Papers by Asma Ghandeharioun
Racing Thoughts: Explaining Contextualization Errors in Large Language Models (2025.naacl-long)
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| Challenge: | Large Language Models have demonstrated a remarkable capacity for accomplishing a wide variety of language generation and classification tasks. |
| Approach: | They propose a race conditions hypothesis to explain contextualization errors . they propose to use a variety of techniques to test the hypothesis . |
| Outcome: | The proposed model fails to properly contextualize a financial institution if it does not include a bank . the proposed model is based on the race conditions hypothesis . |
Human-centric dialog training via offline reinforcement learning (2020.emnlp-main)
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Natasha Jaques, Judy Hanwen Shen, Asma Ghandeharioun, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Gu, Rosalind Picard
| Challenge: | a novel offline RL method can train dialog models to produce better conversations without the risk of humans teaching it harmful chat behaviors. |
| Approach: | They develop offline reinforcement learning algorithms that use human feedback to train dialog models . they use language similarity, laughter, sentiment, and more to identify positive feedback . |
| Outcome: | The proposed method improves on existing methods with 80 users in an open-domain setting. |