| Challenge: | Tasks are a fundamental unit of work in the daily lives of people, who are increasingly using digital means to keep track of, organize, triage, and act on them. |
| Approach: | They compile and release a large-scale dataset that captures location and time for tasks and a BERT-fine-tuned model that predicts task co-occurrence. |
| Outcome: | The proposed framework captures location and time, and predicts task co-occurrence with a BERT fine-tuned model outperforming baselines. |
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| Challenge: | Existing studies on term annotation show that even experts differ in their understanding of termhood . |
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Task Compass: Scaling Multi-task Pre-training with Task Prefix (2022.findings-emnlp)
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Zhuosheng Zhang, Shuohang Wang, Yichong Xu, Yuwei Fang, Wenhao Yu, Yang Liu, Hai Zhao, Chenguang Zhu, Michael Zeng
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Learning to Decompose and Organize Complex Tasks (2021.naacl-main)
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| Challenge: | Using a novel end-to-end pipeline, we propose a solution that consumes a complex task and induces 'dependency graphs' from unstructured text to represent sub-tasks and their relationships. |
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| Challenge: | Existing approaches to label annotation are labor-intensive and time-consuming. |
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| Challenge: | a tutorial on task instruction is aimed at researchers and practitioners interested in NLP generalization . labeled examples are unlikely to be available in large numbers or do not exist . |
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LLM-Driven Multi-Perspective Location Completion for Next Location Prediction (2026.findings-acl)
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Multi-Task Networks with Universe, Group, and Task Feature Learning (P19-1)
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| Challenge: | In multi-task learning, multiple related tasks are learned together. |
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PRESTO: A Multilingual Dataset for Parsing Realistic Task-Oriented Dialogs (2023.emnlp-main)
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Rahul Goel, Waleed Ammar, Aditya Gupta, Siddharth Vashishtha, Motoki Sano, Faiz Surani, Max Chang, HyunJeong Choe, David Greene, Chuan He, Rattima Nitisaroj, Anna Trukhina, Shachi Paul, Pararth Shah, Rushin Shah, Zhou Yu
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