iNLP-Lab/GlobeAudio
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Papers
What Should Agents Say? Action-state Communication for Efficient Multi-Agent Systems
Language of Thought Shapes Output Diversity in Large Language Models
iNLP-Lab/multilingual-safety
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iNLP-Lab/multilingual-s1
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iNLP-Lab/multilingual-lima
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iNLP-Lab/Moltbook-MoltNet
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iNLP-Lab/DDCF-Falcon3-10B-Base-1k-0.2-mmlu
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iNLP-Lab/DDCF-Qwen3-8B-Base-1k-0.2-mmlu
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iNLP-Lab/DDCF-Qwen2.5-7B-1k-0.2-mmlu
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iNLP-Lab/DDCF-binary-correctness-mmlu
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iNLP-Lab/DDCF-Qwen3-8B-Base-1k-0.2-math
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iNLP-Lab/DDCF-Qwen2.5-Math-7B-1k-0.2-math
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iNLP-Lab/DDCF-fullcorpus-math
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iNLP-Lab/DDCF-seed-math
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iNLP-Lab/DDCF-binary-correctness-math
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