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Winston Wu

11 accepted papers

2024

Analyzing Occupational Distribution Representation in Japanese Language Models

COLING 2024main

Recent advances in large language models (LLMs) have enabled users to generate fluent and seemingly convincing text. However, these models have uneven performance in different languages, which is also associated with undesirable societal biases toward marginalized populations. Specifically, there is…

Cited by 1SourcePDFScholar
2024

Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models

COLING 2024main

Recent progress in large language models (LLMs) has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse that “it’s all been solved.” Not surprisingly, this has, in turn, made many NLP researchers – especially those at the beg…

Cited by 9SourcePDFScholar
2024

MOKA: Moral Knowledge Augmentation for Moral Event Extraction

NAACL 2024long

News media often strive to minimize explicit moral language in news articles, yet most articles are dense with moral values as expressed through the reported events themselves. However, values that are reflected in the intricate dynamics among *participating entities* and *moral events* are far more…

2023

Crossing the Aisle: Unveiling Partisan and Counter-Partisan Events in News Reporting

EMNLP 2023short findings

News media is expected to uphold unbiased reporting. Yet they may still affect public opinion by selectively including or omitting events that support or contradict their ideological positions. Prior work in NLP has only studied media bias via linguistic style and word usage. In this paper, we s…

Cited by 0SourcecodeScholar
2023

You Are What You Annotate: Towards Better Models through Annotator Representations

EMNLP 2023long findings

Annotator disagreement is ubiquitous in natural language processing (NLP) tasks. There are multiple reasons for such disagreements, including the subjectivity of the task, difficult cases, unclear guidelines, and so on. Rather than simply aggregating labels to obtain data annotations, we instead try…

Cited by 0SourcecodeScholar
2022

Deciphering and Characterizing Out-of-Vocabulary Words for Morphologically Rich Languages

COLING 2022main

This paper presents a detailed foundational empirical case study of the nature of out-of-vocabulary words encountered in modern text in a moderate-resource language such as Bulgarian, and a multi-faceted distributional analysis of the underlying word-formation processes that can aid in their composi…

2022

Late Fusion with Triplet Margin Objective for Multimodal Ideology Prediction and Analysis

EMNLP 2022main

Prior work on ideology prediction has largely focused on single modalities, i.e., text or images. In this work, we introduce the task of multimodal ideology prediction, where a model predicts binary or five-point scale ideological leanings, given a text-image pair with political content. We first co…

2020

Neural Transduction for Multilingual Lexical Translation

COLING 2020main

We present a method for completing multilingual translation dictionaries. Our probabilistic approach can synthesize new word forms, allowing it to operate in settings where correct translations have not been observed in text (cf. cross-lingual embeddings). In addition, we propose an approximate Maxi…

Cited by 7SourcePDFScholar