64 citations · 239 across the 40 of their papers we have counts for
44 papers
Language Modeling Using Tensor Trains
Zhan Su, Yuqin Zhou, Fengran Mo +1
We propose a novel tensor network language model based on the simplest tensor network (i.e., tensor trains), called `Tensor Train Language Model' (TTLM). TTLM represents sentences…
Mixture of Latent Experts Using Tensor Products
Zhan Su, Fengran Mo, Prayag Tiwari +3
In multi-task learning, the conventional approach involves training a model on multiple tasks simultaneously. However, the training signals from different tasks can interfere with…
Faithfulness Tests for Natural Language Explanations
Pepa Atanasova, Oana-Maria Camburu, Christina Lioma +3
Explanations of neural models aim to reveal a model's decision-making process for its predictions. However, recent work shows that current methods giving explanations such as salie…
On representations of real numbers and the computational complexity of converting between such representations
Amir M. Ben-Amram, Lars Kristiansen, Jakob Grue Simonsen
We study the computational complexity of converting one representation of real numbers into another representation. Typical examples of representations are Cauchy sequences, base-1…
Principled Multi-Aspect Evaluation Measures of Rankings
Maria Maistro, Lucas Chaves Lima, Jakob Grue Simonsen +1
Information Retrieval evaluation has traditionally focused on defining principled ways of assessing the relevance of a ranked list of documents with respect to a query. Several met…
Fact Checking with Insufficient Evidence
Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma +1
Automating the fact checking (FC) process relies on information obtained from external sources. In this work, we posit that it is crucial for FC models to make veracity predictions…