#information-bottleneck2 articles

2 articles

AINeutralarXiv – CS AI · 2d ago6/10

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Mitigating Translationese Bias in Multilingual LLM-as-a-Judge via Disentangled Information Bottleneck

Researchers introduce DIBJudge, a new framework to address systematic bias in large language models that favor machine-translated text over human-authored content in multilingual evaluations. The solution uses variational information compression to isolate bias factors and improve LLM judgment accuracy across languages.

AINeutralLil'Log (Lilian Weng) · Sep 286/10

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Anatomize Deep Learning with Information Theory

Professor Naftali Tishby applied information theory to analyze deep neural network training, proposing the Information Bottleneck method as a new learning bound for DNNs. His research identified two distinct phases in DNN training: first representing input data to minimize generalization error, then compressing representations by forgetting irrelevant details.