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09/20/2023
Vehicle-to-Grid and ancillary services:a profitability analysis under uncertainty
The rapid and massive diffusion of electric vehicles poses new challenge...
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09/14/2023
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions
Training large language models to follow instructions makes them perform...
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08/02/2023
XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models
Without proper safeguards, large language models will readily follow mal...
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04/20/2023
E Pluribus Unum: Guidelines on Multi-Objective Evaluation of Recommender Systems
Recommender Systems today are still mostly evaluated in terms of accurac...
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04/14/2023
EvalRS 2023. Well-Rounded Recommender Systems For Real-World Deployments
EvalRS aims to bring together practitioners from industry and academia t...
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12/18/2022
Beyond Digital "Echo Chambers": The Role of Viewpoint Diversity in Political Discussion
Increasingly taking place in online spaces, modern political conversatio...
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11/08/2022
SocioProbe: What, When, and Where Language Models Learn about Sociodemographics
Pre-trained language models (PLMs) have outperformed other NLP models on...
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11/07/2022
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale
Machine learning models are now able to convert user-written text descri...
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10/28/2022
"It's Not Just Hate”: A Multi-Dimensional Perspective on Detecting Harmful Speech Online
Well-annotated data is a prerequisite for good Natural Language Processi...
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10/26/2022
ProSiT! Latent Variable Discovery with PROgressive SImilarity Thresholds
The most common ways to explore latent document dimensions are topic mod...
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10/20/2022
Data-Efficient Strategies for Expanding Hate Speech Detection into Under-Resourced Languages
Hate speech is a global phenomenon, but most hate speech datasets so far...
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10/13/2022
Is It Worth the (Environmental) Cost? Limited Evidence for the Benefits of Diachronic Continuous Training
Language is constantly changing and evolving, leaving language models to...
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10/04/2022
When and why vision-language models behave like bags-of-words, and what to do about it?
Despite the success of large vision and language models (VLMs) in many d...
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08/10/2022
Real-Time Oil Leakage Detection on Aftermarket Motorcycle Damping System with Convolutional Neural Networks
In this work, we describe in detail how Deep Learning and Computer Visio...
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07/12/2022
EvalRS: a Rounded Evaluation of Recommender Systems
Much of the complexity of Recommender Systems (RSs) comes from the fact ...
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04/05/2022
"Does it come in black?" CLIP-like models are zero-shot recommenders
Product discovery is a crucial component for online shopping. However, i...
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01/26/2022
Twitter-Demographer: A Flow-based Tool to Enrich Twitter Data
Twitter data have become essential to Natural Language Processing (NLP) ...
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11/18/2021
Beyond NDCG: behavioral testing of recommender systems with RecList
As with most Machine Learning systems, recommender systems are typically...
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09/27/2021
Language Invariant Properties in Natural Language Processing
Meaning is context-dependent, but many properties of language (should) r...
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09/15/2021
SWEAT: Scoring Polarization of Topics across Different Corpora
Understanding differences of viewpoints across corpora is a fundamental ...
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04/19/2021
SIGIR 2021 E-Commerce Workshop Data Challenge
The 2021 SIGIR workshop on eCommerce is hosting the Coveo Data Challenge...
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04/18/2021
Language in a (Search) Box: Grounding Language Learning in Real-World Human-Machine Interaction
We investigate grounded language learning through real-world data, by mo...
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04/02/2021
Query2Prod2Vec Grounded Word Embeddings for eCommerce
We present Query2Prod2Vec, a model that grounds lexical representations ...
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12/17/2020
BERT Goes Shopping: Comparing Distributional Models for Product Representations
Word embeddings (e.g., word2vec) have been applied successfully to eComm...
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07/20/2020
Fantastic Embeddings and How to Align Them: Zero-Shot Inference in a Multi-Shop Scenario
This paper addresses the challenge of leveraging multiple embedding spac...
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04/30/2020
Knowledge Graph Embeddings and Explainable AI
Knowledge graph embeddings are now a widely adopted approach to knowledg...
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04/16/2020
Cross-lingual Contextualized Topic Models with Zero-shot Learning
Many data sets in a domain (reviews, forums, news, etc.) exist in parall...
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04/13/2020
Compass-aligned Distributional Embeddings for Studying Semantic Differences across Corpora
Word2vec is one of the most used algorithms to generate word embeddings ...
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04/08/2020
Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence
Topic models extract meaningful groups of words from documents, allowing...
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03/11/2020
"An Image is Worth a Thousand Features": Scalable Product Representations for In-Session Type-Ahead Personalization
We address the problem of personalizing query completion in a digital co...
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03/05/2020
What the [MASK]? Making Sense of Language-Specific BERT Models
Recently, Natural Language Processing (NLP) has witnessed an impressive ...
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06/05/2019
Training Temporal Word Embeddings with a Compass
Temporal word embeddings have been proposed to support the analysis of w...
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04/11/2019
Experimental neural network enhanced quantum tomography
Quantum tomography is currently ubiquitous for testing any implementatio...
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11/09/2018