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Merchant matching resolves a noisy payment descriptor to a retrieved merchant entity or returns no match. A key challenge in curating training labels is distinguishing teacher abstention from evidence that no acceptable entity exists: false no-match labels contaminate pseudo-labeled data, while conservative labeling re...
The role of commonsense reasoning in LLMs is discussed, how they strive to emulate human-like reasoning, and why they often struggle to capture the nuanced inferences associated with commonsense understanding of the physical and social world.
The results show that compact fine-tuned models can preserve most extraction accuracy, but model selection must account for prompt choice, throughput, and serving-stack behavior.
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