Papers by Lawrence Cavedon
Evaluating Numeracy of Language Models as a Natural Language Inference Task (2025.findings-naacl)
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| Challenge: | Recent advances in large language models (LLMs) have enhanced their capabilities to solve mathematical problems, but other aspects of numeracy remain underexplored. |
| Approach: | They propose to frame numeracy as a Natural Language Inference task to assess the models’ ability to understand both numbers and language contexts. |
| Outcome: | The proposed model outperforms smaller models in arithmetic tasks, indicating that mathematical reasoning cannot be generalized to other numeracy skills such as number comparison and normalization. |
RADS: Reinforcement Learning-Based Sample Selection Improves Transfer Learning in Low-resource and Imbalanced Clinical Settings (2026.findings-acl)
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| Challenge: | Experimental evaluations show that RL methods favor outliers rather than truly informative samples under low-resource and class-imbalanced conditions. |
| Approach: | They propose a robust sample selection strategy using reinforcement learning to identify the most informative samples using a class imbalance approach. |
| Outcome: | The proposed strategy improves model transferability while maintaining robust performance under extreme class imbalance compared to traditional methods. |