4 citations · 13 across the 16 of their papers we have counts for
12 papers · 1 filter
Reasoning with Natural Language Explanations
Marco Valentino, André Freitas
Explanation constitutes an archetypal feature of human rationality, underpinning learning and generalisation, and representing one of the media supporting scientific discovery and…
SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials
Mael Jullien, Marco Valentino, André Freitas
Large Language Models (LLMs) are at the forefront of NLP achievements but fall short in dealing with shortcut learning, factual inconsistency, and vulnerability to adversarial inpu…
A Differentiable Integer Linear Programming Solver for Explanation-Based Natural Language Inference
Mokanarangan Thayaparan, Marco Valentino, André Freitas
Integer Linear Programming (ILP) has been proposed as a formalism for encoding precise structural and semantic constraints for Natural Language Inference (NLI). However, traditiona…
Estimating the Causal Effects of Natural Logic Features in Transformer-Based NLI Models
Julia Rozanova, Marco Valentino, André Freitas
Rigorous evaluation of the causal effects of semantic features on language model predictions can be hard to achieve for natural language reasoning problems. However, this is such a…
Enhancing Ethical Explanations of Large Language Models through Iterative Symbolic Refinement
Xin Quan, Marco Valentino, Louise A. Dennis +1
An increasing amount of research in Natural Language Inference (NLI) focuses on the application and evaluation of Large Language Models (LLMs) and their reasoning capabilities. Des…
Improving Semantic Control in Discrete Latent Spaces with Transformer Quantized Variational Autoencoders
Yingji Zhang, Danilo S. Carvalho, Marco Valentino +2
Achieving precise semantic control over the latent spaces of Variational AutoEncoders (VAEs) holds significant value for downstream tasks in NLP as the underlying generative mechan…