LLaVA-OneVision-1.5 provides open datasets, code, and models that match or exceed closed competitors on 27 benchmarks at low cost through curated data and efficient training.
Fengshenbang 1.0: Being the foundation of chinese cognitive intelligence
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
baseline 1
citation-polarity summary
verdicts
UNVERDICTED 3representative citing papers
InternVL scales a vision model to 6B parameters and aligns it with LLMs using web data to achieve state-of-the-art results on 32 visual-linguistic benchmarks.
A survey on LLM-as-a-Judge that reviews reliability strategies, proposes evaluation methods, and introduces a novel benchmark for assessing such systems.
citing papers explorer
-
LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training
LLaVA-OneVision-1.5 provides open datasets, code, and models that match or exceed closed competitors on 27 benchmarks at low cost through curated data and efficient training.
-
InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
InternVL scales a vision model to 6B parameters and aligns it with LLMs using web data to achieve state-of-the-art results on 32 visual-linguistic benchmarks.
-
A Survey on LLM-as-a-Judge
A survey on LLM-as-a-Judge that reviews reliability strategies, proposes evaluation methods, and introduces a novel benchmark for assessing such systems.