Tiny Model, Big Logic: Diversity-Driven Optimization Elicits Large-Model Reasoning Ability in VibeThinker-1.5B
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Sen, Zhou, Yi, Wang, Wei, Min, Jixin, Yin, Zhibin, Dai, Yingwei, Liu, Shixi, Pang, Lianyu, Chen, Yirong, Zhang, Junlin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
by: Li, Weijia, et al.
Published: (2025)
by: Li, Weijia, et al.
Published: (2025)
Eliciting Causal Abilities in Large Language Models for Reasoning Tasks
by: Wang, Yajing, et al.
Published: (2024)
by: Wang, Yajing, et al.
Published: (2024)
Evaluating the Logical Reasoning Abilities of Large Reasoning Models
by: Liu, Hanmeng, et al.
Published: (2025)
by: Liu, Hanmeng, et al.
Published: (2025)
A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning
by: Hong, Ruixin, et al.
Published: (2023)
by: Hong, Ruixin, et al.
Published: (2023)
DDA-Thinker: Decoupled Dual-Atomic Reinforcement Learning for Reasoning-Driven Image Editing
by: Yang, Hanqing, et al.
Published: (2026)
by: Yang, Hanqing, et al.
Published: (2026)
TinyThinker: Distilling Reasoning through Coarse-to-Fine Knowledge Internalization with Self-Reflection
by: Piao, Shengmin, et al.
Published: (2024)
by: Piao, Shengmin, et al.
Published: (2024)
HateTinyLLM : Hate Speech Detection Using Tiny Large Language Models
by: Sen, Tanmay, et al.
Published: (2024)
by: Sen, Tanmay, et al.
Published: (2024)
LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models
by: Wan, Yuxuan, et al.
Published: (2024)
by: Wan, Yuxuan, et al.
Published: (2024)
Tiny Refinements Elicit Resilience: Toward Efficient Prefix-Model Against LLM Red-Teaming
by: Liu, Jiaxu, et al.
Published: (2024)
by: Liu, Jiaxu, et al.
Published: (2024)
Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles
by: Shah, Kulin, et al.
Published: (2024)
by: Shah, Kulin, et al.
Published: (2024)
Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers
by: Green, Tommaso, et al.
Published: (2025)
by: Green, Tommaso, et al.
Published: (2025)
LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models
by: Parmar, Mihir, et al.
Published: (2024)
by: Parmar, Mihir, et al.
Published: (2024)
Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verification
by: Mitchell, Jacqueline, et al.
Published: (2025)
by: Mitchell, Jacqueline, et al.
Published: (2025)
Vibe Reasoning: Eliciting Frontier AI Mathematical Capabilities -- A Case Study on IMO 2025 Problem 6
by: Wu, Jiaao, et al.
Published: (2025)
by: Wu, Jiaao, et al.
Published: (2025)
ORACLE: Optimizing Reasoning Abilities of Large Language Models via Constraint-Led Synthetic Data Elicitation
by: Yang, Zhuojie, et al.
Published: (2026)
by: Yang, Zhuojie, et al.
Published: (2026)
VeriThinker: Learning to Verify Makes Reasoning Model Efficient
by: Chen, Zigeng, et al.
Published: (2025)
by: Chen, Zigeng, et al.
Published: (2025)
DiffThinker: Towards Generative Multimodal Reasoning with Diffusion Models
by: He, Zefeng, et al.
Published: (2025)
by: He, Zefeng, et al.
Published: (2025)
OneThinker: All-in-one Reasoning Model for Image and Video
by: Feng, Kaituo, et al.
Published: (2025)
by: Feng, Kaituo, et al.
Published: (2025)
Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs
by: Puerto, Haritz, et al.
Published: (2024)
by: Puerto, Haritz, et al.
Published: (2024)
Logic-Regularized Verifier Elicits Reasoning from LLMs
by: Wang, Xinyu, et al.
Published: (2026)
by: Wang, Xinyu, et al.
Published: (2026)
From Blind Solvers to Logical Thinkers: Benchmarking LLMs' Logical Integrity on Faulty Mathematical Problems
by: Rahman, A M Muntasir, et al.
Published: (2024)
by: Rahman, A M Muntasir, et al.
Published: (2024)
EgoThinker: Unveiling Egocentric Reasoning with Spatio-Temporal CoT
by: Pei, Baoqi, et al.
Published: (2025)
by: Pei, Baoqi, et al.
Published: (2025)
LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models
by: Gui, Jiayi, et al.
Published: (2024)
by: Gui, Jiayi, et al.
Published: (2024)
LogTinyLLM: Tiny Large Language Models Based Contextual Log Anomaly Detection
by: Ocansey, Isaiah Thompson, et al.
Published: (2025)
by: Ocansey, Isaiah Thompson, et al.
Published: (2025)
Apriel-1.5-15b-Thinker
by: Radhakrishna, Shruthan, et al.
Published: (2025)
by: Radhakrishna, Shruthan, et al.
Published: (2025)
TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking
by: Wang, Danqing, et al.
Published: (2024)
by: Wang, Danqing, et al.
Published: (2024)
WebThinker: Empowering Large Reasoning Models with Deep Research Capability
by: Li, Xiaoxi, et al.
Published: (2025)
by: Li, Xiaoxi, et al.
Published: (2025)
Self-Evolving Spatial Reasoning in Vision Language Models via Geometric Logic Consistency
by: Liu, Junming, et al.
Published: (2026)
by: Liu, Junming, et al.
Published: (2026)
Vibe Modeling: Challenges and Opportunities
by: Cabot, Jordi
Published: (2025)
by: Cabot, Jordi
Published: (2025)
Apriel-Nemotron-15B-Thinker
by: Radhakrishna, Shruthan, et al.
Published: (2025)
by: Radhakrishna, Shruthan, et al.
Published: (2025)
Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models
by: Zhao, Zekai, et al.
Published: (2025)
by: Zhao, Zekai, et al.
Published: (2025)
Intuitive Thinkers and Social Adaptation: The Role of Language Ability in Academic and Life Outcomes
by: Sugawara, Akihito
Published: (2026)
by: Sugawara, Akihito
Published: (2026)
Intuitive Thinkers and Social Adaptation: The Role of Language Ability in Academic and Life Outcomes
by: Sugawara, Akihito
Published: (2026)
by: Sugawara, Akihito
Published: (2026)
MDD-Thinker: Towards Large Reasoning Models for Major Depressive Disorder Diagnosis
by: Sha, Yuyang, et al.
Published: (2025)
by: Sha, Yuyang, et al.
Published: (2025)
VR-Thinker: Boosting Video Reward Models through Thinking-with-Image Reasoning
by: Wang, Qunzhong, et al.
Published: (2025)
by: Wang, Qunzhong, et al.
Published: (2025)
VideoThinker: Building Agentic VideoLLMs with LLM-Guided Tool Reasoning
by: Li, Chenglin, et al.
Published: (2026)
by: Li, Chenglin, et al.
Published: (2026)
AutoLogi: Automated Generation of Logic Puzzles for Evaluating Reasoning Abilities of Large Language Models
by: Zhu, Qin, et al.
Published: (2025)
by: Zhu, Qin, et al.
Published: (2025)
Eliciting Reasoning in Language Models with Cognitive Tools
by: Ebouky, Brown, et al.
Published: (2025)
by: Ebouky, Brown, et al.
Published: (2025)
Diversity of Thought Improves Reasoning Abilities of LLMs
by: Naik, Ranjita, et al.
Published: (2023)
by: Naik, Ranjita, et al.
Published: (2023)
RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models
by: Wang, Zekun Moore, et al.
Published: (2023)
by: Wang, Zekun Moore, et al.
Published: (2023)
Similar Items
-
LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
by: Li, Weijia, et al.
Published: (2025) -
Eliciting Causal Abilities in Large Language Models for Reasoning Tasks
by: Wang, Yajing, et al.
Published: (2024) -
Evaluating the Logical Reasoning Abilities of Large Reasoning Models
by: Liu, Hanmeng, et al.
Published: (2025) -
A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning
by: Hong, Ruixin, et al.
Published: (2023) -
DDA-Thinker: Decoupled Dual-Atomic Reinforcement Learning for Reasoning-Driven Image Editing
by: Yang, Hanqing, et al.
Published: (2026)