I mapped Anthropic’s J-Space Hallucination signal across 7 datasets on Qwen3-4B to find out where it works and where it breaks
英文标题:I mapped Anthropic’s J-Space Hallucination signal across 7 datasets on Qwen3-4B to find out where it works and where it breaks
Anthropic recently published their paper on "Global Workspaces" (J-Space) inside language models, showing that looking at internal "workspace noise" (entropy) can catch hallucinations better than just looking at output logprobs. `solarkyle` followed up with a great open-source implementation showing
中文
Anthropic recently published their paper on "Global Workspaces" (J-Space) inside language models, showing that looking at internal "workspace noise" (entropy) can catch hallucinations better than just looking at output logprobs. `solarkyle` followed up with a great open-source implementation showing
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English / 原文
Anthropic recently published their paper on "Global Workspaces" (J-Space) inside language models, showing that looking at internal "workspace noise" (entropy) can catch hallucinations better than just looking at output logprobs. `solarkyle` followed up with a great open-source implementation showing