Papers by Cristian Calderon
Deep Natural Language Feature Learning for Interpretable Prediction (2023.emnlp-main)
Copied to clipboard
| Challenge: | Using a small transformer language model, we can break down a complex task into a set of intermediary easier sub-tasks. |
| Approach: | They propose a method to break down a main task into a set of intermediary easier sub-tasks, which are formulated in natural language as binary questions related to the final target task. |
| Outcome: | The proposed method breaks down a complex task into a set of easier sub-tasks, which are formulated in natural language as binary questions related to the final target task. |
Large Language Models are biased to overestimate profoundness (2023.emnlp-main)
Copied to clipboard
| Challenge: | Recent advances in natural language processing have been suggested to approach AI . however, it is still unclear whether LLMs possess similar reasoning abilities to humans . |
| Approach: | They evaluate GPT-4 and other LLMs in judging the profoundness of mundane statements . they find a significant correlation between the LLM and humans . |
| Outcome: | The proposed model overestimates the profoundness of nonsensical statements . the model overstates the profound nature of non-senior statements, the study finds . |