LITA uses seed-initialized clustering and selectively asks an LLM to reclassify only ambiguous documents, reducing API calls by over 80 percent while matching or beating full-prompt baselines.
In: Proceedings of the ACM Web Conference 2022
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
LITA: An Efficient LLM-assisted Iterative Topic Augmentation Framework
LITA uses seed-initialized clustering and selectively asks an LLM to reclassify only ambiguous documents, reducing API calls by over 80 percent while matching or beating full-prompt baselines.