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Yi Cui

onekq
KOUAMEFRANCK1978's profile picture drvishnu's profile picture cahdieng's profile picture
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https://onekq.ai

AI & ML interests

Benchmark, Code Generation Model

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posted an update about 8 hours ago
I am on the model layer and focus on atomic tasks, so I don't get involved in product discussions. But this provocative article provoked the community quite a bit. The case in point is Claude Code, which happens to be my biggest productivity revolution since ChatGPT. RAG predated TUI and agents. So to be fair it's quite an achievement to survive the AI evolution. But I feel it is overshadowed by context engineering in the agent era. How does everyone feel about this? https://www.nicolasbustamante.com/p/the-rag-obituary-killed-by-agents
posted an update 2 days ago
I tried to test the DeepSeek OCR model on a diagram-to-SQL task, i.e. visualize SQL schema to a E-R diagram, the combine the diagram with natural language question as prompt. The model outputs SQL query but unusable. The multimodality model (DeepSeek VL) performs better, but the good old coding LLM is far better. So this model is still, and meant to be, an OCR model. It does compress long context in a new way, but will have to be trained for other tasks will long context will be applied. OCR itself doesn't need long context. TLDR: lots of work will have to be done to make this main stream.
posted an update 4 days ago
I wrote this article to explain the difference between vision token and text token. They are apples and oranges, but also the source of compression efficiency of DeepSeek OCR (don't forget Glyph by THUDM!) https://huggingface.co/blog/onekq/behind-each-token I am running experiment with DeepSeek OCR BTW
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