Papers with numerical reasoning capabilities
LLMs Know More About Numbers than They Can Say (2026.eacl-short)
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| Challenge: | Large language models (LLMs) are increasingly used in mathematical, scientific, financial and engineering domains. |
| Approach: | They probe the hidden states of several smaller open-source LLMs to find out how big they are . |
| Outcome: | The proposed model improves verbalized accuracy by 3.22% over base models. |
Exploiting Numerical-Contextual Knowledge to Improve Numerical Reasoning in Question Answering (2022.findings-naacl)
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| Challenge: | Existing numerical reasoning models overly rely on parametric knowledge at inference time . previous studies show that understanding numbers in text improves numerical reasoning accuracy . |
| Approach: | They propose a numerical reasoning model that leverages parametric knowledge to alleviate this over-reliance on parametric information. |
| Outcome: | The proposed model improves numerical reasoning accuracy and performance in DROP. |
Do NLP Models Know Numbers? Probing Numeracy in Embeddings (D19-1)
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| Challenge: | Existing models cannot capture numeracy, but they can be useful for complex reasoning tasks. |
| Approach: | They investigate numerical reasoning capabilities of a question-answering model . they probe token embedding methods on synthetic list maximum, number decoding, and addition tasks. |
| Outcome: | The proposed model excels on questions that require numerical reasoning, i.e., it already captures numeracy. |