1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Don't Learn, Ground: A Case for Natural Language Inference with Visual Grounding
Daniil Ignatev, Ayman Santeer, Albert Gatt +1
We propose a zero-shot method for Natural Language Inference (NLI) that leverages multimodal representations by grounding language in visual contexts. Our approach generates visual…
cs.LG2025
Hypernetworks for Perspectivist Adaptation
Daniil Ignatev, Denis Paperno, Massimo Poesio
The task of perspective-aware classification introduces a bottleneck in terms of parametric efficiency that did not get enough recognition in existing studies. In this article, we…
cs.CL2025★ 1 cited
Burn After Reading: Do Multimodal Large Language Models Truly Capture Order of Events in Image Sequences?
Yingjin Song, Yupei Du, Denis Paperno +1
This paper introduces the TempVS benchmark, which focuses on temporal grounding and reasoning capabilities of Multimodal Large Language Models (MLLMs) in image sequences. TempVS co…