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Found 13 papers, 1 papers with code
Clue-Instruct: Text-Based Clue Generation for Educational Crossword Puzzles
By gathering from Wikipedia pages informative content associated with relevant keywords, we use Large Language Models to automatically generate pedagogical clues related to the given input keyword and its context.
Enhancing Modern Supervised Word Sense Disambiguation Models by Semantic Lexical Resources
Supervised models for Word Sense Disambiguation (WSD) currently yield to state-of-the-art results in the most popular benchmarks.
Multitask Kernel-based Learning with Logic Constraints
This paper presents a general framework to integrate prior knowledge in the form of logic constraints among a set of task functions into kernel machines.
A novel integrated industrial approach with cobots in the age of industry 4.0 through conversational interaction and computer vision
From robots that replace workers to robots that serve as helpful colleagues, the field of robotic automation is experiencing a new trend that represents a huge challenge for component manufacturers.
Neural paraphrasing by automatically crawled and aligned sentence pairs
In this paper we present a method for the automatic generation of large aligned corpora, that is based on the assumption that news and blog websites talk about the same events using different narrative styles.
BUSTER: a "BUSiness Transaction Entity Recognition" dataset
Albeit Natural Language Processing has seen major breakthroughs in the last few years, transferring such advances into real-world business cases can be challenging.
Data Augmentation and Transfer Learning Approaches Applied to Facial Expressions Recognition
To measure the generalization ability of the models, we apply extra-database protocol approach, namely we train models on the augmented versions of training dataset and test them on two different databases.
Fast Vocabulary Transfer for Language Model Compression
Real-world business applications require a trade-off between language model performance and size.
Multi-word Tokenization for Sequence Compression
Large Language Models have proven highly successful at modelling a variety of tasks.
Italian Crossword Generator: Enhancing Education through Interactive Word Puzzles
On the other hand, for generating crossword clues from a given text, Zero/Few-shot learning techniques were used to extract clues from the input text, adding variety and creativity to the puzzles.
Multitask Kernel-based Learning with First-Order Logic Constraints
In this paper we propose a general framework to integrate supervised and unsupervised examples with background knowledge expressed by a collection of first-order logic clauses into kernel machines.
SortNet: Learning To Rank By a Neural-Based Sorting Algorithm
Two main approaches exist in literature for the task of learning to rank: 1) a score function, learned by examples, which evaluates the properties of each object yielding an absolute relevance value that can be used to order the objects or 2) a pairwise approach, where a "preference function" is learned using pairs of objects to define which one has to be ranked first.
An energy-based comparative analysis of common approaches to text classification in the Legal domain
Most Machine Learning research evaluates the best solutions in terms of performance.
