ServiceNow Research

Compositional Generalization

On the Compositional Generalization Gap of In-Context Learning
Pretrained large generative language models have shown great performance on many tasks, but exhibit low compositional generalization …
Conference on Empirical Methods in Natural Language Processing (EMNLP),  2022.
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Scaling up ML-based Black-box Planning with Partial STRIPS Models
Scaling up ML-based Black-box Planning with Partial STRIPS Models
A popular approach for sequential decision-making is to perform simulator-based search guided with Machine Learning (ML) methods like …
Workshop at International Join Conference on Artificial Intelligence (IJCAI),  2022.
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A Planning based Neural-Symbolic Approach for Embodied Instruction Following
A Planning based Neural-Symbolic Approach for Embodied Instruction Following
The ALFRED environment features embodied instruction following tasks in simulated home environments. However, end-to-end deep learning …
Workshop at the Conference on Computer Vision and Pattern Recognition (CVPR),  2022.
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Scaling up ML-based Black-box Planning with Partial STRIPS Models
Scaling up ML-based Black-box Planning with Partial STRIPS Models
A popular approach for sequential decision-making is to perform simulator-based search guided with Machine Learning (ML) methods like …
ICAPS'22 Workshop on Reliable Data-Driven Planning and Scheduling,  2022.
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Compositional Generalization in Dependency Parsing
Compositional Generalization in Dependency Parsing
Compositionality, or the ability to combine familiar units like words into novel phrases and sentences, has been the focus of intense …
Annual Meeting of the Association for Computational Linguistics (ACL),  2022.
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Object-centric Compositional Imagination for Visual Abstract Reasoning
Object-centric Compositional Imagination for Visual Abstract Reasoning
Like humans devoid of imagination, current machine learning systems lack the ability to adapt to new, unexpected situations by …
Workshop at the International Conference on Learning Representations (ICLR),  2022.
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Continual Learning via Local Module Composition
Continual Learning via Local Module Composition
Modularity is a compelling solution to continual learning (CL), the problem of modeling sequences of related tasks. Learning and then …
Conference on Neural Information Processing Systems (NeurIPS),  2021.
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Generative Compositional Augmentations for Scene Graph Prediction
Generative Compositional Augmentations for Scene Graph Prediction
Inferring objects and their relationships from an image in the form of a scene graph is useful in many applications at the intersection …
International Conference on Computer Vision (ICCV),  2021.
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