Papers by Robert D. Hawkins
Evaluating distillation methods for data-efficient syntax learning (2025.findings-emnlp)
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| Challenge: | knowledge distillation (KD) targeting attention should selectively accelerate syntax acquisition, a study finds . logit-based KD dramatically improves data-efficiency, attention-based one provides minimal benefit even for syntactic tasks. |
| Approach: | a study predicts that knowledge distillation targeting attention should selectively accelerate syntax acquisition . a systolic analysis of student models compared to logit-based knowledge distillations . |
| Outcome: | a new study shows that knowledge distillation (KD) targeting attention accelerates syntax acquisition . the hypothesis is tested on syntactic benchmarks and perplexity. |
Comparing human and LLM politeness strategies in free production (2025.emnlp-main)
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| Challenge: | Polite speech poses a fundamental alignment challenge for large language models (LLMs). |
| Approach: | They compare human and LLM responses to English-language scenarios to determine whether they employ a similarly context-sensitive repertoire. |
| Outcome: | The results show that large models replicate key effects from the computational pragmatics literature and human evaluators prefer LLM-generated responses in open-ended contexts. |
Accommodation and Epistemic Vigilance: A Pragmatic Account of Why LLMs Fail to Challenge Harmful Beliefs (2026.acl-long)
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| Challenge: | Recent studies show that large language models fail to challenge users’ harmful beliefs in domains ranging from medical advice to social reasoning. |
| Approach: | They propose to examine whether pragmatic factors influence LLM accommodation and epistemic vigilance in humans. |
| Outcome: | The proposed model can be understood and addressed as having excessive accommodation and insufficient epistemic vigilance. |
When More Words Say Less: Decoupling Length and Specificity in Image Description Evaluation (2026.acl-short)
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| Challenge: | Vision-language models are increasingly used to produce textual descriptions of visual content. |
| Approach: | They propose to disentangle description specificity from description length . they find people prefer more specific descriptions regardless of length based on their own subjective preferences . |
| Outcome: | The proposed model shows that people prefer more specific descriptions regardless of length. |