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05/07/2023
Laziness Is a Virtue When It Comes to Compositionality in Neural Semantic Parsing
Nearly all general-purpose neural semantic parsers generate logical form...
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03/30/2023
Learning in Factored Domains with Information-Constrained Visual Representations
Humans learn quickly even in tasks that contain complex visual informati...
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03/01/2022
AI Planning Annotation for Sample Efficient Reinforcement Learning
AI planning and Reinforcement Learning (RL) both solve sequential decisi...
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11/23/2020
Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games
This paper introduces an information-theoretic constraint on learned pol...
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10/09/2020
Deep RL With Information Constrained Policies: Generalization in Continuous Control
Biological agents learn and act intelligently in spite of a highly limit...
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06/16/2020
A Study of Compositional Generalization in Neural Models
Compositional and relational learning is a hallmark of human intelligenc...
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04/28/2020
Finding Macro-Actions with Disentangled Effects for Efficient Planning with the Goal-Count Heuristic
The difficulty of classical planning increases exponentially with search...
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04/29/2019
Routing Networks and the Challenges of Modular and Compositional Computation
Compositionality is a key strategy for addressing combinatorial complexi...
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09/06/2018
Logical Rule Induction and Theory Learning Using Neural Theorem Proving
A hallmark of human cognition is the ability to continually acquire and ...
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11/17/2017
Scalable Recollections for Continual Lifelong Learning
Given the recent success of Deep Learning applied to a variety of single...
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11/17/2017
Generation and Consolidation of Recollections for Efficient Deep Lifelong Learning
Deep lifelong learning systems need to efficiently manage resources to s...
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11/14/2017
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
A popular recent approach to answering open-domain questions is to first...
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11/03/2017
Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning
Multi-task learning (MTL) with neural networks leverages commonalities i...
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08/31/2017
R^3: Reinforced Reader-Ranker for Open-Domain Question Answering
In recent years researchers have achieved considerable success applying ...
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08/05/2017
e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations
In this paper we present a new dataset and user simulator e-QRAQ (explai...
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06/02/2016
