Typhoon’s Papers Acceptances at ICLR 2025: Advancing Open Science for Low-Resource Language AI
PaperConferenceTyphoon 2
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We're proud to announce the acceptance of two groundbreaking papers at the Open Science for Foundation Models (SCI-FM) workshop, International Conference on Learning Representations (ICLR) 2025 🎉
ICLR is regarded as one of the premier machine learning conferences globally. These acceptances mark a significant milestone in our mission to democratize AI technology for low-resource languages, particularly Thai, and establish a replicable framework for advancing AI capabilities in other low-resource languages.
Breaking the Resource Barrier Through Open Science
AI development has largely focused on resource-rich languages, creating a technological divide. Our research demonstrates how open science can bridge this gap, using Thai as a proving ground for methodologies applicable to any low-resource language.
Typhoon T1: The First Open Thai Reasoning Model with Structured Thinking Format
Figure 1: Structured Long-thinking Data Transformation-And-Refinement Pipeline
Typhoon T1: An Open Thai Reasoning Model represents a fundamental shift in how we approach reasoning capabilities in low-resource languages. Key innovations include:
- Novel Supervised Fine-tuning Pipeline: Unlike traditional reinforcement learning approaches, our supervised fine-tuning methodology ensures stable and transparent development of reasoning capabilities.
- Structured Thinking Format: Implementation of XML-based thinking traces that enhance the model's ability to break down complex problems into manageable steps.
- Open-Source Implementation: Complete transparency in datasets, methodology, and model weights, fostering collaborative development in the Thai AI community.
Fun fact: Typhoon T1 is not only the first Thai reasoning model but also the first reasoning model in Southeast Asia.
Adapting Language-Specific LLMs to a Reasoning Model in One Day via Model Merging – An Open Recipe
Figure 2: Overview of our Typhoon 2 R1 70B recipe
This paper showcases how we can incorporate advanced reasoning capabilities such as those of DeepSeek R1 into language-specific large language models (LLMs), Typhoon 2 in this case.
We present a scalable approach to enhancing low-resource language models through model merging techniques:
- Representation Alignment: A sophisticated approach to aligning Thai language understanding with reasoning capabilities through bilingual dataset training.
- Ability-Aware Layer Weighting: Strategic assignment of model weights that preserves language capabilities while significantly enhancing reasoning abilities.
- Resource-Efficient Implementation: Achieving state-of-the-art results without the need for massive computational resources.
- Cross-Lingual Knowledge Transfer: Systematic approach to adapting reasoning capabilities across languages
Impact on Global AI Development
Our research demonstrates that sophisticated AI capabilities aren't exclusive to high-resource languages. These papers represent significant breakthroughs in:
| Aspect | Achievement |
|---|---|
| Reasoning Capability | Comparable performance to English language models in complex reasoning tasks |
| Accessibility | Full open-source implementation with comprehensive documentation |
| Resource Efficiency | Makes advanced AI development accessible to smaller research communities |
| Cross-Lingual Methodology | Provides a blueprint for adaptation to any other low-resource language |
Looking Forward
These acceptances at the SCI-FM Workshop, ICLR 2025, highlight the importance of our approach to open science and our focus on improving low-resource languages, not just the dominant ones. We're committed to:
- Open Collaboration: Releasing our models and datasets to the research community
- Continued Innovation: Building upon these foundations for even more sophisticated low-resource language AI capabilities, particularly Thai.
- Community Engagement: Working with Thai developers and researchers to expand the applications of these technologies
About ICLR and SCI-FM Workshop
We're particularly excited to be presenting at the Open Science for Foundation Models (SCI-FM) Workshop at ICLR 2025, which perfectly aligns with our mission of promoting open science in AI development. Our contributions to SCI-FM workshop exemplify the workshop's core mission: making advanced AI research accessible and reproducible for the global research community.
Meet Our Team at ICLR 2025
Join us at ICLR 2025's SCI-FM workshop to:
- 🤝 Discuss potential collaborations for adapting our framework to your language
- 💡 Learn about our open-science methodologies firsthand
- 🔍 Deep dive into our technical implementations
- 🌐 Connect with our research team and join our growing community
Workshop Details:
- 📍 ICLR 2025 SCI-FM (Workshop Hall 4 #5)
- 📅 April 28, 2025 15:00 - 16:00 (GMT+8)
- 💬 Meet us at our booth from 24 to 28 April 2025
Join our virtual community
Beyond ICLR 2025: 📚 Read our papers:
- Typhoon T1: https://arxiv.org/abs/2502.09042
- Typhoon2 R1: https://arxiv.org/abs/2502.09056
🔬 Explore our open-source implementations
- Open-weight models: https://huggingface.co/scb10x
- More open-source initiatives of us can be found at: opentyphoon.ai
📱 Join us in our always-on Discord community
