Search Results for author:
Found 16 papers, 5 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.
Are Compressed Language Models Less Subgroup Robust?
To reduce the inference cost of large language models, model compression is increasingly used to create smaller scalable models.
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.
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.
The WebCrow French Crossword Solver
Crossword puzzles are one of the most popular word games, played in different languages all across the world, where riddle style can vary significantly from one country to another.
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.
Contrastive Language-Image Pretrained Models are Zero-Shot Human Scanpath Predictors
Understanding the mechanisms underlying human attention is a fundamental challenge for both vision science and artificial intelligence.
Ranked #1 on
Scanpath prediction
on CapMIT1003
Generate and Revise: Reinforcement Learning in Neural Poetry
Writers, poets, singers usually do not create their compositions in just one breath.
An Optimal Control Approach to Learning in SIDARTHE Epidemic model
We formulate the problem in terms of a functional risk that depends on the learning variables through the solutions of a dynamic system.
Vulgaris: Analysis of a Corpus for Middle-Age Varieties of Italian Language
Italian is a Romance language that has its roots in Vulgar Latin.
Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances
We consider a scenario where an artificial agent is reading a stream of text composed of a set of narrations, and it is informed about the identity of some of the individuals that are mentioned in the text portion that is currently being read.
Neural Poetry: Learning to Generate Poems using Syllables
Motivated by the recent progresses on machine learning-based models that learn artistic styles, in this paper we focus on the problem of poem generation.
An Unsupervised Character-Aware Neural Approach to Word and Context Representation Learning
In the last few years, neural networks have been intensively used to develop meaningful distributed representations of words and contexts around them.
Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow
This report provides an introduction to some Machine Learning tools within the most common development environments.
