Search Results for author:
Found 6 papers, 3 papers with code
Exploratory Model Analysis Using Data-Driven Neuron Representations
Probing classifiers have been extensively used to inspect whether a model component captures specific linguistic phenomena.
Tracing the Roots of Facts in Multilingual Language Models: Independent, Shared, and Transferred Knowledge
Acquiring factual knowledge for language models (LMs) in low-resource languages poses a serious challenge, thus resorting to cross-lingual transfer in multilingual LMs (ML-LMs).
PerPLM: Personalized Fine-tuning of Pretrained Language Models via Writer-specific Intermediate Learning and Prompts
The meanings of words and phrases depend not only on where they are used (contexts) but also on who use them (writers).
In-Contextual Gender Bias Suppression for Large Language Models
We show that, using CrowsPairs dataset, our textual preambles covering counterfactual statements can suppress gender biases in English LLMs such as LLaMA2.
Dynamic Data Augmentation with Gating Networks for Time Series Recognition
We propose a neural network that dynamically selects the best combination of data augmentation methods using a mutually beneficial gating network and a feature consistency loss.
Modeling Personal Biases in Language Use by Inducing Personalized Word Embeddings
In this study, we propose a method of modeling such personal biases in word meanings (hereafter, semantic variations) with personalized word embeddings obtained by solving a task on subjective text while regarding words used by different individuals as different words.
