Papers by Sky CH-Wang
Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York City (2023.emnlp-main)
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| Challenge: | Critical toponymy studies the dynamics of power, capital, and resistance through place names and the sites to which they refer. |
| Approach: | They propose a model that measures how cultural and economic capital shape the ways in which people refer to places through an annotated dataset of Airbnb listings in New York City. |
| Outcome: | The proposed model can identify important discourse categories integral to the characterization of place. |
Do Androids Know They’re Only Dreaming of Electric Sheep? (2024.findings-acl)
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| Challenge: | Detecting hallucinations in grounded generation tasks is commonly framed as a textual entailment problem. |
| Approach: | They develop probes that are narrowly trained to predict hallucination in a transformer language model. |
| Outcome: | The probes can detect hallucinations at many transformer layers outperforming baselines and human annotators on two out of three generation tasks. |
NormDial: A Comparable Bilingual Synthetic Dialog Dataset for Modeling Social Norm Adherence and Violation (2023.emnlp-main)
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| Challenge: | Social norms fundamentally shape interpersonal communication. |
| Approach: | They propose a human-in-the-loop pipeline to synthesize a bilingual dyadic dialogue dataset with turn-by-turn annotations of social norms for Chinese and American cultures. |
| Outcome: | The proposed dataset is high-quality through human evaluation and compares with existing models. |
Sociocultural Norm Similarities and Differences via Situational Alignment and Explainable Textual Entailment (2023.emnlp-main)
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| Challenge: | Current research on developing computational models of social norms has focused on American society. |
| Approach: | They propose to leverage a Chinese Q&A platform and a socialchiemistry dataset as proxies for contrasting cultural axes and align social situations cross-culturally. |
| Outcome: | The proposed model can reason across cultures using a Chinese Q&A platform and the existing socialChemistry dataset. |
Affective Idiosyncratic Responses to Music (2022.emnlp-main)
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| Challenge: | Affective responses to music are highly personal, but it's difficult to measure marginal effects of these variables . a study of 403M listener comments on a social music platform in china aims to address this gap . |
| Approach: | They propose to measure affective responses to music from 403M listener comments on a Chinese social music platform. |
| Outcome: | The proposed method identifies musical, lyrical, contextual, demographic, and mental health effects that drive listener affective responses from over 403M listener comments on a Chinese social music platform. |
Using Sociolinguistic Variables to Reveal Changing Attitudes Towards Sexuality and Gender (2021.emnlp-main)
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| Challenge: | Existing studies show that word choice is driven by demographics within the United States. |
| Approach: | They develop computational methods to study word choice within a sociolinguistic lexical variable . they use two variables to test for attitudes towards sexuality and gender in the u.s. |
| Outcome: | The proposed methods allow us to examine attitudes towards sexuality and gender in the United States through two lexical variables. |
MindCraft: Theory of Mind Modeling for Situated Dialogue in Collaborative Tasks (2021.emnlp-main)
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| Challenge: | Creating embodied, situated agents able to move in, communicate naturally about, and collaborate on human terms in the physical world has been a persisting goal in artificial intelligence (Winograd, 1972). |
| Approach: | They propose to use a 3D Minecraft dataset to model the beliefs of human partners in situ to enable theory of mind modeling in situated interactions. |
| Outcome: | The proposed model can be used to model human collaborative behaviors in the 3D virtual blocks world of Minecraft. |
Browsing Lost Unformed Recollections: A Benchmark for Tip-of-the-Tongue Search and Reasoning (2025.acl-long)
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| Challenge: | BLUR is a tip-of-the-tongue known-item search and reasoning benchmark for general AI assistants. |
| Approach: | They introduce a tip-of-the-tongue known-item search and reasoning benchmark for general AI assistants. |
| Outcome: | The proposed benchmark demands searching and reasoning across multimodal and multilingual inputs, as well as proficient tool use, in order to excel on. |