Papers by Nadia Polikarpova
Solving Data-centric Tasks using Large Language Models (2024.findings-naacl)
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Shraddha Barke, Christian Poelitz, Carina Negreanu, Benjamin Zorn, José Cambronero, Andrew Gordon, Vu Le, Elnaz Nouri, Nadia Polikarpova, Advait Sarkar, Brian Slininger, Neil Toronto, Jack Williams
| Challenge: | Large language models are increasingly useful for data-centric tasks, but how do we decide how much data to include in the prompt? |
| Approach: | They propose a cluster-then-select prompting technique that adds the most representative rows from the input data to the LLM prompt. |
| Outcome: | The proposed technique outperforms a baseline for tasks with syntactic variation in the input table. |
Constraint-based Learning of Phonological Processes (D19-1)
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| Challenge: | Phonological processes govern the way speech sounds in natural languages change depending on context . a novel approach to learning phonological processes from related utterances is proposed . |
| Approach: | They propose an unsupervised approach to learning phonological processes from related utterances . they encode the problem into Boolean constraints that enable data efficiency and fast inference . |
| Outcome: | The proposed approach achieves high accuracy at interactive speeds on phonology problems and datasets. |