1 citations · 1 across the 5 of their papers we have counts for
7 papers
HyperBrowseComp: A Multilingual and Multimodal Stress Test for Web-Browsing Agents
Alham Fikri Aji, Faiz Rizki Ramadhan, Zayd M. K. Zuhri +14
We introduce HyperBrowseComp, a multilingual and multimodal browsing benchmark comprising 423 manually authored and human-validated questions across 13 languages, written by native…
Deep and shallow biases in language models
An Vo, Vy Tuong Dang, Khai-Nguyen Nguyen +4
Large language models often repeatedly select the same answer even when many alternatives are plausible. Prior work treats this concentration as bias, but it does not distinguish s…
Afri-MCQA: Multimodal Cultural Question Answering for African Languages
Atnafu Lambebo Tonja, Srija Anand, Emilio Villa-Cueva +16
Africa is home to over one-third of the world's languages, yet remains underrepresented in AI research. We introduce Afri-MCQA, the first Multilingual Cultural Question-Answering b…
VMMU: A Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark
Vy Tuong Dang, An Vo, Emilio Villa-Cueva +4
We introduce VMMU, a Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark designed to evaluate how vision-language models (VLMs) interpret and reason over visual a…
MOMENTS: A Comprehensive Multimodal Benchmark for Theory of Mind
Emilio Villa-Cueva, S M Masrur Ahmed, Rendi Chevi +7
Understanding Theory of Mind is essential for building socially intelligent multimodal agents capable of perceiving and interpreting human behavior. We introduce MoMentS (Multimoda…
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…