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Towards Multi-dimensional Explanation Alignment for Medical Classification
The lack of interpretability in the field of medical image analysis has significant ethical and
legal implications. Existing interpretable methods in this domain encounter several …
legal implications. Existing interpretable methods in this domain encounter several …
Steering language model refusal with sparse autoencoders
K O'Brien, D Majercak, X Fernandes, R Edgar… - arxiv preprint arxiv …, 2024 - arxiv.org
Responsible practices for deploying language models include guiding models to recognize
and refuse answering prompts that are considered unsafe, while complying with safe …
and refuse answering prompts that are considered unsafe, while complying with safe …
Mqa-keal: Multi-hop question answering under knowledge editing for arabic language
Large Language Models (LLMs) have demonstrated significant capabilities across
numerous application domains. A key challenge is to keep these models updated with latest …
numerous application domains. A key challenge is to keep these models updated with latest …
Mechanistic Unveiling of Transformer Circuits: Self-Influence as a Key to Model Reasoning
Transformer-based language models have achieved notable success, yet their internal
reasoning mechanisms remain largely opaque due to complex non-linear interactions and …
reasoning mechanisms remain largely opaque due to complex non-linear interactions and …
EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification
Understanding the internal mechanisms of transformer-based language models remains
challenging. Mechanistic interpretability based on circuit discovery aims to reverse engineer …
challenging. Mechanistic interpretability based on circuit discovery aims to reverse engineer …