OpenVision 3: A Family of Unified Visual Encoder for Both Understanding and Generation
Paper • 2601.15369 • Published • 21 •
3
Ritvik Rastogi
Ritvik19
AI & ML interests
Machine Learning Deep Learning, Natural Language Processing, Computer Vision
Recent Activity
updated a dataset about 8 hours ago
Ritvik19/flickr30k published a dataset about 8 hours ago
Ritvik19/flickr30k updated a dataset about 22 hours ago
Ritvik19/qqp-info_nceOrganizations
commented a
paper 2 months ago
commented a
paper 6 months ago
commented 2
papers 9 months ago
commented 6
papers 11 months ago
REFINE-AF: A Task-Agnostic Framework to Align Language Models via Self-Generated Instructions using Reinforcement Learning from Automated Feedback
Paper • 2505.06548 • Published • 30 •
6
REFINE-AF: A Task-Agnostic Framework to Align Language Models via Self-Generated Instructions using Reinforcement Learning from Automated Feedback
Paper • 2505.06548 • Published • 30 •
6
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Paper • 2504.20571 • Published • 98 •
15
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Paper • 2504.20571 • Published • 98 •
15
Process Reward Models That Think
Paper • 2504.16828 • Published • 18 •
5
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 141 •
21
commented 8
papers 12 months ago
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 141 •
21
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 141 •
21
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 141 •
21
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 141 •
21
DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
Paper • 2504.11456 • Published • 12 •
6
DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
Paper • 2504.11456 • Published • 12 •
6
From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models
Paper • 2504.06214 • Published •
1
Unlocking Efficient Long-to-Short LLM Reasoning with Model Merging
Paper • 2503.20641 • Published • 10 •
5
commented a
paper about 1 year ago
[24/ 11] What are you working on this week! 💪
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#2 opened over 1 year ago
by 
reach-vb