Papers with self-attention based LLMs
Do Robot Snakes Dream like Electric Sheep? Investigating the Effects of Architectural Inductive Biases on Hallucination (2025.findings-acl)
Copied to clipboard
| Challenge: | Large language models (LLMs) have a tendency to hallucinate false or misleading information, limiting their reliability. |
| Approach: | They examine how architecture-based inductive biases affect the propensity to hallucinate . they find that the models are more reliable and more reliable than traditional models . |
| Outcome: | The proposed models can be used to train and train large language models that are factual or able to explain themselves through their knowledge. |