Search Results for author: Andre Freitas

Found 38 papers, 9 papers with code

To be or not to be an Integer? Encoding Variables for Mathematical Text

no code implementations Findings (ACL) 2022 Deborah Ferreira, Mokanarangan Thayaparan, Marco Valentino, Julia Rozanova, Andre Freitas

The application of Natural Language Inference (NLI) methods over large textual corpora can facilitate scientific discovery, reducing the gap between current research and the available large-scale scientific knowledge.

Natural Language Inference

Generating Mathematical Derivations with Large Language Models

1 code implementation19 Jul 2023 Jordan Meadows, Marco Valentino, Andre Freitas

In addition, we analyse 1. 7K equations, and over 200 derivations, to highlight common reasoning errors such as the inclusion of incorrect, irrelevant, and redundant equations.

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

no code implementations28 May 2023 Magdalena Wysocka, Oskar Wysocki, Maxime Delmas, Vincent Mutel, Andre Freitas

The results show that while LLMs are currently not fit for purpose to be used as biomedical factual knowledge bases, there is a promising emerging property in the direction of factuality as the models become domain specialised, scale-up in size and level of human feedback.


A Symbolic Framework for Systematic Evaluation of Mathematical Reasoning with Transformers

no code implementations21 May 2023 Jordan Meadows, Marco Valentino, Damien Teney, Andre Freitas

Whether Transformers can learn to apply symbolic rules and generalise to out-of-distribution examples is an open research question.

Mathematical Reasoning

A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation

no code implementations19 May 2023 Xiaowei Huang, Wenjie Ruan, Wei Huang, Gaojie Jin, Yi Dong, Changshun Wu, Saddek Bensalem, Ronghui Mu, Yi Qi, Xingyu Zhao, Kaiwen Cai, Yanghao Zhang, Sihao Wu, Peipei Xu, Dengyu Wu, Andre Freitas, Mustafa A. Mustafa

Large Language Models (LLMs) have exploded a new heatwave of AI for their ability to engage end-users in human-level conversations with detailed and articulate answers across many knowledge domains.

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

no code implementations15 May 2023 Julia Rozanova, Marco Valentino, Andre Freitas

Rigorous evaluation of the causal effects of semantic features on language model predictions can be hard to achieve for natural language reasoning problems.

Language Modelling

Interventional Probing in High Dimensions: An NLI Case Study

no code implementations20 Apr 2023 Julia Rozanova, Marco Valentino, Lucas Cordeiro, Andre Freitas

Probing strategies have been shown to detect the presence of various linguistic features in large language models; in particular, semantic features intermediate to the "natural logic" fragment of the Natural Language Inference task (NLI).

Natural Language Inference Vocal Bursts Intensity Prediction

On the Visualisation of Argumentation Graphs to Support Text Interpretation

no code implementations6 Mar 2023 Hanadi Mardah, Oskar Wysocki, Markel Vigo, Andre Freitas

Therefore, AGs were considered to deliver a more critical approach to argument interpretation, especially with unfamiliar topics.

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

no code implementations9 Feb 2023 Mauricio Jacobo-Romero, Danilo S. Carvalho, Andre Freitas

In this work, we examined Business Process (BP) production as a signal; this novel approach explores a BP workflow as a linear time-invariant (LTI) system.

Learning Disentangled Representations for Natural Language Definitions

no code implementations22 Sep 2022 Danilo S. Carvalho, Giangiacomo Mercatali, Yingji Zhang, Andre Freitas

Disentangling the encodings of neural models is a fundamental aspect for improving interpretability, semantic control and downstream task performance in Natural Language Processing.


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

no code implementations20 Jun 2022 Alex Bogatu, Magdalena Wysocka, Oskar Wysocki, Holly Butterworth, Donal Landers, Elaine Kilgour, Andre Freitas

Cytokine release syndrome (CRS), also known as cytokine storm, is one of the most consequential adverse effects of chimeric antigen receptor therapies that have shown promising results in cancer treatment.

A Survey in Mathematical Language Processing

no code implementations30 May 2022 Jordan Meadows, Andre Freitas

Informal mathematical text underpins real-world quantitative reasoning and communication.


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

no code implementations25 Jan 2022 Mael Jullien, Marco Valentino, Andre Freitas

With the methodological support of probing (or diagnostic classification), recent studies have demonstrated that Transformers encode syntactic and semantic information to some extent.

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

1 code implementation LREC 2022 Jordan Meadows, Zili Zhou, Andre Freitas

In order for language models to aid physics research, they must first encode representations of mathematical and natural language discourse which lead to coherent explanations, with correct ordering and relevance of statements.

Sentence Ordering

Decomposing Natural Logic Inferences in Neural NLI

1 code implementation15 Dec 2021 Julia Rozanova, Deborah Ferreira, Marco Valentino, Mokanrarangan Thayaparan, Andre Freitas

In the interest of interpreting neural NLI models and their reasoning strategies, we carry out a systematic probing study which investigates whether these models capture the crucial semantic features central to natural logic: monotonicity and concept inclusion.

Decision Making valid

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

1 code implementation17 Sep 2021 Julia Rozanova, Deborah Ferreira, Krishna Dubba, Weiwei Cheng, Dell Zhang, Andre Freitas

Even though BERT and similar pre-trained language models have excelled in several NLP tasks, their use has not been widely explored for the UI grounding domain.

Architectures of Meaning, A Systematic Corpus Analysis of NLP Systems

no code implementations16 Jul 2021 Oskar Wysocki, Malina Florea, Donal Landers, Andre Freitas

This paper proposes a novel statistical corpus analysis framework targeted towards the interpretation of Natural Language Processing (NLP) architectural patterns at scale.

Encoding Explanatory Knowledge for Zero-shot Science Question Answering

no code implementations IWCS (ACL) 2021 Zili Zhou, Marco Valentino, Donal Landers, Andre Freitas

This paper describes N-XKT (Neural encoding based on eXplanatory Knowledge Transfer), a novel method for the automatic transfer of explanatory knowledge through neural encoding mechanisms.

Science Question Answering Transfer Learning

Why scholars are diagramming neural network models

no code implementations30 Apr 2021 Guy Clarke Marshall, Caroline Jay, Andre Freitas

Perhaps because of this, diagrams, as "icons of relation", are a prevalent medium for signifying complex models.

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

no code implementations30 Apr 2021 Guy Clarke Marshall, Caroline Jay, Andre Freitas

We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings (ACL 2017), and find inclusion of a system diagram to be correlated with higher numbers of citations after 3 years.

Structuralist analysis for neural network system diagrams

no code implementations30 Apr 2021 Guy Clarke Marshall, Caroline Jay, Andre Freitas

Using a corpus-based approach, we argue that the heterogeneous diagrammatic notations used for neural network systems has implications for signification in this domain.

Cost-effective Variational Active Entity Resolution

no code implementations20 Nov 2020 Alex Bogatu, Norman W. Paton, Mark Douthwaite, Stuart Davie, Andre Freitas

In this paper, we set out to devise an entity resolution method that builds on the robustness conferred by deep autoencoders to reduce human-involvement costs.

Active Learning Entity Resolution +3

What is SemEval evaluating? A Systematic Analysis of Evaluation Campaigns in NLP

no code implementations EMNLP (Eval4NLP) 2021 Oskar Wysocki, Malina Florea, Andre Freitas

SemEval is the primary venue in the NLP community for the proposal of new challenges and for the systematic empirical evaluation of NLP systems.

Proceedings of the AAAI-20 Workshop on Intelligent Process Automation (IPA-20)

no code implementations15 Jan 2020 Dell Zhang, Andre Freitas, DaCheng Tao, Dawn Song

This is the Proceedings of the AAAI-20 Workshop on Intelligent Process Automation (IPA-20) which took place in New York, NY, USA on February 7th 2020.

Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks

no code implementations WS 2019 Mokanarangan Thayaparan, Marco Valentino, Viktor Schlegel, Andre Freitas

Recent advances in reading comprehension have resulted in models that surpass human performance when the answer is contained in a single, continuous passage of text.

Multi-hop Question Answering Question Answering +1

DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English and German

1 code implementation26 Sep 2019 Christina Niklaus, Matthias Cetto, Andre Freitas, Siegfried Handschuh

We introduce DisSim, a discourse-aware sentence splitting framework for English and German whose goal is to transform syntactically complex sentences into an intermediate representation that presents a simple and more regular structure which is easier to process for downstream semantic applications.

Text Simplification

MinWikiSplit: A Sentence Splitting Corpus with Minimal Propositions

no code implementations WS 2019 Christina Niklaus, Andre Freitas, Siegfried Handschuh

We compiled a new sentence splitting corpus that is composed of 203K pairs of aligned complex source and simplified target sentences.

Text Simplification

Transforming Complex Sentences into a Semantic Hierarchy

1 code implementation ACL 2019 Christina Niklaus, Matthias Cetto, Andre Freitas, Siegfried Handschuh

We present an approach for recursively splitting and rephrasing complex English sentences into a novel semantic hierarchy of simplified sentences, with each of them presenting a more regular structure that may facilitate a wide variety of artificial intelligence tasks, such as machine translation (MT) or information extraction (IE).

Machine Translation Text Simplification +1

DINFRA: A One Stop Shop for Computing Multilingual Semantic Relatedness

no code implementations16 May 2018 Siamak Barzegar, Juliano Efson Sales, Andre Freitas, Siegfried Handschuh, Brian Davis

This demonstration presents an infrastructure for computing multilingual semantic relatedness and correlation for twelve natural languages by using three distributional semantic models (DSMs).

Composite Semantic Relation Classification

no code implementations16 May 2018 Siamak Barzegar, Andre Freitas, Siegfried Handschuh, Brian Davis

Different semantic interpretation tasks such as text entailment and question answering require the classification of semantic relations between terms or entities within text.

BIG-bench Machine Learning Classification +3

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