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Adam Pearce

2 accepted papers

2024

Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models

ICML 2024poster

Understanding the internal representations of large language models (LLMs) can help explain models' behavior and verify their alignment with human values. Given the capabilities of LLMs in generating human-understandable text, we propose leveraging the model itself to explain its internal representa…

Cited by 64SourcePDFScholar
2019

Visualizing and Measuring the Geometry of BERT

NeurIPS 2019poster

Transformer architectures show significant promise for natural language processing. Given that a single pretrained model can be fine-tuned to perform well on many different tasks, these networks appear to extract generally useful linguistic features. A natural question is how such networks represent…

Cited by 512SourcePDFScholar