Papers by Jared Moore
Language Models Understand Us, Poorly (2022.findings-emnlp)
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| Challenge: | Recent large language models have achieved impressive results on benchmark tasks. |
| Approach: | They examine three views of human language understanding: as-mapping, as-reliability and as-representation. |
| Outcome: | The authors argue that language models are inadequate and that they can't understand us . they also argue that as-representation advances a science of understanding . |
Are Large Language Models Consistent over Value-laden Questions? (2024.findings-emnlp)
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| Challenge: | Large language models (LLMs) appear to bias survey answers toward certain values . however, some argue that LLMs are inconsistent to simulate particular values - a recent study . |
| Approach: | They define value consistency as similarity of answers across paraphrases, related questions and multilingual translations of a question to English, Chinese, German, and Japanese. |
| Outcome: | The proposed model is consistent across paraphrases, use-cases, translations, and within a topic. |
I am a Strange Dataset: Metalinguistic Tests for Language Models (2024.acl-long)
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| Challenge: | Existing datasets for metalinguistic self-reference are limited by the number of subtasks. |
| Approach: | They propose a dataset that aims to address metalinguistic self-reference in large language models. |
| Outcome: | The proposed dataset is hand-crafted by experts and validated by non-expert annotators. |