2 citations · 4 across the 10 of their papers we have counts for
8 papers · 1 filter
Predicting Implicit Arguments in Procedural Video Instructions
Anil Batra, Laura Sevilla-Lara, Marcus Rohrbach +1
Procedural texts help AI enhance reasoning about context and action sequences. Transforming these into Semantic Role Labeling (SRL) improves understanding of individual steps by id…
MovieSum: An Abstractive Summarization Dataset for Movie Screenplays
Rohit Saxena, Frank Keller
Movie screenplay summarization is challenging, as it requires an understanding of long input contexts and various elements unique to movies. Large language models have shown signif…
Select and Summarize: Scene Saliency for Movie Script Summarization
Rohit Saxena, Frank Keller
Abstractive summarization for long-form narrative texts such as movie scripts is challenging due to the computational and memory constraints of current language models. A movie scr…
Semi-supervised multimodal coreference resolution in image narrations
Arushi Goel, Basura Fernando, Frank Keller +1
In this paper, we study multimodal coreference resolution, specifically where a longer descriptive text, i.e., a narration is paired with an image. This poses significant challenge…
Visual Storytelling with Question-Answer Plans
Danyang Liu, Mirella Lapata, Frank Keller
Visual storytelling aims to generate compelling narratives from image sequences. Existing models often focus on enhancing the representation of the image sequence, e.g., with exter…
Dynamic Planning with a LLM
Gautier Dagan, Frank Keller, Alex Lascarides
While Large Language Models (LLMs) can solve many NLP tasks in zero-shot settings, applications involving embodied agents remain problematic. In particular, complex plans that requ…