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Found 22 papers, 5 papers with code
The NiuTrans System for the WMT 2021 Efficiency Task
This paper describes the NiuTrans system for the WMT21 translation efficiency task.
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.
Fault-Aware Neural Code Rankers
Large language models (LLMs) have demonstrated an impressive ability to generate code for various programming tasks.
Learning from Self-Sampled Correct and Partially-Correct Programs
Program synthesis aims to generate executable programs that are consistent with the user specification.
Towards Reliable and Explainable AI Model for Solid Pulmonary Nodule Diagnosis
However, detection and accurate diagnosis of pulmonary nodules depend heavily on the experiences of radiologists and can be a heavy workload for them.
ADD 2022: the First Audio Deep Synthesis Detection Challenge
Audio deepfake detection is an emerging topic, which was included in the ASVspoof 2021.
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 the WMT21 Efficiency Task
This paper describes the NiuTrans system for the WMT21 translation efficiency task (http://statmt. org/wmt21/efficiency-task. html).
The NiuTrans System for WNGT 2020 Efficiency Task
This paper describes the submissions of the NiuTrans Team to the WNGT 2020 Efficiency Shared Task.
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.
Continual Learning for Fake Audio Detection
However, fine-tuning leads to performance degradation on previous data.
Half-Truth: A Partially Fake Audio Detection Dataset
Diverse promising datasets have been designed to hold back the development of fake audio detection, such as ASVspoof databases.
Falx: Synthesis-Powered Visualization Authoring
Modern visualization tools aim to allow data analysts to easily create exploratory visualizations.
Human-Computer Interaction Programming Languages
Organ Segmentation From Full-size CT Images Using Memory-Efficient FCN
In this paper, we present a memory-efficient FCN to tackle the high GPU memory demand challenge in organ segmentation problem from clinical CT images.
Scout: Rapid Exploration of Interface Layout Alternatives through High-Level Design Constraints
Although exploring alternatives is fundamental to creating better interface designs, current processes for creating alternatives are generally manual, limiting the alternatives a designer can explore.
Learning Transferable Graph Exploration
We propose a `learning to explore' framework where we learn a policy from a distribution of environments.
Precise Estimation of Renal Vascular Dominant Regions Using Spatially Aware Fully Convolutional Networks, Tensor-Cut and Voronoi Diagrams
Then we generate a Voronoi diagram to estimate the renal vascular dominant regions based on the segmented kidney and renal arteries.
Knowing When to Stop: Evaluation and Verification of Conformity to Output-size Specifications
This behavior can have severe consequences such as usage of increased computation and induce faults in downstream modules that expect outputs of a certain length.
Robust Text-to-SQL Generation with Execution-Guided Decoding
We consider the problem of neural semantic parsing, which translates natural language questions into executable SQL queries.
Natural Language to Structured Query Generation via Meta-Learning
In conventional supervised training, a model is trained to fit all the training examples.
Ranked #7 on
Code Generation
on WikiSQL
NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System
We present new data and semantic parsing methods for the problem of mapping English sentences to Bash commands (NL2Bash).
Pointing Out SQL Queries From Text
We present a system that allows for querying data tables using natural language questions, where the system translates the question into an executable SQL query.
