-
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Paper • 2509.22186 • Published • 139 -
PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model
Paper • 2510.14528 • Published • 111 -
MinerU: An Open-Source Solution for Precise Document Content Extraction
Paper • 2409.18839 • Published • 37
Anurag Yadav
harryadav3
·
AI & ML interests
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Organizations
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web-crawlers
llms-mlm
3d-4d/embodied
LLMS
audio
RL
mech-inter
videogeneration
agentic ai
-
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 228 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 53 -
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 117 -
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 122
parsing
-
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Paper • 2509.22186 • Published • 139 -
PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model
Paper • 2510.14528 • Published • 111 -
MinerU: An Open-Source Solution for Precise Document Content Extraction
Paper • 2409.18839 • Published • 37
audio
web-crawlers
RL
llms-mlm
mech-inter
3d-4d/embodied
videogeneration
LLMS
agentic ai
-
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 228 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 53 -
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 117 -
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 122