65 citations · 123 across the 21 of their papers we have counts for
21 papers
Towards participatory speech dataset curation: A queer case study and conceptual framework
Brooklyn Sheppard, Anaelia Ovalle, Adina Williams +1
In this paper, we motivate the need for a participatory speech dataset creation framework through a case study of the LGBTQIA+, or queer, community - a community with documented co…
Queer inclusion in speech datasets: An audit and taxonomy of practical tensions
Brooklyn Sheppard, Anaelia Ovalle, Adina Williams +1
In this paper, we examine speech datasets for their inclusion of LGBTQIA+, or queer, voices and provide a taxonomy of tensions to better understand why there is a lack of such voic…
From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop
Rahul Gupta, Abhinav Mohanty, Anaelia Ovalle +10
The Workshop on Trustworthy Natural Language Processing (TrustNLP), co-located with major ACL conferences since 2021, has grown from 8 proceedings papers to 41 over six editions, d…
SCRuB: Social Concept Reasoning under Rubric-Based Evaluation
Jamelle Watson-Daniels, Himaghna Bhattacharjee, Skyler Wang +11
While many studies of Large Language Model (LLM) reasoning capabilities emphasize mathematical or technical tasks, few address reasoning about social concepts: the abstract ideas s…
Reasoning over mathematical objects: on-policy reward modeling and test time aggregation
Pranjal Aggarwal, Marjan Ghazvininejad, Seungone Kim +18
The ability to precisely derive mathematical objects is a core requirement for downstream STEM applications, including mathematics, physics, and chemistry, where reasoning must cul…
Can Large Language Models Understand, Reason About, and Generate Code-Switched Text?
Genta Indra Winata, David Anugraha, Patrick Amadeus Irawan +15
Code-switching is a pervasive phenomenon in multilingual communication, yet the robustness of large language models (LLMs) in mixed-language settings remains insufficiently underst…
Beg to Differ: Understanding Reasoning-Answer Misalignment Across Languages
Anaelia Ovalle, Candace Ross, Sebastian Ruder +4
Large language models demonstrate strong reasoning capabilities through chain-of-thought prompting, but whether this reasoning quality transfers across languages remains underexplo…
The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation
Martin Mundt, Anaelia Ovalle, Felix Friedrich +5
In a widely popular analogy by Turing Award Laureate Yann LeCun, machine intelligence has been compared to cake - where unsupervised learning forms the base, supervised learning ad…
The Root Shapes the Fruit: On the Persistence of Gender-Exclusive Harms in Aligned Language Models
Anaelia Ovalle, Krunoslav Lehman Pavasovic, Louis Martin +5
Natural-language assistants are designed to provide users with helpful responses while avoiding harmful outputs, largely achieved through alignment to human preferences. Yet there…
Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation
Yixin Wan, Arjun Subramonian, Anaelia Ovalle +6
The recent advancement of large and powerful models with Text-to-Image (T2I) generation abilities -- such as OpenAI's DALLE-3 and Google's Gemini -- enables users to generate high-…
Tokenization Matters: Navigating Data-Scarce Tokenization for Gender Inclusive Language Technologies
Anaelia Ovalle, Ninareh Mehrabi, Palash Goyal +6
Gender-inclusive NLP research has documented the harmful limitations of gender binary-centric large language models (LLM), such as the inability to correctly use gender-diverse Eng…
Decoding The Digital Fuku: Deciphering Colonial Legacies to Critically Assess ChatGPT in Dominican Education
Anaelia Ovalle
Educational disparities within the Dominican Republic (DR) have long-standing origins rooted in economic, political, and social inequity. Addressing these challenges has necessaril…
Should they? Mobile Biometrics and Technopolicy meet Queer Community Considerations
Anaelia Ovalle, Davi Liang, Alicia Boyd
Smartphones are integral to our daily lives and activities, providing us with basic functions like texting and phone calls to more complex motion-based functionalities like navigat…
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms
Organizers of QueerInAI, Nathan Dennler, Anaelia Ovalle +11
Bias evaluation benchmarks and dataset and model documentation have emerged as central processes for assessing the biases and harms of artificial intelligence (AI) systems. However…
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation
Anaelia Ovalle, Palash Goyal, Jwala Dhamala +5
Transgender and non-binary (TGNB) individuals disproportionately experience discrimination and exclusion from daily life. Given the recent popularity and adoption of language gener…
ChatGPT for Us: Preserving Data Privacy in ChatGPT via Dialogue Text Ambiguation to Expand Mental Health Care Delivery
Anaelia Ovalle, Mehrab Beikzadeh, Parshan Teimouri +2
Large language models have been useful in expanding mental health care delivery. ChatGPT, in particular, has gained popularity for its ability to generate human-like dialogue. Howe…
Queer In AI: A Case Study in Community-Led Participatory AI
Organizers Of QueerInAI, :, Anaelia Ovalle +48
We present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community…
Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN
Anaelia Ovalle, Sunipa Dev, Jieyu Zhao +2
Auditing machine learning-based (ML) healthcare tools for bias is critical to preventing patient harm, especially in communities that disproportionately face health inequities. Gen…
Improving Adversarial Robustness to Sensitivity and Invariance Attacks with Deep Metric Learning
Anaelia Ovalle, Evan Czyzycki, Cho-Jui Hsieh
Intentionally crafted adversarial samples have effectively exploited weaknesses in deep neural networks. A standard method in adversarial robustness assumes a framework to defend a…
Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies
Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle +3
Gender is widely discussed in the context of language tasks and when examining the stereotypes propagated by language models. However, current discussions primarily treat gender as…
COVID-19 and Big Data: Multi-faceted Analysis for Spatio-temporal Understanding of the Pandemic with Social Media Conversations
Shayan Fazeli, Davina Zamanzadeh, Anaelia Ovalle +3
COVID-19 has been devastating the world since the end of 2019 and has continued to play a significant role in major national and worldwide events, and consequently, the news. In it…