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Found 12 papers, 5 papers with code
The NiuTrans System for the WMT20 Quality Estimation Shared Task
This paper describes the submissions of the NiuTrans Team to the WMT 2020 Quality Estimation Shared Task.
The NiuTrans System for the WMT 2021 Efficiency Task
This paper describes the NiuTrans system for the WMT21 translation efficiency task.
Teaching Language Models to Self-Improve by Learning from Language Feedback
Aligning Large Language Models (LLMs) with human intentions and values is crucial yet challenging.
RankPrompt: Step-by-Step Comparisons Make Language Models Better Reasoners
Our experiments across 11 arithmetic and commonsense reasoning tasks show that RankPrompt significantly enhances the reasoning performance of ChatGPT and GPT-4, with improvements of up to 13%.
Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality Estimation
Given the significant resource allocation required for training and evaluating models, it is advantageous to have an efficient method for selecting high-quality IT data.
Bridging the Granularity Gap for Acoustic Modeling
While Transformer has become the de-facto standard for speech, modeling upon the fine-grained frame-level features remains an open challenge of capturing long-distance dependencies and distributing the attention weights.
The NiuTrans Machine Translation Systems for WMT21
This paper describes NiuTrans neural machine translation systems of the WMT 2021 news translation tasks.
The NiuTrans System for WNGT 2020 Efficiency Task
This paper describes the submissions of the NiuTrans Team to the WNGT 2020 Efficiency Shared Task.
The NiuTrans System for the WMT21 Efficiency Task
This paper describes the NiuTrans system for the WMT21 translation efficiency task (http://statmt. org/wmt21/efficiency-task. html).
RankNAS: Efficient Neural Architecture Search by Pairwise Ranking
This paper addresses the efficiency challenge of Neural Architecture Search (NAS) by formulating the task as a ranking problem.
Learning Architectures from an Extended Search Space for Language Modeling
Neural architecture search (NAS) has advanced significantly in recent years but most NAS systems restrict search to learning architectures of a recurrent or convolutional cell.
Improved Differentiable Architecture Search for Language Modeling and Named Entity Recognition
In this paper, we study differentiable neural architecture search (NAS) methods for natural language processing.
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