Search Results for author:
Found 7 papers, 2 papers with code
Factual Confidence of LLMs: on Reliability and Robustness of Current Estimators
Our experiments across a series of LLMs indicate that trained hidden-state probes provide the most reliable confidence estimates, albeit at the expense of requiring access to weights and training data.
UniMorph 4.0: Universal Morphology
The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics
Measuring bias is key for better understanding and addressing unfairness in NLP/ML models.
Morphologically Aware Word-Level Translation
We propose a novel morphologically aware probability model for bilingual lexicon induction, which jointly models lexeme translation and inflectional morphology in a structured way.
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Systems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages.
Don't Forget the Long Tail! A Comprehensive Analysis of Morphological Generalization in Bilingual Lexicon Induction
Human translators routinely have to translate rare inflections of words - due to the Zipfian distribution of words in a language.
Words are Vectors, Dependencies are Matrices: Learning Word Embeddings from Dependency Graphs
Distributional Semantic Models (DSMs) construct vector representations of word meanings based on their contexts.
