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EnvEdit: Environment Editing for Vision-and-Language Navigation ...
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Homepage2Vec: Language-Agnostic Website Embedding and Classification ...
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Multilinguals at SemEval-2022 Task 11: Transformer Based Architecture for Complex NER ...
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A new approach to calculating BERTScore for automatic assessment of translation quality ...
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A New Generation of Perspective API: Efficient Multilingual Character-level Transformers ...
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ViWOZ: A Multi-Domain Task-Oriented Dialogue Systems Dataset For Low-resource Language ...
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EAG: Extract and Generate Multi-way Aligned Corpus for Complete Multi-lingual Neural Machine Translation ...
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Learning Bidirectional Translation between Descriptions and Actions with Small Paired Data ...
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Abstract:
This study achieved bidirectional translation between descriptions and actions using small paired data. The ability to mutually generate descriptions and actions is essential for robots to collaborate with humans in their daily lives. The robot is required to associate real-world objects with linguistic expressions, and large-scale paired data are required for machine learning approaches. However, a paired dataset is expensive to construct and difficult to collect. This study proposes a two-stage training method for bidirectional translation. In the proposed method, we train recurrent autoencoders (RAEs) for descriptions and actions with a large amount of non-paired data. Then, we fine-tune the entire model to bind their intermediate representations using small paired data. Because the data used for pre-training do not require pairing, behavior-only data or a large language corpus can be used. We experimentally evaluated our method using a paired dataset consisting of motion-captured actions and ... : 8 pages, 7 figures. Submitted to RA-L (IEEE Robotics and Automation Letters) with IROS 2022 Option. An accompanying video is available at https://youtu.be/YlxM_kw6YLE ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG; Robotics cs.RO
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URL: https://dx.doi.org/10.48550/arxiv.2203.04218 https://arxiv.org/abs/2203.04218
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A Feasibility Study of Answer-Agnostic Question Generation for Education ...
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Language Generation for Broad-Coverage, Explainable Cognitive Systems ...
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Regional Negative Bias in Word Embeddings Predicts Racial Animus--but only via Name Frequency ...
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Grounding Hindsight Instructions in Multi-Goal Reinforcement Learning for Robotics ...
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Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit Complexity ...
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Curriculum: A Broad-Coverage Benchmark for Linguistic Phenomena in Natural Language Understanding ...
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