189 citations · 394 across the 29 of their papers we have counts for
29 papers
Evaluation Kidney Layer Segmentation on Whole Slide Imaging using Convolutional Neural Networks and Transformers
Muhao Liu, Chenyang Qi, Shunxing Bao +6
The segmentation of kidney layer structures, including cortex, outer stripe, inner stripe, and inner medulla within human kidney whole slide images (WSI) plays an essential role in…
SHINE: Syntax-augmented Hierarchical Interactive Encoder for Zero-shot Cross-lingual Information Extraction
Jun-Yu Ma, Jia-Chen Gu, Zhen-Hua Ling +3
Zero-shot cross-lingual information extraction(IE) aims at constructing an IE model for some low-resource target languages, given annotations exclusively in some rich-resource lang…
MADNet: Maximizing Addressee Deduction Expectation for Multi-Party Conversation Generation
Jia-Chen Gu, Chao-Hong Tan, Caiyuan Chu +4
Modeling multi-party conversations (MPCs) with graph neural networks has been proven effective at capturing complicated and graphical information flows. However, existing methods r…
GIFT: Graph-Induced Fine-Tuning for Multi-Party Conversation Understanding
Jia-Chen Gu, Zhen-Hua Ling, Quan Liu +2
Addressing the issues of who saying what to whom in multi-party conversations (MPCs) has recently attracted a lot of research attention. However, existing methods on MPC understand…
MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformer
Yunsong Zhou, Hongzi Zhu, Quan Liu +2
Mobile monocular 3D object detection (Mono3D) (e.g., on a vehicle, a drone, or a robot) is an important yet challenging task. Existing transformer-based offline Mono3D models adopt…
WIDER & CLOSER: Mixture of Short-channel Distillers for Zero-shot Cross-lingual Named Entity Recognition
Jun-Yu Ma, Beiduo Chen, Jia-Chen Gu +5
Zero-shot cross-lingual named entity recognition (NER) aims at transferring knowledge from annotated and rich-resource data in source languages to unlabeled and lean-resource data…
Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding
Quande Liu, Youpeng Wen, Jianhua Han +3
To bridge the gap between supervised semantic segmentation and real-world applications that acquires one model to recognize arbitrary new concepts, recent zero-shot segmentation at…
Omni-Seg: A Scale-aware Dynamic Network for Renal Pathological Image Segmentation
Ruining Deng, Quan Liu, Can Cui +9
Comprehensive semantic segmentation on renal pathological images is challenging due to the heterogeneous scales of the objects. For example, on a whole slide image (WSI), the cross…
Partner Matters! An Empirical Study on Fusing Personas for Personalized Response Selection in Retrieval-Based Chatbots
Jia-Chen Gu, Hui Liu, Zhen-Hua Ling +3
Persona can function as the prior knowledge for maintaining the consistency of dialogue systems. Most of previous studies adopted the self persona in dialogue whose response was ab…
SimTriplet: Simple Triplet Representation Learning with a Single GPU
Quan Liu, Peter C. Louis, Yuzhe Lu +9
Contrastive learning is a key technique of modern self-supervised learning. The broader accessibility of earlier approaches is hindered by the need of heavy computational resources…
ASIST: Annotation-free Synthetic Instance Segmentation and Tracking by Adversarial Simulations
Quan Liu, Isabella M. Gaeta, Mengyang Zhao +6
Background: The quantitative analysis of microscope videos often requires instance segmentation and tracking of cellular and subcellular objects. The traditional method consists of…
Learning to Retrieve Entity-Aware Knowledge and Generate Responses with Copy Mechanism for Task-Oriented Dialogue Systems
Chao-Hong Tan, Xiaoyu Yang, Zi'ou Zheng +7
Task-oriented conversational modeling with unstructured knowledge access, as track 1 of the 9th Dialogue System Technology Challenges (DSTC 9), requests to build a system to genera…
Exploring End-to-End Differentiable Natural Logic Modeling
Yufei Feng, Zi'ou Zheng, Quan Liu +2
We explore end-to-end trained differentiable models that integrate natural logic with neural networks, aiming to keep the backbone of natural language reasoning based on the natura…
GAN based Unsupervised Segmentation: Should We Match the Exact Number of Objects
Quan Liu, Isabella M. Gaeta, Bryan A. Millis +2
The unsupervised segmentation is an increasingly popular topic in biomedical image analysis. The basic idea is to approach the supervised segmentation task as an unsupervised synth…
Program Enhanced Fact Verification with Verbalization and Graph Attention Network
Xiaoyu Yang, Feng Nie, Yufei Feng +3
Performing fact verification based on structured data is important for many real-life applications and is a challenging research problem, particularly when it involves both symboli…
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking
Mengyang Zhao, Aadarsh Jha, Quan Liu +6
Recently, single-stage embedding based deep learning algorithms gain increasing attention in cell segmentation and tracking. Compared with the traditional "segment-then-associate"…
Pre-Trained and Attention-Based Neural Networks for Building Noetic Task-Oriented Dialogue Systems
Jia-Chen Gu, Tianda Li, Quan Liu +3
The NOESIS II challenge, as the Track 2 of the 8th Dialogue System Technology Challenges (DSTC 8), is the extension of DSTC 7. This track incorporates new elements that are vital f…
Filtering before Iteratively Referring for Knowledge-Grounded Response Selection in Retrieval-Based Chatbots
Jia-Chen Gu, Zhen-Hua Ling, Quan Liu +2
The challenges of building knowledge-grounded retrieval-based chatbots lie in how to ground a conversation on its background knowledge and how to match response candidates with bot…
Fine-Tuning BERT for Schema-Guided Zero-Shot Dialogue State Tracking
Yu-Ping Ruan, Zhen-Hua Ling, Jia-Chen Gu +1
We present our work on Track 4 in the Dialogue System Technology Challenges 8 (DSTC8). The DSTC8-Track 4 aims to perform dialogue state tracking (DST) under the zero-shot settings,…
Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
Jia-Chen Gu, Zhen-Hua Ling, Quan Liu
This paper proposes an utterance-to-utterance interactive matching network (U2U-IMN) for multi-turn response selection in retrieval-based chatbots. Different from previous methods…
Several Experiments on Investigating Pretraining and Knowledge-Enhanced Models for Natural Language Inference
Tianda Li, Xiaodan Zhu, Quan Liu +3
Natural language inference (NLI) is among the most challenging tasks in natural language understanding. Recent work on unsupervised pretraining that leverages unsupervised signals…
Exploring Unsupervised Pretraining and Sentence Structure Modelling for Winograd Schema Challenge
Yu-Ping Ruan, Xiaodan Zhu, Zhen-Hua Ling +3
Winograd Schema Challenge (WSC) was proposed as an AI-hard problem in testing computers' intelligence on common sense representation and reasoning. This paper presents the new stat…
The USTC-NEL Speech Translation system at IWSLT 2018
Dan Liu, Junhua Liu, Wu Guo +5
This paper describes the USTC-NEL system to the speech translation task of the IWSLT Evaluation 2018. The system is a conventional pipeline system which contains 3 modules: speech…
Building Sequential Inference Models for End-to-End Response Selection
Jia-Chen Gu, Zhen-Hua Ling, Yu-Ping Ruan +1
This paper presents an end-to-end response selection model for Track 1 of the 7th Dialogue System Technology Challenges (DSTC7). This task focuses on selecting the correct next utt…