23 citations · 37 across the 10 of their papers we have counts for
10 papers
The promising potential of vision language models for the generation of textual weather forecasts
Edward C. C. Steele, Dinesh Mane, Emilio Monti +14
Despite the promising capability of multimodal foundation models, their application to the generation of meteorological products and services remains nascent. To accelerate aspirat…
Handling Ontology Gaps in Semantic Parsing
Andrea Bacciu, Marco Damonte, Marco Basaldella +1
The majority of Neural Semantic Parsing (NSP) models are developed with the assumption that there are no concepts outside the ones such models can represent with their target symbo…
MASSIVE Multilingual Abstract Meaning Representation: A Dataset and Baselines for Hallucination Detection
Michael Regan, Shira Wein, George Baker +1
Abstract Meaning Representation (AMR) is a semantic formalism that captures the core meaning of an utterance. There has been substantial work developing AMR corpora in English and…
Enhancing Contextual Understanding in Large Language Models through Contrastive Decoding
Zheng Zhao, Emilio Monti, Jens Lehmann +1
Large language models (LLMs) tend to inadequately integrate input context during text generation, relying excessively on encoded prior knowledge in model parameters, potentially re…
We Need to Talk About Classification Evaluation Metrics in NLP
Peter Vickers, Loïc Barrault, Emilio Monti +1
In Natural Language Processing (NLP) classification tasks such as topic categorisation and sentiment analysis, model generalizability is generally measured with standard metrics su…
Semantic Parsing for Conversational Question Answering over Knowledge Graphs
Laura Perez-Beltrachini, Parag Jain, Emilio Monti +1
In this paper, we are interested in developing semantic parsers which understand natural language questions embedded in a conversation with a user and ground them to formal queries…
One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets
Marco Damonte, Emilio Monti
Semantic parsers map natural language utterances to meaning representations. The lack of a single standard for meaning representations led to the creation of a plethora of semantic…
Multilingual Neural Semantic Parsing for Low-Resourced Languages
Menglin Xia, Emilio Monti
Multilingual semantic parsing is a cost-effective method that allows a single model to understand different languages. However, researchers face a great imbalance of availability o…
Don't Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsing
Subendhu Rongali, Luca Soldaini, Emilio Monti +1
Virtual assistants such as Amazon Alexa, Apple Siri, and Google Assistant often rely on a semantic parsing component to understand which action(s) to execute for an utterance spoke…
Transfer Learning for Neural Semantic Parsing
Xing Fan, Emilio Monti, Lambert Mathias +1
The goal of semantic parsing is to map natural language to a machine interpretable meaning representation language (MRL). One of the constraints that limits full exploration of dee…