paper-with-me

홈 › Papers

Predicting Word Concreteness and Imagery

2019-05-01 · WS 2019 5 · Jean Charbonnier, Christian Wartena

Concreteness of words has been studied extensively in psycholinguistic literature. A number of datasets have been created with average values for perceived concreteness of words. We show that we can train a regression model on these data, using word embeddings and morphological features, that can predict these concreteness values with high accuracy. We evaluate the model on 7 publicly available datasets. Only for a few small subsets of these datasets prediction of concreteness values are found in the literature. Our results clearly outperform the reported results for these datasets.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

regressionWord Embeddings

Similar Papers 제목 키워드 기반

Language-Independent Prediction of Psycholinguistic Properties of Words

2017-11-01 · IJCNLP 2017 11 · Yo Ehara

The psycholinguistic properties of words, namely, word familiarity, age of acquisition, concreteness, and imagery, have been reported to be effective for educational natural language-processing tasks. Previous studies on…

Lexical SimplificationPrediction

Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings

2018-07-09 · Nikola Ljubešić, Darja Fišer, Anita Peti-Stantić

The notions of concreteness and imageability, traditionally important in psycholinguistics, are gaining significance in semantic-oriented natural language processing tasks. In this paper we investigate the predictability…

Cross-Lingual TransferWord Embeddings

Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings

2018-07-01 · WS 2018 7 · Nikola Ljube{\v{s}}i{\'c}, Darja Fi{\v{s}}er, Anita Peti-Stanti{\'c}

The notions of concreteness and imageability, traditionally important in psycholinguistics, are gaining significance in semantic-oriented natural language processing tasks. In this paper we investigate the predictability…

Cross-Lingual TransferRepresentation LearningWord Embeddings

Real Images, Worse Judgments: Evaluating Vision-Language Models on Concreteness and Imagery

2026-05-26 · Yifan Jiang, Ruoxi Ning, Sheng Yao, Freda Shi arxiv

Visual inputs are often assumed to improve language understanding in multimodal models. We examine this assumption by asking whether vision-language models (VLMs) can distinguish useful visual evidence from incidental im…

On the Geometry of Concreteness

2022-05-01 · RepL4NLP (ACL) 2022 5 · Christian Wartena

In this paper we investigate how concreteness and abstractness are represented in word embedding spaces. We use data for English and German, and show that concreteness and abstractness can be determined independently and…