Search Results for author:
Found 22 papers, 5 papers with code
TinyBERT: Distilling BERT for Natural Language Understanding
To accelerate inference and reduce model size while maintaining accuracy, we first propose a novel Transformer distillation method that is specially designed for knowledge distillation (KD) of the Transformer-based models.
Ranked #1 on
Natural Language Inference
on MultiNLI Dev
DyLex: Incorporating Dynamic Lexicons into BERT for Sequence Labeling
Incorporating lexical knowledge into deep learning models has been proved to be very effective for sequence labeling tasks.
A Neural Multi-digraph Model for Chinese NER with Gazetteers
Gazetteers were shown to be useful resources for named entity recognition (NER).
Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding
Current researches on spoken language understanding (SLU) heavily are limited to a simple setting: the plain text-based SLU that takes the user utterance as input and generates its corresponding semantic frames (e. g., intent and slots).
Ranked #1 on
Semantic Frame Parsing
on ProSLU
A Unified Syntax-aware Framework for Semantic Role Labeling
Semantic role labeling (SRL) aims to recognize the predicate-argument structure of a sentence.
DM\_NLP at SemEval-2018 Task 8: neural sequence labeling with linguistic features
This paper describes our submissions for SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using NLP.
NLP\_HZ at SemEval-2018 Task 9: a Nearest Neighbor Approach
Hypernym discovery aims to discover the hypernym word sets given a hyponym word and proper corpus.
Ranked #3 on
Hypernym Discovery
on General
A Hybrid System for Chinese Grammatical Error Diagnosis and Correction
In the correction stage, candidates were generated by the three GEC models and then merged to output the final corrections for M and S types.
Alibaba at IJCNLP-2017 Task 1: Embedding Grammatical Features into LSTMs for Chinese Grammatical Error Diagnosis Task
This paper introduces Alibaba NLP team system on IJCNLP 2017 shared task No.
Ranked #1 on
2D Human Pose Estimation
on Alibaba Cluster Trace
(using extra training data)
Better Modeling of Incomplete Annotations for Named Entity Recognition
Supervised approaches to named entity recognition (NER) are largely developed based on the assumption that the training data is fully annotated with named entity information.
Neural Chinese Address Parsing
This paper introduces a new task {--} Chinese address parsing {--} the task of mapping Chinese addresses into semantically meaningful chunks.
DM\_NLP at SemEval-2018 Task 12: A Pipeline System for Toponym Resolution
This paper describes DM-NLP{'}s system for toponym resolution task at Semeval 2019.
Improving Task-Agnostic BERT Distillation with Layer Mapping Search
Comprehensive experiments on the evaluation benchmarks demonstrate that 1) layer mapping strategy has a significant effect on task-agnostic BERT distillation and different layer mappings can result in quite different performances; 2) the optimal layer mapping strategy from the proposed search process consistently outperforms the other heuristic ones; 3) with the optimal layer mapping, our student model achieves state-of-the-art performance on the GLUE tasks.
LightMBERT: A Simple Yet Effective Method for Multilingual BERT Distillation
The multilingual pre-trained language models (e. g, mBERT, XLM and XLM-R) have shown impressive performance on cross-lingual natural language understanding tasks.
Application of the unified control and detection framework to detecting stealthy integrity cyber-attacks on feedback control systems
It is demonstrated, in the unified framework of control and detection, that all kernel attacks can be structurally detected when not only the observer-based residual, but also the control signal based residual signals are generated and used for the detection purpose.
An alternative paradigm of fault diagnosis in dynamic systems: orthogonal projection-based methods
In this paper, we propose a new paradigm of fault diagnosis in dynamic systems as an alternative to the well-established observer-based framework.
Control theoretically explainable application of autoencoder methods to fault detection in nonlinear dynamic systems
The major efforts are made on the development of a control theoretic solution to the optimal fault detection problem, in which an analog concept to minimal sufficient statistic, the so-called lossless information compression, is introduced and proven for dynamic systems and fault detection specifications.
Controllable Image Captioning via Prompting
Despite the remarkable progress of image captioning, existing captioners typically lack the controllable capability to generate desired image captions, e. g., describing the image in a rough or detailed manner, in a factual or emotional view, etc.
Efficient Image Captioning for Edge Devices
On the other hand, we transfer the image-text retrieval design of CLIP to image captioning scenarios by devising a novel visual concept extractor and a cross-modal modulator.
High-resolution tomographic reconstruction of optical absorbance through scattering media using neural fields
Light scattering imposes a major obstacle for imaging objects seated deeply in turbid media, such as biological tissues and foggy air.
A study on fault diagnosis in nonlinear dynamic systems with uncertainties
It is demonstrated that the projection onto the manifold of uncertainty data, together with the correspondingly defined Bregman divergence, is also capable for fault detection.
