most citedFace2Text revisited: Improved data set and baseline results

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cs.CL2024

Automatic Metrics in Natural Language Generation: A Survey of Current Evaluation Practices

Patrícia Schmidtová, Saad Mahamood, Simone Balloccu +6

Automatic metrics are extensively used to evaluate natural language processing systems. However, there has been increasing focus on how they are used and reported by practitioners…

cs.CL2024

Context-aware Visual Storytelling with Visual Prefix Tuning and Contrastive Learning

Yingjin Song, Denis Paperno, Albert Gatt

Visual storytelling systems generate multi-sentence stories from image sequences. In this task, capturing contextual information and bridging visual variation bring additional chal…

cs.CL2024

How and where does CLIP process negation?

Vincent Quantmeyer, Pablo Mosteiro, Albert Gatt

Various benchmarks have been proposed to test linguistic understanding in pre-trained vision \& language (VL) models. Here we build on the existence task from the VALSE benchmark (…

cs.CL2023

ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models

Ilker Kesen, Andrea Pedrotti, Mustafa Dogan +8

With the ever-increasing popularity of pretrained Video-Language Models (VidLMs), there is a pressing need to develop robust evaluation methodologies that delve deeper into their v…

cs.CL2023

The Scenario Refiner: Grounding subjects in images at the morphological level

Claudia Tagliaferri, Sofia Axioti, Albert Gatt +1

Derivationally related words, such as "runner" and "running", exhibit semantic differences which also elicit different visual scenarios. In this paper, we ask whether Vision and La…