Marco Valentino | DeepAI

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∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 09/30/2020

Explainable Natural Language Reasoning via Conceptual Unification

This paper presents an abductive framework for multi-hop and interpretab...

0 Marco Valentino, et al. ∙

∙ 03/31/2020

Unification-based Reconstruction of Explanations for Science Questions

The paper presents a framework to reconstruct explanations for multiple ...

0 Marco Valentino, et al. ∙

∙ 03/10/2020

A Framework for Evaluation of Machine Reading Comprehension Gold Standards

Machine Reading Comprehension (MRC) is the task of answering a question ...

0 Viktor Schlegel, et al. ∙

∙ 10/01/2019

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

Recent advances in reading comprehension have resulted in models that su...

0 Mokanarangan Thayaparan, et al. ∙

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