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Marija Sakota

2 accepted papers

2025

Combining Constrained and Unconstrained Decoding via Boosting: BoostCD and Its Application to Information Extraction

EMNLP 2025

Many recent approaches to structured NLP tasks use an autoregressive language model M to map unstructured input text x to output text y representing structured objects (such as tuples, lists, trees, code, etc.), where the desired output structure is enforced via constrained decoding. During training

Cited by 0SourcePDFScholar
2023

Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

EMNLP 2023long main

Large language models (LLMs) have great potential for synthetic data generation. This work shows that useful data can be synthetically generated even for tasks that cannot be solved directly by LLMs: for problems with structured outputs, it is possible to prompt an LLM to perform the task in the rev…

Cited by 0SourcecodeScholar