9 citations · 15 across the 6 of their papers we have counts for
6 papers
Log-Depth Recurrent Language Modeling
Yiqin Wang, Nuri Cingillioglu, Charles Pert
Language modeling using Transformers has become commonplace despite their fixed computational depth and quadratic runtime with respect to input tokens. Recurrent models on the othe…
Neuro-symbolic Rule Learning in Real-world Classification Tasks
Kexin Gu Baugh, Nuri Cingillioglu, Alessandra Russo
Neuro-symbolic rule learning has attracted lots of attention as it offers better interpretability than pure neural models and scales better than symbolic rule learning. A recent ap…
pix2rule: End-to-end Neuro-symbolic Rule Learning
Nuri Cingillioglu, Alessandra Russo
Humans have the ability to seamlessly combine low-level visual input with high-level symbolic reasoning often in the form of recognising objects, learning relations between them an…
HySTER: A Hybrid Spatio-Temporal Event Reasoner
Theophile Sautory, Nuri Cingillioglu, Alessandra Russo
The task of Video Question Answering (VideoQA) consists in answering natural language questions about a video and serves as a proxy to evaluate the performance of a model in scene…
Learning Invariants through Soft Unification
Nuri Cingillioglu, Alessandra Russo
Human reasoning involves recognising common underlying principles across many examples. The by-products of such reasoning are invariants that capture patterns such as "if someone w…
DeepLogic: Towards End-to-End Differentiable Logical Reasoning
Nuri Cingillioglu, Alessandra Russo
Combining machine learning with logic-based expert systems in order to get the best of both worlds are becoming increasingly popular. However, to what extent machine learning can a…