Search Results for author: Yangming Li

Found 22 papers, 9 papers with code

Fine-grained Entity Typing without Knowledge Base

1 code implementation EMNLP 2021 Jing Qian, Yibin Liu, Lemao Liu, Yangming Li, Haiyun Jiang, Haisong Zhang, Shuming Shi

Existing work on Fine-grained Entity Typing (FET) typically trains automatic models on the datasets obtained by using Knowledge Bases (KB) as distant supervision.

Entity Typing Named Entity Recognition +1

Efficient Sub-structured Knowledge Distillation

1 code implementation9 Mar 2022 Wenye Lin, Yangming Li, Lemao Liu, Shuming Shi, Hai-Tao Zheng

Specifically, we transfer the knowledge from a teacher model to its student model by locally matching their predictions on all sub-structures, instead of the whole output space.

Knowledge Distillation Structured Prediction

Real-time Virtual Intraoperative CT for Image Guided Surgery

no code implementations5 Dec 2021 Yangming Li, Neeraja Konuthula, Ian M. Humphreys, Kris Moe, Blake Hannaford, Randall Bly

Purpose: This paper presents a scheme for generating virtual intraoperative CT scans in order to improve surgical completeness in Endoscopic Sinus Surgeries (ESS).

Real-time Informative Surgical Skill Assessment with Gaussian Process Learning

no code implementations5 Dec 2021 Yangming Li, Randall Bly, Sarah Akkina, Rajeev C. Saxena, Ian Humphreys, Mark Whipple, Kris Moe, Blake Hannaford

Different with classical surgical skill assessment algorithms, the proposed method 1) utilizes the kinematic features in surgical instrument relative movements, instead of using specific surgical tasks or the statistics to assess skills in real-time; 2) provide informative feedback, instead of a summative scores; 3) has the ability to incrementally learn from new data, instead of depending on a fixed dataset.

TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis

no code implementations31 Dec 2020 Haisong Zhang, Lemao Liu, Haiyun Jiang, Yangming Li, Enbo Zhao, Kun Xu, Linfeng Song, Suncong Zheng, Botong Zhou, Jianchen Zhu, Xiao Feng, Tao Chen, Tao Yang, Dong Yu, Feng Zhang, Zhanhui Kang, Shuming Shi

This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.

Named Entity Recognition NER

Interpretable NLG for Task-oriented Dialogue Systems with Heterogeneous Rendering Machines

no code implementations29 Dec 2020 Yangming Li, Kaisheng Yao

To address this problem, we propose a novel framework, heterogeneous rendering machines (HRM), that interprets how neural generators render an input dialogue act (DA) into an utterance.

Task-Oriented Dialogue Systems Text Generation

Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition

1 code implementation ICLR 2021 Yangming Li, Lemao Liu, Shuming Shi

Experiments on synthetic datasets and real-world datasets show that our model is robust to unlabeled entity problem and surpasses prior baselines.

Named Entity Recognition NER

Rewriter-Evaluator Framework for Neural Machine Translation

no code implementations28 Sep 2020 Yangming Li, Kaisheng Yao

We apply the proposed framework to improve the general NMT models (e. g., Transformer).

Machine Translation Translation

DCR-Net: A Deep Co-Interactive Relation Network for Joint Dialog Act Recognition and Sentiment Classification

no code implementations16 Aug 2020 Libo Qin, Wanxiang Che, Yangming Li, Minheng Ni, Ting Liu

In dialog system, dialog act recognition and sentiment classification are two correlative tasks to capture speakers intentions, where dialog act and sentiment can indicate the explicit and the implicit intentions separately.

Sentiment Analysis

Handling Rare Entities for Neural Sequence Labeling

no code implementations ACL 2020 Yangming Li, Han Li, Kaisheng Yao, Xiaolong Li

One great challenge in neural sequence labeling is the data sparsity problem for rare entity words and phrases.

Multi-Domain Spoken Language Understanding Using Domain- and Task-Aware Parameterization

no code implementations30 Apr 2020 Libo Qin, Minheng Ni, Yue Zhang, Wanxiang Che, Yangming Li, Ting Liu

Spoken language understanding has been addressed as a supervised learning problem, where a set of training data is available for each domain.

Spoken Language Understanding

LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images

1 code implementation10 Mar 2020 Shan Lin, Fangbo Qin, Yangming Li, Randall A. Bly, Kris S. Moe, Blake Hannaford

For live image segmentation, we first translate the live images to fake-cadaveric images with LC-GAN and then perform segmentation on the fake-cadaveric images with models trained on the real cadaveric dataset.

Image-to-Image Translation Semantic Segmentation +1

Towards Better Surgical Instrument Segmentation in Endoscopic Vision: Multi-Angle Feature Aggregation and Contour Supervision

1 code implementation25 Feb 2020 Fangbo Qin, Shan Lin, Yangming Li, Randall A. Bly, Kris S. Moe, Blake Hannaford

Accurate and real-time surgical instrument segmentation is important in the endoscopic vision of robot-assisted surgery, and significant challenges are posed by frequent instrument-tissue contacts and continuous change of observation perspective.

A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding

2 code implementations IJCNLP 2019 Libo Qin, Wanxiang Che, Yangming Li, Haoyang Wen, Ting Liu

In our framework, we adopt a joint model with Stack-Propagation which can directly use the intent information as input for slot filling, thus to capture the intent semantic knowledge.

Intent Detection Slot Filling +1

Simulation Results on Selector Adaptation in Behavior Trees

1 code implementation29 Jun 2016 Blake Hannaford, Danying Hu, Dianmu Zhang, Yangming Li

The "Selector" node of a BT tries alternative strategies (its children) and returns success only if all of its children return failure.


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