Zobrazeno 1 - 10
of 64
pro vyhledávání: '"KhudaBukhsh, Ashiqur R."'
Autor:
Pandita, Deepak, Weerasooriya, Tharindu Cyril, Dutta, Sujan, Luger, Sarah K., Ranasinghe, Tharindu, KhudaBukhsh, Ashiqur R., Zampieri, Marcos, Homan, Christopher M.
Human feedback is essential for building human-centered AI systems across domains where disagreement is prevalent, such as AI safety, content moderation, or sentiment analysis. Many disagreements, particularly in politically charged settings, arise b
Externí odkaz:
http://arxiv.org/abs/2408.08411
A community needs assessment is a tool used by non-profits and government agencies to quantify the strengths and issues of a community, allowing them to allocate their resources better. Such approaches are transitioning towards leveraging social medi
Externí odkaz:
http://arxiv.org/abs/2403.13272
Current research concentrates on studying discussions on social media related to structural failures to improve disaster response strategies. However, detecting social web posts discussing concerns about anticipatory failures is under-explored. If su
Externí odkaz:
http://arxiv.org/abs/2402.13528
This paper makes three contributions. First, it presents a generalizable, novel framework dubbed \textit{toxicity rabbit hole} that iteratively elicits toxic content from a wide suite of large language models. Spanning a set of 1,266 identity groups,
Externí odkaz:
http://arxiv.org/abs/2309.06415
Autor:
Yoo, Clay H., KhudaBukhsh, Ashiqur R.
This paper makes two key contributions. First, it argues that highly specialized rare content classifiers trained on small data typically have limited exposure to the richness and topical diversity of the negative class (dubbed anticontent) as observ
Externí odkaz:
http://arxiv.org/abs/2310.07078
Divorce is the legal dissolution of a marriage by a court. Since this is usually an unpleasant outcome of a marital union, each party may have reasons to call the decision to quit which is generally documented in detail in the court proceedings. Via
Externí odkaz:
http://arxiv.org/abs/2307.10200
Autor:
Weerasooriya, Tharindu Cyril, Luger, Sarah, Poddar, Saloni, KhudaBukhsh, Ashiqur R., Homan, Christopher M.
Human-annotated data plays a critical role in the fairness of AI systems, including those that deal with life-altering decisions or moderating human-created web/social media content. Conventionally, annotator disagreements are resolved before any lea
Externí odkaz:
http://arxiv.org/abs/2307.10189
In this paper, we present a computational analysis of the Persian language Twitter discourse with the aim to estimate the shift in stance toward gender equality following the death of Mahsa Amini in police custody. We present an ensemble active learn
Externí odkaz:
http://arxiv.org/abs/2307.03764
Autor:
Weerasooriya, Tharindu Cyril, Dutta, Sujan, Ranasinghe, Tharindu, Zampieri, Marcos, Homan, Christopher M., KhudaBukhsh, Ashiqur R.
Offensive speech detection is a key component of content moderation. However, what is offensive can be highly subjective. This paper investigates how machine and human moderators disagree on what is offensive when it comes to real-world social web po
Externí odkaz:
http://arxiv.org/abs/2301.12534
Autor:
Chen, Keyu, Shi, Yiwen, Luo, Jun, Jiang, Joyce, Yadav, Shweta, De Choudhury, Munmun, KhudaBukhsh, Ashiqur R., Babaeianjelodar, Marzieh, Altice, Frederick, Kumar, Navin
We analyze 1,888 articles and 1,119,453 vaping posts to study how vaping is framed across multiple knowledge dissemination platforms (Wikipedia, Quora, Medium, Reddit, Stack Exchange, wikiHow). We use various NLP techniques to understand these differ
Externí odkaz:
http://arxiv.org/abs/2206.10594