軽量化・量子化生成強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- Medium
→
huggingfaceHugging Faceあり2026-07-13
SVR-R1: Bootstrapping Multi-modal Reasoning with Self-verification in Reinforcement Learning
We introduce Self-Verified Reasoner (SVR-R1), a multi-turn RL framework that turns a model's own verification
コンピュータビジョンセグメンテーション生成マルチモーダル強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-12
Predictive Divergence Masks for LLM RL
Reinforcement learning for large language models (LLMs) typically relies on trust-region masks to stabilize of
深層学習軽量化・量子化テキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-11
Beyond Euclidean Clipping: Overcoming Exploration Collapse in LLM RL via Riemannian Isometric Policy Optimization
Reinforcement learning (RL) has become a dominant paradigm for enhancing LLMs' reasoning capabilities. However
自然言語処理大規模言語モデル強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-08
DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment
Training tool-use agents to improve from their own experience remains challenging, as supervised fine-tuning r
深層学習軽量化・量子化生成強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-07-08
Agon: Competitive Cross-Model RL with Implicit Rival Grading of Reasoning
Reinforcement learning from verifiable rewards (e.g. GRPO) is the engine behind today's reasoning models, yet
コンピュータビジョンセグメンテーションテキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-07
Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL
Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environment
自然言語処理大規模言語モデルテキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→