1 citations · 3 across the 8 of their papers we have counts for
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CulturalBench: A Robust, Diverse, and Challenging Cultural Benchmark by Human-AI CulturalTeaming
Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin +8
Robust, diverse, and challenging cultural knowledge benchmarks are essential for measuring our progress towards making LMs that are helpful across diverse cultures. We introduce Cu…
From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Models
Mehar Bhatia, Sahithya Ravi, Aditya Chinchure +2
Despite recent advancements in vision-language models, their performance remains suboptimal on images from non-western cultures due to underrepresentation in training datasets. Var…
CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs' (Lack of) Multicultural Knowledge
Yu Ying Chiu, Liwei Jiang, Maria Antoniak +7
Frontier large language models (LLMs) are developed by researchers and practitioners with skewed cultural backgrounds and on datasets with skewed sources. However, LLMs' (lack of)…
Empowering Air Travelers: A Chatbot for Canadian Air Passenger Rights
Maksym Taranukhin, Sahithya Ravi, Gabor Lukacs +2
The Canadian air travel sector has seen a significant increase in flight delays, cancellations, and other issues concerning passenger rights. Recognizing this demand, we present a…
Small But Funny: A Feedback-Driven Approach to Humor Distillation
Sahithya Ravi, Patrick Huber, Akshat Shrivastava +4
The emergence of Large Language Models (LLMs) has brought to light promising language generation capabilities, particularly in performing tasks like complex reasoning and creative…
CASE: Commonsense-Augmented Score with an Expanded Answer Space
Wenkai Chen, Sahithya Ravi, Vered Shwartz
LLMs have demonstrated impressive zero-shot performance on NLP tasks thanks to the knowledge they acquired in their training. In multiple-choice QA tasks, the LM probabilities are…