Referring expression generation
12 papers with code • 0 benchmarks • 1 datasets
Generate referring expressions
Benchmarks
These leaderboards are used to track progress in Referring expression generation
A Game Of Sorts
Most implemented papers
Modeling Context in Referring Expressions
Humans refer to objects in their environments all the time, especially in dialogue with other people.
Kosmos-2: Grounding Multimodal Large Language Models to the World
microsoft/unilm
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We introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enabling new capabilities of perceiving object descriptions (e. g., bounding boxes) and grounding text to the visual world.
NeuralREG: An end-to-end approach to referring expression generation
Traditionally, Referring Expression Generation (REG) models first decide on the form and then on the content of references to discourse entities in text, typically relying on features such as salience and grammatical function.
Enriching the WebNLG corpus
This paper describes the enrichment of WebNLG corpus (Gardent et al., 2017a, b), with the aim to further extend its usefulness as a resource for evaluating common NLG tasks, including Discourse Ordering, Lexicalization and Referring Expression Generation.
Referring Expression Generation Using Entity Profiles
mcao610/ProfileREG
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IJCNLP 2019
Referring Expression Generation (REG) is the task of generating contextually appropriate references to entities.
Improving Quality and Efficiency in Plan-based Neural Data-to-Text Generation
We follow the step-by-step approach to neural data-to-text generation we proposed in Moryossef et al (2019), in which the generation process is divided into a text-planning stage followed by a plan-realization stage.
Pento-DIARef: A Diagnostic Dataset for Learning the Incremental Algorithm for Referring Expression Generation from Examples
NLP tasks are typically defined extensionally through datasets containing example instantiations (e. g., pairs of image i and text t), but motivated intensionally through capabilities invoked in verbal descriptions of the task (e. g., "t is a description of i, for which the content of i needs to be recognised and understood").
Whether you can locate or not? Interactive Referring Expression Generation
superhero-7/ireg
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Referring Expression Generation (REG) aims to generate unambiguous Referring Expressions (REs) for objects in a visual scene, with a dual task of Referring Expression Comprehension (REC) to locate the referred object.
Collecting Visually-Grounded Dialogue with A Game Of Sorts
We address these concerns by introducing a collaborative image ranking task, a grounded agreement game we call "A Game Of Sorts".
GLaMM: Pixel Grounding Large Multimodal Model
In this work, we present Grounding LMM (GLaMM), the first model that can generate natural language responses seamlessly intertwined with corresponding object segmentation masks.
