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Shachi Dave

7 accepted papers

2026

CURVE: A Benchmark for Cultural and Multilingual Long Video Reasoning

CVPR 2026

Recent advancements in video models have shown tremendous progress, particularly in long video understanding. However, current benchmarks predominantly feature western-centric data and English as the dominant language, introducing significant biases in evaluation. To address this, we introduce CURVE

Cited by 0SourceScholar
2024

Beyond Aesthetics: Cultural Competence in Text-to-Image Models

NeurIPS 2024poster

Text-to-Image (T2I) models are being increasingly adopted in diverse global communities where they create visual representations of their unique cultures. Current T2I benchmarks primarily focus on faithfulness, aesthetics, and realism of generated images, overlooking the critical dimension of *cultu…

Cited by 10SourcePDFScholar
2024

SeeGULL Multilingual: a Dataset of Geo-Culturally Situated Stereotypes

ACL 2024short

While generative multilingual models are rapidly being deployed, their safety and fairness evaluations are largely limited to resources collected in English. This is especially problematic for evaluations targeting inherently socio-cultural phenomena such as stereotyping, where it is important to bu…

2024

ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation

ACL 2024long

Recent studies have shown that Text-to-Image (T2I) model generations can reflect social stereotypes present in the real world. However, existing approaches for evaluating stereotypes have a noticeable lack of coverage of global identity groups and their associated stereotypes. To address this gap, w…

2023

Building Socio-culturally Inclusive Stereotype Resources with Community Engagement

NeurIPS 2023poster

With rapid development and deployment of generative language models in global settings, there is an urgent need to also scale our measurements of harm, not just in the number and types of harms covered, but also how well they account for local cultural contexts, including marginalized identities and…

Cited by 21SourcePDFScholar
2023

Parameter-Efficient Finetuning for Robust Continual Multilingual Learning

ACL 2023findings

We introduce and study the problem of Continual Multilingual Learning (CML) where a previously trained multilingual model is periodically updated using new data arriving in stages. If the new data is present only in a subset of languages, we find that the resulting model shows improved performance o…

2023

SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models

ACL 2023long

Stereotype benchmark datasets are crucial to detect and mitigate social stereotypes about groups of people in NLP models. However, existing datasets are limited in size and coverage, and are largely restricted to stereotypes prevalent in the Western society. This is especially problematic as languag…