Multimodal models with leading performance.
AI & ML interests
Large Language Models
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Papers
InfLLM-V2: Dense-Sparse Switchable Attention for Seamless Short-to-Long Adaptation
MiniCPM4: Ultra-Efficient LLMs on End Devices
The MiniCPM family of LLMs and VLLMs.
The collection of open-source models that adopt Ultra Series datasets for training
CPM-Bee series models.
Parsing-free RAG supported by VLMs
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VisRAG 2.0: Evidence-Guided Multi-Image Reasoning in Visual Retrieval-Augmented Generation
Paper • 2510.09733 • Published • 4 -
VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents
Paper • 2410.10594 • Published • 28 -
Boggy666/EVisRAG-7B
8B • Updated • 344 • 2 -
hmhm1229/EVisRAG-Train
Viewer • Updated • 500 • 144 • 2
Multimodal models with leading performance.
MiniCPM4: Ultra-Efficient LLMs on End Devices
The MiniCPM family of LLMs and VLLMs.
Extrapolating RLVR to General Domains without Verifiers
The collection of open-source models that adopt Ultra Series datasets for training
UltraLM, UltraRM and UltraCM.
CPM-Bee series models.
Advancing LLM Reasoning Generalists with Preference Trees
Parsing-free RAG supported by VLMs
-
VisRAG 2.0: Evidence-Guided Multi-Image Reasoning in Visual Retrieval-Augmented Generation
Paper • 2510.09733 • Published • 4 -
VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents
Paper • 2410.10594 • Published • 28 -
Boggy666/EVisRAG-7B
8B • Updated • 344 • 2 -
hmhm1229/EVisRAG-Train
Viewer • Updated • 500 • 144 • 2
Embedding, re-ranking, generation -- the cornerstone of RAG.