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An Exploration of Arbitrary-Order Sequence Labeling via Energy-Based Inference Networks
Many tasks in natural language processing involve predicting structured ...
10/06/2020 ∙ by Lifu Tu, et al. ∙
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An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models
Recent work has shown that pre-trained language models such as BERT impr...
07/14/2020 ∙ by Lifu Tu, et al. ∙
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ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation
We propose to train a non-autoregressive machine translation model to mi...
05/02/2020 ∙ by Lifu Tu, et al. ∙
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Improving Joint Training of Inference Networks and Structured Prediction Energy Networks
Deep energy-based models are powerful, but pose challenges for learning ...
11/07/2019 ∙ by Lifu Tu, et al. ∙
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Generating Diverse Story Continuations with Controllable Semantics
We propose a simple and effective modeling framework for controlled gene...
09/30/2019 ∙ by Lifu Tu, et al. ∙
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Benchmarking Approximate Inference Methods for Neural Structured Prediction
Exact structured inference with neural network scoring functions is comp...
04/01/2019 ∙ by Lifu Tu, et al. ∙
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Learning Approximate Inference Networks for Structured Prediction
Structured prediction energy networks (SPENs; Belanger & McCallum 2016) ...
03/09/2018 ∙ by Lifu Tu, et al. ∙
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Learning to Embed Words in Context for Syntactic Tasks
We present models for embedding words in the context of surrounding word...
06/09/2017 ∙ by Lifu Tu, et al. ∙
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Network Inference by Learned Node-Specific Degree Prior
We propose a novel method for network inference from partially observed ...
02/07/2016 ∙ by Qingming Tang, et al. ∙
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