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This raises critical questions about agency: who drives conversations and sets boundaries in human-AI chatrooms
from the top result below
https://huggingface.co/papers?q=companion
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https://huggingface.co/datasets/microsoft/benchpress-score-matrix
\", \"range\": [0, 100], \"sampling\": \"pass@1; public harness default maxTurns=20\", \"tools\": \"agentic MCP servers in the official containerized harness\", \"version\": \"MCP-Atlas public 500-task HuggingFace release\"}"},"in_paper_matrix":{"kind":"bool","value":true,"string":"true"}}},{"rowIdx":9,"cells":
https://huggingface.co/MiniMaxAI/MiniMax-H3
Thanks to its task-generalization-oriented system design, H3 already possesses broad multimodal context understanding and generation capabilities at the pre-training stage, enabling outstanding performance in following complex multimodal instructions
https://huggingface.co/papers?q=reflective%20essays
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