Summary of Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models, by Javier Ferrando et al.
Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models
by Javier Ferrando, Oscar Obeso, Senthooran Rajamanoharan, Neel Nanda
First submitted to arxiv on: 21 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores the mechanisms behind hallucinations in large language models. Researchers use sparse autoencoders as a tool for interpretability and discover that entity recognition plays a key role. The model detects if it can recall facts about an entity, suggesting self-knowledge and internal representations about its own capabilities. These directions are causally relevant, influencing the model’s refusal behavior and hallucination patterns. The study demonstrates that chat finetuning has repurposed this existing mechanism, and provides initial insights into the mechanistic role of these directions in disrupting attentional processes. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at why big language models sometimes make things up. They use a special tool to understand how the model works and find that it’s connected to recognizing what they know about certain things. This means the model has some self-awareness, knowing what it can and can’t do. The study shows that this affects how the model answers questions or makes things up when it doesn’t know. It also looks at how this affects how the model pays attention to information. |
Keywords
» Artificial intelligence » Attention » Hallucination » Recall
