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Found 15 papers, 5 papers with code
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on.
Visual Cues and Error Correction for Translation Robustness
Neural Machine Translation models are sensitive to noise in the input texts, such as misspelled words and ungrammatical constructions.
Test-Time Personalization with Meta Prompt for Gaze Estimation
Despite the recent remarkable achievement in gaze estimation, efficient and accurate personalization of gaze estimation without labels is a practical problem but rarely touched on in the literature.
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-Translation
Neural Machine Translation (NMT) models have been proved strong when translating clean texts, but they are very sensitive to noise in the input.
Exploring Model Consensus to Generate Translation Paraphrases
This paper describes our submission to the 2020 Duolingo Shared Task on Simultaneous Translation And Paraphrase for Language Education (STAPLE).
Video Restoration Against Yin-Yang Phasing
A common video degradation problem, which is largely untreated in literature, is what we call Yin-Yang Phasing (YYP).
A Comparison on Fine-grained Pre-trained Embeddings for the WMT19Chinese-English News Translation Task
This paper describes our submission to the WMT 2019 Chinese-English (zh-en) news translation shared task.
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation
Neural Machine Translation (NMT) models have been proved strong when translating clean texts, but they are very sensitive to noise in the input.
Design and Performance Evaluation of Joint Sensing and Communication Integrated System for 5G MmWave Enabled CAVs
Finally, both simulation and hardware testbed are designed, and the results show that the proposed CTRA algorithm can improve the radar total mutual information by 26%, and the feasibility of the proposed JSCIS is achieved with an acceptable radar ranging accuracy within 0. 25 m, as well as a stable data rate of 2. 8 Gbps using the 28 GHz mmWave frequency band.
Findings of the WMT 2020 Shared Task on Machine Translation Robustness
We report the findings of the second edition of the shared task on improving robustness in Machine Translation (MT).
Towards a Better Understanding of Noise in Natural Language Processing
In this paper, we propose a definition and taxonomy of various types of non-standard textual content – generally referred to as “noise” – in Natural Language Processing (NLP).
Findings of the WMT 2021 Shared Task on Quality Estimation
We report the results of the WMT 2021 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the word and sentence levels.
ICL’s Submission to the WMT21 Critical Error Detection Shared Task
This paper presents Imperial College London’s submissions to the WMT21 Quality Estimation (QE) Shared Task 3: Critical Error Detection.
Ensemble Multi-Relational Graph Neural Networks
This EMR optimization objective is able to derive an iterative updating rule, which can be formalized as an ensemble message passing (EnMP) layer with multi-relations.
Evaluating Large Language Models with Runtime Behavior of Program Execution
Typically, they focus on predicting the input and output of a program, ignoring the evaluation of the intermediate behavior during program execution, as well as the logical consistency (e. g., the model should not give the correct output if the prediction of execution path is wrong) when performing the reasoning.
