Zixiang Zheng

imzhengzx's activity

• All
• Models
• Datasets
• Spaces
• Papers
• Collections
• Community
• Posts
• Upvotes
• Likes
• Articles

upvoted 2 papers 21 days ago

Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?

Paper • 2504.00509 • Published 22 days ago • 21

Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead

Paper • 2504.00294 • Published 23 days ago • 10

upvoted 3 papers 27 days ago

Wan: Open and Advanced Large-Scale Video Generative Models

Paper • 2503.20314 • Published 28 days ago • 49

Qwen2.5-Omni Technical Report

Paper • 2503.20215 • Published 29 days ago • 140

Think Twice: Enhancing LLM Reasoning by Scaling Multi-round Test-time Thinking

Paper • 2503.19855 • Published 29 days ago • 26

upvoted 3 papers 28 days ago

Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models via Vision-Guided Reinforcement Learning

Paper • 2503.18013 • Published Mar 23 • 19

SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

Paper • 2503.18892 • Published 30 days ago • 30

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Paper • 2503.19470 • Published 29 days ago • 17

upvoted 4 papers about 1 month ago

OmniMamba: Efficient and Unified Multimodal Understanding and Generation via State Space Models

Paper • 2503.08686 • Published Mar 11 • 18

Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Paper • 2503.06749 • Published Mar 9 • 29

Agent models: Internalizing Chain-of-Action Generation into Reasoning models

Paper • 2503.06580 • Published Mar 9 • 16

BlackGoose Rimer: Harnessing RWKV-7 as a Simple yet Superior Replacement for Transformers in Large-Scale Time Series Modeling

Paper • 2503.06121 • Published Mar 8 • 5

upvoted a paper about 2 months ago

Babel: Open Multilingual Large Language Models Serving Over 90% of Global Speakers

Paper • 2503.00865 • Published Mar 2 • 64

upvoted 4 papers 2 months ago

LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Paper • 2502.07374 • Published Feb 11 • 39

The Curse of Depth in Large Language Models

Paper • 2502.05795 • Published Feb 9 • 39

Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning

Paper • 2502.06781 • Published Feb 10 • 61

Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling

Paper • 2502.06703 • Published Feb 10 • 151

liked a model 10 months ago

AI-MO/NuminaMath-7B-TIR

Text Generation • Updated Aug 14, 2024 • 7.56k • 340