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Found 10 papers, 0 papers with code
Domain-specific knowledge distillation yields smaller and better models for conversational commerce
We demonstrate that knowledge distillation can be used not only to reduce model size, but to simultaneously adapt a contextual language model to a specific domain.
Quantum Natural Language Processing
In this context, we argue that "hallucinations" in modern artificial intelligence systems are a misunderstanding of the way facts are conceptualized: language can express many plausible hypotheses, of which only a few become actual.
Spatial Entity Resolution between Restaurant Locations and Transportation Destinations in Southeast Asia
As a tech company, Grab has expanded from transportation to food delivery, aiming to serve Southeast Asia with hyperlocalized applications.
Quantum Circuit Components for Cognitive Decision-Making
The claim is not that the human brain uses qubits and quantum circuits explicitly (just like the use of Boolean set theory does not require the brain to be using classical bits), but that the mathematics shared between quantum cognition and quantum computing motivates the exploration of quantum computers for cognition modeling.
Near-Term Advances in Quantum Natural Language Processing
This paper describes experiments showing that some tasks in natural language processing (NLP) can already be performed using quantum computers, though so far only with small datasets.
Actionable Conversational Quality Indicators for Improving Task-Oriented Dialog Systems
Automatic dialog systems have become a mainstream part of online customer service.
Language Identification with a Reciprocal Rank Classifier
The key finding for language classification is that ranked lists of words and frequencies of characters form a sufficient and robust representation of the regularities of key languages and their orthographies.
Should Semantic Vector Composition be Explicit? Can it be Linear?
The second considers whether semantic vector composition should be explicitly described mathematically, or whether it can be a model-internal side-effect of training a neural network.
Quantum Mathematics in Artificial Intelligence
In the decade since 2010, successes in artificial intelligence have been at the forefront of computer science and technology, and vector space models have solidified a position at the forefront of artificial intelligence.
Bringing Order to Neural Word Embeddings with Embeddings Augmented by Random Permutations (EARP)
Word order is clearly a vital part of human language, but it has been used comparatively lightly in distributional vector models.
