GreenMind: A Next-Generation Vietnamese Large Language Model for Structured and Logical Reasoning
On the map: LLM reasoning → Reasoning benchmarks and evaluation
Abstract (arXiv)
Chain-of-Thought (CoT) is a robust approach for tackling LLM tasks that require intermediate reasoning steps prior to generating a final answer. In this paper, we present GreenMind-Medium-14B-R1, the Vietnamese reasoning model inspired by the finetuning strategy based on Group Relative Policy Optimization. We also leverage a high-quality Vietnamese synthesized reasoning dataset and design two reward functions to tackle the main limitations of this technique: (i) language mixing, where we explicitly detect the presence of biased language characters during the process of sampling tokens, and (ii) we leverage Sentence Transformer-based models to ensure that the generated reasoning content maintains factual correctness and does not distort the final output. Experimental results on the Vietnamese dataset from the VLSP 2023 Challenge demonstrate that our model outperforms prior works and enhances linguistic consistency in its responses. Furthermore, we extend our evaluation to SeaExam-a multilingual multiple-choice dataset, showing the effectiveness of our reasoning method compared to few-shot prompting techniques.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 10 of its 20 references that are in the map. First posted on arXiv 23 Apr 2025.
Builds on
10 of 20 references.
References · 10
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
- 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
- 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
- 2020GLU Variants Improve Transformercited by 1,804
- 20242 OLMo 2 Furiouscited by 340
- 2022What Language Model to Train if You Have One Million GPU Hours?cited by 92
- 2016Gated-Attention Readers for Text Comprehensioncited by 37
- 2023PhoGPT: Generative Pre-training for Vietnamesecited by 8
- 2024Overview of the VLSP 2023 -- ComOM Shared Task: A Data Challenge for Comparative Opinion Mining from Vietnamese Product Reviewscited by 3
- 2024ViLLM-Eval: A Comprehensive Evaluation Suite for Vietnamese Large Language Modelscited by 1
Built on by
Citing papers per year: 2026: 3.
3 papers.
- 2026Towards general embodied intelligence: integrating large language models, knowledge bases, and reasoning capabilities to build the next generation of AI agentscited by 1
- 2026ConnectED: A Curriculum-Aligned AI System for Vietnamese Instructional Lesson Planning and Student Learningcited by 0
- 2026VIVID: A Culturally Grounded Benchmark Exposing the Figurative Language Gap in Vietnamese NLPcited by 0
- 2026Towards general embodied intelligence: integrating large language models, knowledge bases, and reasoning capabilities to build the next generation of AI agents20 Aug 2026
- 2026VIVID: A Culturally Grounded Benchmark Exposing the Figurative Language Gap in Vietnamese NLP4 Aug 2026
- 2026ConnectED: A Curriculum-Aligned AI System for Vietnamese Instructional Lesson Planning and Student Learning2 Jun 2026
Similar, not cited
Close in wording, no citation either way
- 2026Bridging the Reasoning Gap in Vietnamese with Small Language Models via Test-Time Scaling
- 2025Pushing on Multilingual Reasoning Models with Language-Mixed Chain-of-Thought
- 2025Reasoning Beyond Limits: Advances and Open Problems for LLMs
- 2024Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought
- 2025Advancing Reasoning in Large Language Models: Promising Methods and Approaches
- 2024General Purpose Verification for Chain of Thought Prompting
- 2024Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
- 2026Correct, Concise and Complete: Multi-stage Training For Adaptive Reasoning