Search Results for author: Yifan Gao

Found 34 papers, 15 papers with code

MBA-Net: SAM-driven Bidirectional Aggregation Network for Ovarian Tumor Segmentation

no code implementations8 Jul 2024 Yifan Gao, Wei Xia, Wenkui Wang, Xin Gao

In this paper, we propose MBA-Net, a novel architecture that integrates the powerful segmentation capabilities of the Segment Anything Model (SAM) with domain-specific knowledge for accurate and robust ovarian tumor segmentation.

Segmentation Tumor Segmentation

MEMORYLLM: Towards Self-Updatable Large Language Models

1 code implementation7 Feb 2024 Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian McAuley

We aim to build models containing a considerable portion of self-updatable parameters, enabling the model to integrate new knowledge effectively and efficiently.

Model Editing

Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns

1 code implementation NeurIPS 2023 Xin Liu, Zheng Li, Yifan Gao, Jingfeng Yang, Tianyu Cao, Zhengyang Wang, Bing Yin, Yangqiu Song

The goal of session-based recommendation in E-commerce is to predict the next item that an anonymous user will purchase based on the browsing and purchase history.

Attribute Session-Based Recommendations

Situated Natural Language Explanations

no code implementations27 Aug 2023 Zining Zhu, Haoming Jiang, Jingfeng Yang, Sreyashi Nag, Chao Zhang, Jie Huang, Yifan Gao, Frank Rudzicz, Bing Yin

Situated NLE provides a perspective and facilitates further research on the generation and evaluation of explanations.

Prompt Engineering

AutoPoster: A Highly Automatic and Content-aware Design System for Advertising Poster Generation

no code implementations2 Aug 2023 Jinpeng Lin, Min Zhou, Ye Ma, Yifan Gao, Chenxi Fei, Yangjian Chen, Zhang Yu, Tiezheng Ge

Meanwhile, to our knowledge, we propose the first poster generation dataset that includes visual attribute annotations for over 76k posters.


DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation

1 code implementation1 Jun 2023 Yifan Gao, Wei Xia, Dingdu Hu, Wenkui Wang, Xin Gao

Upon further investigation, we discovered that the degradation in performance was related to the coupling effect of inevitable poor prompts and mask generation.

Decoder Domain Generalization +4

Graph Reasoning for Question Answering with Triplet Retrieval

no code implementations30 May 2023 Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, Bing Yin

State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which are then fed into KG encoder, e. g. graph neural networks (GNNs), to model their local structures and integrated into language models for question answering.

Knowledge Graphs Question Answering +1

CCGen: Explainable Complementary Concept Generation in E-Commerce

no code implementations19 May 2023 Jie Huang, Yifan Gao, Zheng Li, Jingfeng Yang, Yangqiu Song, Chao Zhang, Zining Zhu, Haoming Jiang, Kevin Chen-Chuan Chang, Bing Yin

We propose and study Complementary Concept Generation (CCGen): given a concept of interest, e. g., "Digital Cameras", generating a list of complementary concepts, e. g., 1) Camera Lenses 2) Batteries 3) Camera Cases 4) Memory Cards 5) Battery Chargers.

SCOTT: Self-Consistent Chain-of-Thought Distillation

1 code implementation3 May 2023 Peifeng Wang, Zhengyang Wang, Zheng Li, Yifan Gao, Bing Yin, Xiang Ren

While CoT can yield dramatically improved performance, such gains are only observed for sufficiently large LMs.

counterfactual Counterfactual Reasoning +1

The ProfessionAl Go annotation datasEt (PAGE)

no code implementations3 Nov 2022 Yifan Gao, Danni Zhang, Haoyue Li

To the best of our knowledge, PAGE is the first dataset with extensive annotation in the game of Go.

Game of Go

An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI

no code implementations4 Oct 2022 Yifan Gao, Yin Dai, Fayu Liu, Weibing Chen, Lifu Shi

Second, considering that the segmentation model is prone to be disturbed by similar anatomical structures and make wrong predictions, we design anatomy-aware loss.

Anatomy Segmentation +1

Improving Task Generalization via Unified Schema Prompt

no code implementations5 Aug 2022 Wanjun Zhong, Yifan Gao, Ning Ding, Zhiyuan Liu, Ming Zhou, Jiahai Wang, Jian Yin, Nan Duan

Task generalization has been a long standing challenge in Natural Language Processing (NLP).

ProQA: Structural Prompt-based Pre-training for Unified Question Answering

1 code implementation NAACL 2022 Wanjun Zhong, Yifan Gao, Ning Ding, Yujia Qin, Zhiyuan Liu, Ming Zhou, Jiahai Wang, Jian Yin, Nan Duan

Furthermore, ProQA exhibits strong ability in both continual learning and transfer learning by taking the advantages of the structural prompt.

Continual Learning Few-Shot Learning +2

PGD: A Large-scale Professional Go Dataset for Data-driven Analytics

no code implementations30 Apr 2022 Yifan Gao

This paper creates the Professional Go Dataset (PGD), containing 98, 043 games played by 2, 148 professional players from 1950 to 2021.

Board Games

Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis

no code implementations24 Jan 2022 Yin Dai, Yifan Gao, Fayu Liu, Jun Fu

Recent works on Multimodal 3D Computer-aided diagnosis have demonstrated that obtaining a competitive automatic diagnosis model when a 3D convolution neural network (CNN) brings more parameters and medical images are scarce remains nontrivial and challenging.

Image Classification Medical Image Classification

TransMed: Transformers Advance Multi-modal Medical Image Classification

no code implementations10 Mar 2021 Yin Dai, Yifan Gao

To our best knowledge, this is the first work to apply transformers to medical image classification.

General Classification Image Classification +3

Open-Retrieval Conversational Machine Reading

1 code implementation17 Feb 2021 Yifan Gao, Jingjing Li, Chien-Sheng Wu, Michael R. Lyu, Irwin King

On our created OR-ShARC dataset, MUDERN achieves the state-of-the-art performance, outperforming existing single-passage conversational machine reading models as well as a new multi-passage conversational machine reading baseline by a large margin.

Discourse Segmentation Reading Comprehension +1

Leveraging WordNet Paths for Neural Hypernym Prediction

1 code implementation COLING 2020 Yejin Cho, Juan Diego Rodriguez, Yifan Gao, Katrin Erk

We formulate the problem of hypernym prediction as a sequence generation task, where the sequences are taxonomy paths in WordNet.


Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading

1 code implementation EMNLP 2020 Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu

Based on the learned EDU and entailment representations, we either reply to the user our final decision "yes/no/irrelevant" of the initial question, or generate a follow-up question to inquiry more information.

Decision Making Discourse Segmentation +3

EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

1 code implementation26 May 2020 Yifan Gao, Chien-Sheng Wu, Shafiq Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, Steven C. H. Hoi

The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions.

Decision Making Reading Comprehension +1

Non-linearity identification for construction workers' personality-safety behaviour predictive relationship using neural network and linear regression modelling

no code implementations11 Dec 2019 Yifan Gao, Vicente A. Gonzalez, Tak Wing Yiu, Guillermo Cabrera-Guerrerod

The latest literature has evidenced that there is within-population diversity that leads people's intended safety behaviours in the workplace, which are found to vary among individuals as a function of their personality traits.

Decision Making Diversity +1

Improving Question Generation With to the Point Context

no code implementations IJCNLP 2019 Jingjing Li, Yifan Gao, Lidong Bing, Irwin King, Michael R. Lyu

Question generation (QG) is the task of generating a question from a reference sentence and a specified answer within the sentence.

Question Generation Question-Generation +1

Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling

1 code implementation ACL 2019 Yifan Gao, Piji Li, Irwin King, Michael R. Lyu

The coreference alignment modeling explicitly aligns coreferent mentions in conversation history with corresponding pronominal references in generated questions, which makes generated questions interconnected to conversation history.

Question Answering Question Generation +2

Generating Distractors for Reading Comprehension Questions from Real Examinations

2 code implementations8 Sep 2018 Yifan Gao, Lidong Bing, Piji Li, Irwin King, Michael R. Lyu

We investigate the task of distractor generation for multiple choice reading comprehension questions from examinations.

Decoder Distractor Generation +3

Title-Guided Encoding for Keyphrase Generation

no code implementations26 Aug 2018 Wang Chen, Yifan Gao, Jiani Zhang, Irwin King, Michael R. Lyu

Keyphrase generation (KG) aims to generate a set of keyphrases given a document, which is a fundamental task in natural language processing (NLP).

Decoder Keyphrase Generation

Difficulty Controllable Generation of Reading Comprehension Questions

no code implementations10 Jul 2018 Yifan Gao, Lidong Bing, Wang Chen, Michael R. Lyu, Irwin King

We investigate the difficulty levels of questions in reading comprehension datasets such as SQuAD, and propose a new question generation setting, named Difficulty-controllable Question Generation (DQG).

Question Generation Question-Generation +2

Learning Multi-level Features For Sensor-based Human Action Recognition

no code implementations22 Nov 2016 Yan Xu, Zhengyang Shen, Xin Zhang, Yifan Gao, Shujian Deng, Yipei Wang, Yubo Fan, Eric I-Chao Chang

This paper proposes a multi-level feature learning framework for human action recognition using a single body-worn inertial sensor.

Action Recognition Temporal Action Localization

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