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Found 17 papers, 6 papers with code
DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset
This paper describes in detail the construction process and data statistics of DuSQL.
End-to-end Speech Translation System Description of LIT for IWSLT 2019
We propose layer-tied self-attention for end-to-end speech translation.
LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models
We introduce LongSkywork, a long-context Large Language Model (LLM) capable of processing up to 200, 000 tokens.
Graph Attention-Based Symmetry Constraint Extraction for Analog Circuits
In recent years, analog circuits have received extensive attention and are widely used in many emerging applications.
IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models
Then, we pair each sample with a bias indicator representing its bias degree, and use these extended samples to train a sample generator.
Skywork: A More Open Bilingual Foundation Model
In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3. 2 trillion tokens drawn from both English and Chinese texts.
SkyMath: Technical Report
Large language models (LLMs) have shown great potential to solve varieties of natural language processing (NLP) tasks, including mathematical reasoning.
A Simple yet Effective Self-Debiasing Framework for Transformer Models
In this way, the top-layer sentence representation will be trained to ignore the common biased features encoded by the low-layer sentence representation and focus on task-relevant unbiased features.
SeSQL: Yet Another Large-scale Session-level Chinese Text-to-SQL Dataset
As the first session-level Chinese dataset, CHASE contains two separate parts, i. e., 2, 003 sessions manually constructed from scratch (CHASE-C), and 3, 456 sessions translated from English SParC (CHASE-T).
An Interpretability Evaluation Benchmark for Pre-trained Language Models
To fill in the gap, we propose a novel evaluation benchmark providing with both English and Chinese annotated data.
A Fine-grained Interpretability Evaluation Benchmark for Neural NLP
Based on this benchmark, we conduct experiments on three typical models with three saliency methods, and unveil their strengths and weakness in terms of interpretability.
Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Loss
Grammar-based parsers have achieved high performance in the cross-domain text-to-SQL parsing task, but suffer from low decoding efficiency due to the much larger number of actions for grammar selection than that of tokens in SQL queries.
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation
Therefore, in order to systematically evaluate the factors for building trustworthy systems, we propose a novel and well-annotated sentiment analysis dataset to evaluate robustness and interpretability.
Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing
For better distribution matching, we require that at least 80% of SQL patterns in the training data are covered by generated queries.
A Practical Chinese Dependency Parser Based on A Large-scale Dataset
DDParser is extended on the graph-based biaffine parser to accommodate to the characteristics of Chinese dataset.
Image Aesthetics Prediction Using Multiple Patches Preserving the Original Aspect Ratio of Contents
The spread of social networking services has created an increasing demand for selecting, editing, and generating impressive images.
LIT Team's System Description for Japanese-Chinese Machine Translation Task in IWSLT 2020
This paper describes the LIT Team{'}s submission to the IWSLT2020 open domain translation task, focusing primarily on Japanese-to-Chinese translation direction.
