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@@ -23,14 +23,14 @@ Our Mission: **GenAI for all, intelligence in every task.**
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  - [InfiFPO](https://huggingface.co/InfiX-ai/InfiFPO-14B): **InfiFPO** is a lightweight fusion method during the preference alignment phase that injects fused model behavior into preference learning, enabling richer signal during DPO-style fine-tuning.
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- #### 🧠 Reaoning-enhanced End-to-end Train Pipeline within Ultra Low Resource
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  - [InfiR](https://huggingface.co/papers/2502.11573): **InfiR** aims to advance AI systems by improving reasoning, reducing adoption barriers, and addressing privacy concerns through smaller model sizes.
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  - [InfiR-FP8](https://huggingface.co/InfiX-ai): **InfiR-FP8** is a smaller reasoning-enhanced model trained from scratch using FP8 precision, achieving successful convergence while reducing memory usage by 10% and improving training speed by 20% during the training process. The model will be released in mid-September.
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  - [InfiAlign](http://huggingface.co/collections/InfiX-ai/infialign-688600ca363ab9ef0b78f7a6): **InfiAlign** is a scalable and data-efficient post-training framework that combines supervised fine-tuning (SFT) and reinforcement learning (RL) with a high-quality data selection pipeline to enhance reasoning in large language models.
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  - [InfiMMR](https://arxiv.org/abs/2505.23091): **InfiMMR** is a novel three-phase curriculum framework that systematically enhances multimodal reasoning capabilities in small language models through foundational reasoning activation, cross-modal adaptation, and multimodal reasoning enhancement.
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- #### 🖥️ Advanced Vision-Native GUI Agent Model
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  - [InfiGUIAgent](https://huggingface.co/papers/2501.04575): **InfiGUIAgent** is a GUI agent that embeds native hierarchical and expectation-reflection reasoning through a unique two-stage supervised pipeline, enabling robust, multi-step GUI task automation.
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  - [InfiGUI-R1](https://huggingface.co/InfiX-ai/InfiGUI-R1-3B): **InfiGUI-R1** is a GUI agent developed via the Actor2Reasoner framework, which evolves a reactive model into a deliberative reasoner capable of sophisticated planning and error recovery through spatial reasoning distillation and reinforcement learning.
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  - [InfiFPO](https://huggingface.co/InfiX-ai/InfiFPO-14B): **InfiFPO** is a lightweight fusion method during the preference alignment phase that injects fused model behavior into preference learning, enabling richer signal during DPO-style fine-tuning.
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+ #### 🧠 Reasoning-Enhanced Low-Resource Training Pipeline
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  - [InfiR](https://huggingface.co/papers/2502.11573): **InfiR** aims to advance AI systems by improving reasoning, reducing adoption barriers, and addressing privacy concerns through smaller model sizes.
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  - [InfiR-FP8](https://huggingface.co/InfiX-ai): **InfiR-FP8** is a smaller reasoning-enhanced model trained from scratch using FP8 precision, achieving successful convergence while reducing memory usage by 10% and improving training speed by 20% during the training process. The model will be released in mid-September.
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  - [InfiAlign](http://huggingface.co/collections/InfiX-ai/infialign-688600ca363ab9ef0b78f7a6): **InfiAlign** is a scalable and data-efficient post-training framework that combines supervised fine-tuning (SFT) and reinforcement learning (RL) with a high-quality data selection pipeline to enhance reasoning in large language models.
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  - [InfiMMR](https://arxiv.org/abs/2505.23091): **InfiMMR** is a novel three-phase curriculum framework that systematically enhances multimodal reasoning capabilities in small language models through foundational reasoning activation, cross-modal adaptation, and multimodal reasoning enhancement.
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+ #### 🖥️ Advanced Vision-Native Agent for GUI Interaction
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  - [InfiGUIAgent](https://huggingface.co/papers/2501.04575): **InfiGUIAgent** is a GUI agent that embeds native hierarchical and expectation-reflection reasoning through a unique two-stage supervised pipeline, enabling robust, multi-step GUI task automation.
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  - [InfiGUI-R1](https://huggingface.co/InfiX-ai/InfiGUI-R1-3B): **InfiGUI-R1** is a GUI agent developed via the Actor2Reasoner framework, which evolves a reactive model into a deliberative reasoner capable of sophisticated planning and error recovery through spatial reasoning distillation and reinforcement learning.
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