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Found 6 papers, 2 papers with code
Assessment of Pre-Trained Models Across Languages and Grammars
We present an approach for assessing how multilingual large language models (LLMs) learn syntax in terms of multi-formalism syntactic structures.
Contrasting Linguistic Patterns in Human and LLM-Generated Text
We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from 4 LLMs from the LLaMa family.
Another Dead End for Morphological Tags? Perturbed Inputs and Parsing
The usefulness of part-of-speech tags for parsing has been heavily questioned due to the success of word-contextualized parsers.
Parsing linearizations appreciate PoS tags - but some are fussy about errors
PoS tags, once taken for granted as a useful resource for syntactic parsing, have become more situational with the popularization of deep learning.
Cross-lingual Inflection as a Data Augmentation Method for Parsing
We propose a morphology-based method for low-resource (LR) dependency parsing.
Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsing
Different linearizations have been proposed to cast dependency parsing as sequence labeling and solve the task as: (i) a head selection problem, (ii) finding a representation of the token arcs as bracket strings, or (iii) associating partial transition sequences of a transition-based parser to words.
