Word embeddings have advanced the state of the art in NLP across numerous tasks.
Understanding the contents of dense neural representations is of utmost interest to the …

In view of the limitation of the forward dictionaries to attend to the needs specific to the
language producers, an alternate resource in the form of 'Reverse Dictionary'needs to be …

A reverse dictionary takes a target word's description as input and returns the words that fit
the description. Reverse Dictionaries are useful for new language learners, anomia patients …

A reverse dictionary is a task of finding appropriate words based on given definitions.
Existing studies struggle to capture the subtle differences between words with similar …

In reverse dictionary (RD) research, the goal is to construct the components of a target word
vector through the parsing of human-comprehensible definitions. This process emulates the …

A reverse dictionary generates a ranked list of vocabulary words that correspond to the
definition of a given input description. Although reverse dictionary has widely practical …

Probing and enhancing large language models' reasoning capacity remains a crucial open
question. Here we re-purpose the reverse dictionary task as a case study to probe LLMs' …

Character-based word segmentation models have been extensively applied to Asian
languages, including Thai, owing to their promising performance. These models estimate …

Owing to the large information content of adjectives in natural language-based data, we
have dealt with the subject of adjective phrases in the paradigm of PNL. We have proposed …

Towards a Transformer-Based Reverse Dictionary Model for Quality Estimation of Definitions
(Student Abstract) Page 1 Towards a Transformer-Based Reverse Dictionary Model for …