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Unlocking Cognitive Capabilities and Analyzing the Perception-Logic Trade-off
arXiv – CS AI|Longyin Zhang, Shuo Sun, Yingxu He, Won Cheng Yi Lewis, Muhammad Huzaifah Bin Md Shahrin, Hardik Bhupendra Sailor, Heng Meng Jeremy Wong, Tarun Kumar Vangani, Yi Ma, Qiongqiong Wang, Minh Duc Pham, Ridong Jiang, Jingtao Li, Jingyi Liao, Zhuohan Liu, Yanfeng Lu, Manas Gupta, Ai Ti Aw||3 views
🤖AI Summary
Researchers introduce MERaLiON2-Omni (Alpha), a 10B-parameter multilingual AI model designed for Southeast Asia that combines perception and reasoning capabilities. The study reveals an efficiency-stability paradox where reasoning enhances abstract tasks but causes instability in basic sensory processing like audio timing and visual interpretation.
Key Takeaways
- →MERaLiON2-Omni is a 10B-parameter multimodal AI model specifically tailored for Southeast Asian languages and cultural contexts.
- →The model uses a progressive training pipeline that separates and then integrates perception and reasoning capabilities.
- →Researchers developed a cost-effective Generate-Judge-Refine pipeline to create high-quality training data without large-scale supervision.
- →The study identifies an efficiency-stability paradox where reasoning improves complex tasks but destabilizes low-level sensory processing.
- →Two key issues were discovered: temporal drift in audio processing and visual over-interpretation where logic overrides visual reality.
#multimodal-ai#large-language-models#southeast-asia#ai-research#perception-reasoning#training-pipeline#model-evaluation
Read Original →via arXiv – CS AI
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