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Found 13 papers, 4 papers with code
Merkel Podcast Corpus: A Multimodal Dataset Compiled from 16 Years of Angela Merkel’s Weekly Video Podcasts
We introduce the Merkel Podcast Corpus, an audio-visual-text corpus in German collected from 16 years of (almost) weekly Internet podcasts of former German chancellor Angela Merkel.
CulturalFrames: Assessing Cultural Expectation Alignment in Text-to-Image Models and Evaluation Metrics
In this work, we present the first study to systematically quantify the alignment of T2I models and evaluation metrics with respect to both explicit as well as implicit cultural expectations.
UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction
We introduce UI-Vision, the first comprehensive, license-permissive benchmark for offline, fine-grained evaluation of computer use agents in real-world desktop environments.
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces
We introduce the Local Intersectional Visual Spaces (LIVS) dataset, a benchmark for multi-criteria alignment, developed through a two-year participatory process with 30 community organizations to support the pluralistic alignment of text-to-image (T2I) models in inclusive urban planning.
Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation
Neural Machine Translation (NMT) systems built on multilingual sequence-to-sequence Language Models (msLMs) fail to deliver expected results when the amount of parallel data for a language, as well as the language's representation in the model are limited.
BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks
We use an efficient data curation process to ensure our data is high-quality and license-permissive.
Benchmarking Vision Language Models for Cultural Understanding
Benchmarking VLMs on CulturalVQA, including GPT-4V and Gemini, reveals disparity in their level of cultural understanding across regions, with strong cultural understanding capabilities for North America while significantly lower performance for Africa.
Towards Adversarially Robust Vision-Language Models: Insights from Design Choices and Prompt Formatting Techniques
Vision-Language Models (VLMs) have witnessed a surge in both research and real-world applications.
Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource Translation
In this paper, we show that intermediate-task fine-tuning (ITFT) of PMSS models is extremely beneficial for domain-specific NMT, especially when target domain data is limited/unavailable and the considered languages are missing or under-represented in the PMSS model.
Merkel Podcast Corpus: A Multimodal Dataset Compiled from 16 Years of Angela Merkel's Weekly Video Podcasts
We introduce the Merkel Podcast Corpus, an audio-visual-text corpus in German collected from 16 years of (almost) weekly Internet podcasts of former German chancellor Angela Merkel.
Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?
What can pre-trained multilingual sequence-to-sequence models like mBART contribute to translating low-resource languages?
The Two Shades of Dubbing in Neural Machine Translation
Dubbing has two shades; synchronisation constraints are applied only when the actor{'}s mouth is visible on screen, while the translation is unconstrained for off-screen dubbing.
A Stochastic Game Framework for Efficient Energy Management in Microgrid Networks
A microgrid is capable of generating a limited amount of energy from a renewable resource and is responsible for handling the demands of its dedicated customers.
