I am a Computer Science sophomore deeply focused on Machine Learning, Large Language Models (LLMs), and Recommender Systems.
- LLMs & Alignment: Post-Training, Reinforcement Learning, NLP, and Machine Translation.
- Recommender Systems: Graph Neural Networks (GNN), Denoising, and Contrastive Learning (e.g., InfoNCE).
- Exploring: AI for Science (AI4S), Embodied AI (Robotics), and Speech Technologies.
- Deep Learning: PyTorch
- LLM Training: Unsloth, verl, LLaMA-Factory
- Inference & Optimization: vLLM, SGLang, OpenAI Triton
- Murasaki-project: An ACGN translation model with native CoT and Long Context support. Achieving SOTA performance in the ACGN translation and localization domain.
- [Ongoing Research]: Currently working on specific research problems in LLM Machine Translation, Math Reasoning, and Recommender Systems.
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