André Freitas

research

∙ 08/27/2023

Empowering Cross-lingual Abilities of Instruction-tuned Large Language Models by Translation-following demonstrations

The language ability of Large Language Models (LLMs) is often unbalanced...

0 Leonardo Ranaldi, et al. ∙

research

∙ 08/07/2023

Towards Controllable Natural Language Inference through Lexical Inference Types

Explainable natural language inference aims to provide a mechanism to pr...

0 Yingji Zhang, et al. ∙

research

∙ 08/01/2023

Discourse-Aware Text Simplification: From Complex Sentences to Linked Propositions

Sentences that present a complex syntax act as a major stumbling block f...

0 Christina Niklaus, et al. ∙

research

∙ 07/19/2023

Generating Mathematical Derivations with Large Language Models

The derivation of mathematical results in specialised fields using Large...

0 Jordan Meadows, et al. ∙

research

∙ 05/28/2023

Large Language Models, scientific knowledge and factuality: A systematic analysis in antibiotic discovery

Inferring over and extracting information from Large Language Models (LL...

0 Magdalena Wysocka, et al. ∙

research

∙ 05/22/2023

Deep Clustering for Data Cleaning and Integration

Deep Learning (DL) techniques now constitute the state-of-the-art for im...

0 Hafiz Tayyab Rauf, et al. ∙

research

∙ 05/21/2023

A Symbolic Framework for Systematic Evaluation of Mathematical Reasoning with Transformers

Whether Transformers can learn to apply symbolic rules and generalise to...

0 Jordan Meadows, et al. ∙

research

∙ 05/15/2023

Estimating the Causal Effects of Natural Logic Features in Neural NLI Models

Rigorous evaluation of the causal effects of semantic features on langua...

3 Julia Rozanova, et al. ∙

research

∙ 05/12/2023

Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitions

Neural-based word embeddings using solely distributional information hav...

11 Marco Valentino, et al. ∙

research

∙ 05/05/2023

NLI4CT: Multi-Evidence Natural Language Inference for Clinical Trial Reports

How can we interpret and retrieve medical evidence to support clinical d...

18 Mael Jullien, et al. ∙

research

∙ 05/04/2023

SemEval-2023 Task 7: Multi-Evidence Natural Language Inference for Clinical Trial Data

This paper describes the results of SemEval 2023 task 7 – Multi-Evidence...

17 Mael Jullien, et al. ∙

research

∙ 05/02/2023

Learning Disentangled Semantic Spaces of Explanations via Invertible Neural Networks

Disentangling sentence representations over continuous spaces can be a c...

0 Yingji Zhang, et al. ∙

research

∙ 04/20/2023

Interventional Probing in High Dimensions: An NLI Case Study

Probing strategies have been shown to detect the presence of various lin...

2 Julia Rozanova, et al. ∙

research

∙ 03/06/2023

On the Visualisation of Argumentation Graphs to Support Text Interpretation

The recent evolution in Natural Language Processing (NLP) methods, in pa...

0 Hanadi Mardah, et al. ∙

research

∙ 02/09/2023

Analysis of business process automation as linear time-invariant system network

In this work, we examined Business Process (BP) production as a signal; ...

0 Mauricio Jacobo Romero, et al. ∙

research

∙ 10/12/2022

Quasi-symbolic explanatory NLI via disentanglement: A geometrical examination

Disentangling the encodings of neural models is a fundamental aspect for...

0 Yingji Zhang, et al. ∙

research

∙ 10/03/2022

Estimating productivity gains in digital automation

This paper proposes a novel productivity estimation model to evaluate th...

0 Mauricio Jacobo Romero, et al. ∙

research

∙ 08/05/2022

Going Beyond Approximation: Encoding Constraints for Explainable Multi-hop Inference via Differentiable Combinatorial Solvers

Integer Linear Programming (ILP) provides a viable mechanism to encode e...

3 Mokanarangan Thayaparan, et al. ∙

research

∙ 08/02/2022

Active entailment encoding for explanation tree construction using parsimonious generation of hard negatives

Entailment trees have been proposed to simulate the human reasoning proc...

0 Alex Bogatu, et al. ∙

research

∙ 07/02/2022

Biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data

In this paper we provide a structured literature analysis focused on Dee...

0 Magdalena Wysocka, et al. ∙

research

∙ 06/20/2022

Metareview-informed Explainable Cytokine Storm Detection during CAR-T cell Therapy

Cytokine release syndrome (CRS), also known as cytokine storm, is one of...

0 Alex Bogatu, et al. ∙

research

∙ 05/30/2022

A Survey in Mathematical Language Processing

Informal mathematical text underpins real-world quantitative reasoning a...

0 Jordan Meadows, et al. ∙

research

∙ 05/03/2022

Scientific Explanation and Natural Language: A Unified Epistemological-Linguistic Perspective for Explainable AI

A fundamental research goal for Explainable AI (XAI) is to build models ...

12 Marco Valentino, et al. ∙

research

∙ 04/26/2022

Systematicity, Compositionality and Transitivity of Deep NLP Models: a Metamorphic Testing Perspective

Metamorphic testing has recently been used to check the safety of neural...

0 Edoardo Manino, et al. ∙

research

∙ 04/11/2022

Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making

This paper contributes with a pragmatic evaluation framework for explain...

0 Oskar Wysocki, et al. ∙

research

∙ 02/04/2022

Transformers and the representation of biomedical background knowledge

BioBERT and BioMegatron are Transformers models adapted for the biomedic...

0 Oskar Wysocki, et al. ∙

research

∙ 01/25/2022

Do Transformers Encode a Foundational Ontology? Probing Abstract Classes in Natural Language

With the methodological support of probing (or diagnostic classification...

10 Mael Jullien, et al. ∙

research

∙ 01/12/2022

PhysNLU: A Language Resource for Evaluating Natural Language Understanding and Explanation Coherence in Physics

In order for language models to aid physics research, they must first en...

0 Jordan Meadows, et al. ∙

research

∙ 01/07/2022

Microeconomic Foundations of Decentralised Organisations

In this article, we analyse how decentralised digital infrastructures ca...

0 Mauricio Jacobo Romero, et al. ∙

research

∙ 12/15/2021

Decomposing Natural Logic Inferences in Neural NLI

In the interest of interpreting neural NLI models and their reasoning st...

9 Julia Rozanova, et al. ∙

research

∙ 09/20/2021

A Survey of Text Games for Reinforcement Learning informed by Natural Language

Reinforcement Learning has shown success in a number of complex virtual ...

0 Philip Osborne, et al. ∙

research

∙ 09/17/2021

Grounding Natural Language Instructions: Can Large Language Models Capture Spatial Information?

Models designed for intelligent process automation are required to be ca...

8 Julia Rozanova, et al. ∙

research

∙ 09/15/2021

Disentangling Generative Factors in Natural Language with Discrete Variational Autoencoders

The ability of learning disentangled representations represents a major ...

0 Giangiacomo Mercatali, et al. ∙

research

∙ 07/25/2021

Hybrid Autoregressive Solver for Scalable Abductive Natural Language Inference

Regenerating natural language explanations for science questions is a ch...

1 Marco Valentino, et al. ∙

research

∙ 07/16/2021

Architectures of Meaning, A Systematic Corpus Analysis of NLP Systems

This paper proposes a novel statistical corpus analysis framework target...

12 Oskar Wysocki, et al. ∙

research

∙ 05/24/2021

Context-Preserving Text Simplification

We present a context-preserving text simplification (TS) approach that r...

0 Christina Niklaus, et al. ∙

research

∙ 05/17/2021

Supporting Context Monotonicity Abstractions in Neural NLI Models

Natural language contexts display logical regularities with respect to s...

3 Julia Rozanova, et al. ∙

research

∙ 05/12/2021

Encoding Explanatory Knowledge for Zero-shot Science Question Answering

This paper describes N-XKT (Neural encoding based on eXplanatory Knowled...

0 Zili Zhou, et al. ∙

research

∙ 05/07/2021

∂-Explainer: Abductive Natural Language Inference via Differentiable Convex Optimization

Constrained optimization solvers with Integer Linear programming (ILP) h...

3 Mokanarangan Thayaparan, et al. ∙

research

∙ 05/05/2021

Do Natural Language Explanations Represent Valid Logical Arguments? Verifying Entailment in Explainable NLI Gold Standards

An emerging line of research in Explainable NLP is the creation of datas...

0 Marco Valentino, et al. ∙

research

∙ 05/03/2021

Switching Contexts: Transportability Measures for NLP

This paper explores the topic of transportability, as a sub-area of gene...

0 Guy Marshall, et al. ∙

research

∙ 04/30/2021

Number and quality of diagrams in scholarly publications is associated with number of citations

Diagrams are often used in scholarly communication. We analyse a corpus ...

0 Guy Clarke Marshall, et al. ∙

research

∙ 04/30/2021

Scholarly AI system diagrams as an access point to mental models

Complex systems, such as Artificial Intelligence (AI) systems, are compr...

0 Guy Clarke Marshall, et al. ∙

research

∙ 04/30/2021

Structuralist analysis for neural network system diagrams

This short paper examines diagrams describing neural network systems in ...

0 Guy Clarke Marshall, et al. ∙

research

∙ 04/12/2021

What's Your Value of Travel Time? Collecting Traveler-Centered Mobility Data via Crowdsourcing

Mobility and transport, by their nature, involve crowds and require the ...

0 Cristian Consonni, et al. ∙

research

∙ 04/12/2021

Does My Representation Capture X? Probe-Ably

Probing (or diagnostic classification) has become a popular strategy for...

18 Deborah Ferreira, et al. ∙

research

∙ 03/24/2021

Similarity-Based Equational Inference in Physics

Derivation in physics, in the form of derivation reconstruction of publi...

0 Jordan Meadows, et al. ∙

research

∙ 11/20/2020

Cost-effective Variational Active Entity Resolution

Accurately identifying different representations of the same real-world ...

0 Alex Bogatu, et al. ∙

research

∙ 10/25/2020

ExplanationLP: Abductive Reasoning for Explainable Science Question Answering

We propose a novel approach for answering and explaining multiple-choice...

0 Mokanarangan Thayaparan, et al. ∙

research

∙ 10/01/2020

A Survey on Explainability in Machine Reading Comprehension

This paper presents a systematic review of benchmarks and approaches for...

0 Mokanarangan Thayaparan, et al. ∙

André Freitas

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