77 citations · 101 across the 18 of their papers we have counts for
11 papers · 1 filter
What, When, and How: Audio Description as Constrained Global Optimization
Igor Sterner, Mirella Lapata, Alex Lascarides +1
Audio Description (AD) makes movies accessible to blind and visually impaired audiences by narrating visual information in gaps between dialogue. Existing automatic AD systems larg…
Comparing British and American Audio Description of Movies
Igor Sterner, Alex Lascarides, Frank Keller
Narrating the visual component of movies is known as audio description. It is a narrative technique designed to enable blind and visually impaired individuals to follow the story.…
REFRAMED: Towards Realistic Audio Description Generation for Movies
Igor Sterner, Mirella Lapata, Alex Lascarides +1
Audio Description (AD) is a verbal narration of key visual content in videos, enabling access for visually impaired audiences. Unlike standard video captioning, AD is a structured…
Contrastive Learning with Narrative Twins for Modeling Story Salience
Igor Sterner, Alex Lascarides, Frank Keller
Understanding narratives requires identifying which events are most salient for a story's progression. We present a contrastive learning framework for modeling narrative salience t…
Plancraft: an evaluation dataset for planning with LLM agents
Gautier Dagan, Frank Keller, Alex Lascarides
We present Plancraft, a multi-modal evaluation dataset for LLM agents. Plancraft has both a text-only and multi-modal interface, based on the Minecraft crafting GUI. We include the…
Conversational Code Generation: a Case Study of Designing a Dialogue System for Generating Driving Scenarios for Testing Autonomous Vehicles
Rimvydas Rubavicius, Antonio Valerio Miceli-Barone, Alex Lascarides +1
Cyber-physical systems like autonomous vehicles are tested in simulation before deployment, using domain-specific programs for scenario specification. To aid the testing of autonom…
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…
Interactive Acquisition of Fine-grained Visual Concepts by Exploiting Semantics of Generic Characterizations in Discourse
Jonghyuk Park, Alex Lascarides, Subramanian Ramamoorthy
Interactive Task Learning (ITL) concerns learning about unforeseen domain concepts via natural interactions with human users. The learner faces a number of significant constraints:…
Learning Manner of Execution from Partial Corrections
Mattias Appelgren, Alex Lascarides
Some actions must be executed in different ways depending on the context. For example, wiping away marker requires vigorous force while wiping away almonds requires more gentle for…
Learning the Effects of Physical Actions in a Multi-modal Environment
Gautier Dagan, Frank Keller, Alex Lascarides
Large Language Models (LLMs) handle physical commonsense information inadequately. As a result of being trained in a disembodied setting, LLMs often fail to predict an action's out…
Learning Sentence-internal Temporal Relations
M. Lapata, A. Lascarides
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either ex…