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1
EmailSum: Abstractive Email Thread Summarization ...
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2
Generation-Augmented Retrieval for Open-Domain Question Answering ...
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3
GO FIGURE: A Meta Evaluation of Factuality in Summarization ...
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4
UnitedQA: A Hybrid Approach for Open Domain Question Answering ...
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5
SOLOIST: Building Task Bots at Scale with Transfer Learning and Machine Teaching ...
Abstract: Read paper: N/A Abstract: We present a new method SOLOIST that uses transfer learning and machine teaching to build task bots at scale. We parameterize classical modular task-oriented dialog systems using a Transformer-based auto-regressive language model, which subsumes different dialog modules into a single neural model. We pre-train, on heterogeneous dialog corpora, a task-grounded response generation model, which can generate dialog responses grounded in user goals and real-world knowledge for task completion. The pre-trained model can be efficiently adapted to accomplish new tasks with a handful of task-specific dialogs via machine teaching, where training samples are generated by human teachers interacting with the system. Experiments show that (i) SOLOIST creates new state-of-the-art on well-studied task-oriented dialog benchmarks, including CamRest676 and MultiWOZ; (ii) in the few-shot fine-tuning settings, SOLOIST significantly outperforms existing methods, and (iii) the use of machine teaching ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/26055-soloist-building-task-bots-at-scale-with-transfer-learning-and-machine-teaching
https://dx.doi.org/10.48448/ka1j-qw19
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6
Reader-Guided Passage Reranking for Open-Domain Question Answering ...
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RADDLE: An Evaluation Benchmark and Analysis Platform for Robust Task-oriented Dialog Systems ...
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