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Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
Paper • 2507.01352 • Published • 56 -
A Data-Centric Framework for Addressing Phonetic and Prosodic Challenges in Russian Speech Generative Models
Paper • 2507.13563 • Published • 52 -
Scaling Laws for Optimal Data Mixtures
Paper • 2507.09404 • Published • 36 -
Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation
Paper • 2511.14993 • Published • 229
Huiwon Yun
mangoxb
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AI & ML interests
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Recent Activity
updated
a collection
3 days ago
cabinet-data_curation
updated
a collection
3 days ago
cabinet-data_curation
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a collection
3 days ago
cabinet-data_curation
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read
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One-Minute Video Generation with Test-Time Training
Paper • 2504.05298 • Published • 110 -
MoCha: Towards Movie-Grade Talking Character Synthesis
Paper • 2503.23307 • Published • 138 -
Towards Understanding Camera Motions in Any Video
Paper • 2504.15376 • Published • 155 -
Antidistillation Sampling
Paper • 2504.13146 • Published • 59
cabinet
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Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 301 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 306 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
cabinet-data_curation
-
Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
Paper • 2507.01352 • Published • 56 -
A Data-Centric Framework for Addressing Phonetic and Prosodic Challenges in Russian Speech Generative Models
Paper • 2507.13563 • Published • 52 -
Scaling Laws for Optimal Data Mixtures
Paper • 2507.09404 • Published • 36 -
Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation
Paper • 2511.14993 • Published • 229
cabinet
-
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 301 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 306 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
read
-
One-Minute Video Generation with Test-Time Training
Paper • 2504.05298 • Published • 110 -
MoCha: Towards Movie-Grade Talking Character Synthesis
Paper • 2503.23307 • Published • 138 -
Towards Understanding Camera Motions in Any Video
Paper • 2504.15376 • Published • 155 -
Antidistillation Sampling
Paper • 2504.13146 • Published • 59