Papers by Ashish Kulkarni
MATHSENSEI: A Tool-Augmented Large Language Model for Mathematical Reasoning (2024.naacl-long)
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| Challenge: | TALMs have been successfully employed in question-answering benchmarks, but their efficacy on complex mathematical reasoning benchmarks are open research questions. |
| Approach: | They propose a tool-augmented large language model for mathematical reasoning that enhances the skillset of large language models (LLMs) by 13.5%. |
| Outcome: | The proposed model achieves better accuracy and better knowledge retrieval performance than existing tools. |
MUTANT: A Recipe for Multilingual Tokenizer Design (2026.acl-long)
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| Challenge: | Subword tokenization schemes such as Byte Pair Encoding (BPE) are widely adopted, but their effectiveness in multilingual settings remains understudied. |
| Approach: | They propose a multilingual tokenizer that produces linguistically coherent tokens for multilingual LLMs. |
| Outcome: | The proposed tokenizer improves fertility score by 39.5% over LLaMA4 and 18% over Sutra. |