32 citations · 85 across the 50 of their papers we have counts for
9 papers · 1 filter
Graph-Induced Syntactic-Semantic Spaces in Transformer-Based Variational AutoEncoders
Yingji Zhang, Marco Valentino, Danilo S. Carvalho +2
The injection of syntactic information in Variational AutoEncoders (VAEs) has been shown to result in an overall improvement of performances and generalisation. An effective strate…
Multi-Operational Mathematical Derivations in Latent Space
Marco Valentino, Jordan Meadows, Lan Zhang +1
This paper investigates the possibility of approximating multiple mathematical operations in latent space for expression derivation. To this end, we introduce different multi-opera…
Controlling Equational Reasoning in Large Language Models with Prompt Interventions
Jordan Meadows, Marco Valentino, Andre Freitas
This paper investigates how hallucination rates in Large Language Models (LLMs) may be controlled via a symbolic data generation framework, exploring a fundamental relationship bet…
Estimating the Causal Effects of Natural Logic Features in Neural NLI Models
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. However, this is such a…
SemEval-2023 Task 7: Multi-Evidence Natural Language Inference for Clinical Trial Data
Maël Jullien, Marco Valentino, Hannah Frost +3
This paper describes the results of SemEval 2023 task 7 -- Multi-Evidence Natural Language Inference for Clinical Trial Data (NLI4CT) -- consisting of 2 tasks, a Natural Language I…
A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers
Jordan Meadows, Marco Valentino, Damien Teney +1
This paper proposes a methodology for generating and perturbing detailed derivations of equations at scale, aided by a symbolic engine, to evaluate the generalisability of Transfor…
Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitions
Marco Valentino, Danilo S. Carvalho, André Freitas
Natural language definitions possess a recursive, self-explanatory semantic structure that can support representation learning methods able to preserve explicit conceptual relation…
NLI4CT: Multi-Evidence Natural Language Inference for Clinical Trial Reports
Maël Jullien, Marco Valentino, Hannah Frost +3
How can we interpret and retrieve medical evidence to support clinical decisions? Clinical trial reports (CTR) amassed over the years contain indispensable information for the deve…
Interventional Probing in High Dimensions: An NLI Case Study
Julia Rozanova, Marco Valentino, Lucas Cordeiro +1
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 log…