Search Results for author: Stephen Pulman

Found 19 papers, 2 papers with code

Feedback Effect in User Interaction with Intelligent Assistants: Delayed Engagement, Adaption and Drop-out

no code implementations17 Mar 2023 Zidi Xiu, Kai-Chen Cheng, David Q. Sun, Jiannan Lu, Hadas Kotek, Yuhan Zhang, Paul McCarthy, Christopher Klein, Stephen Pulman, Jason D. Williams

Next, we expand the time horizon to examine behavior changes and show that as users discover the limitations of the IA's understanding and functional capabilities, they learn to adjust the scope and wording of their requests to increase the likelihood of receiving a helpful response from the IA.

Generalized Reinforcement Meta Learning for Few-Shot Optimization

no code implementations4 May 2020 Raviteja Anantha, Stephen Pulman, Srinivas Chappidi

We present a generic and flexible Reinforcement Learning (RL) based meta-learning framework for the problem of few-shot learning.

Decoder Few-Shot Learning +1

Lattice-based Improvements for Voice Triggering Using Graph Neural Networks

no code implementations25 Jan 2020 Pranay Dighe, Saurabh Adya, Nuoyu Li, Srikanth Vishnubhotla, Devang Naik, Adithya Sagar, Ying Ma, Stephen Pulman, Jason Williams

A pure trigger-phrase detector model doesn't fully utilize the intent of the user speech whereas by using the complete decoding lattice of user audio, we can effectively mitigate speech not intended for the smart assistant.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Deep Learning for Answer Sentence Selection

2 code implementations4 Dec 2014 Lei Yu, Karl Moritz Hermann, Phil Blunsom, Stephen Pulman

Answer sentence selection is the task of identifying sentences that contain the answer to a given question.

Feature Engineering Open-Domain Question Answering +1

Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras

no code implementations23 Jan 2014 Dimitri Kartsaklis, Mehrnoosh Sadrzadeh, Stephen Pulman, Bob Coecke

They also provide semantics for Lambek's pregroup algebras, applied to formalizing the grammatical structure of natural language, and are implicit in a distributional model of word meaning based on vector spaces.

A quantum teleportation inspired algorithm produces sentence meaning from word meaning and grammatical structure

no code implementations2 May 2013 Stephen Clark, Bob Coecke, Edward Grefenstette, Stephen Pulman, Mehrnoosh Sadrzadeh

We discuss an algorithm which produces the meaning of a sentence given meanings of its words, and its resemblance to quantum teleportation.


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