activity
20212026
most citedQueer In AI: A Case Study in Community-Led Participatory AI

65 citations · 123 across the 21 of their papers we have counts for

collaborators

21 papers

cs.AI2026

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…

cs.AI2026

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…

cs.CL2026

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…

cs.AI2026

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…

cs.AI2026

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…

cs.CL2026

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…