Search Results for author: Xiangchen Song

Found 18 papers, 6 papers with code

ChemNER: Fine-Grained Chemistry Named Entity Recognition with Ontology-Guided Distant Supervision

1 code implementation EMNLP 2021 Xuan Wang, Vivian Hu, Xiangchen Song, Shweta Garg, Jinfeng Xiao, Jiawei Han

For example, chemistry research needs to study dozens to hundreds of distinct, fine-grained entity types, making consistent and accurate annotation difficult even for crowds of domain experts.

named-entity-recognition Named Entity Recognition +1

Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models

no code implementations30 Jan 2024 Yewen Fan, Nian Si, Xiangchen Song, Kun Zhang

In this paper, we introduce a novel metric framework, the Calibrated Loss Metric, designed to address this issue by reducing the variance present in its conventional counterpart.

Click-Through Rate Prediction

CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process

no code implementations25 Jan 2024 Guangyi Chen, Yifan Shen, Zhenhao Chen, Xiangchen Song, Yuewen Sun, Weiran Yao, Xiao Liu, Kun Zhang

Identifying the underlying time-delayed latent causal processes in sequential data is vital for grasping temporal dynamics and making downstream reasoning.

A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables

no code implementations18 Dec 2023 Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang

Most existing causal discovery methods rely on the assumption of no latent confounders, limiting their applicability in solving real-life problems.

Causal Discovery

Temporally Disentangled Representation Learning under Unknown Nonstationarity

1 code implementation NeurIPS 2023 Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric Xing, Kun Zhang

In unsupervised causal representation learning for sequential data with time-delayed latent causal influences, strong identifiability results for the disentanglement of causally-related latent variables have been established in stationary settings by leveraging temporal structure.

Disentanglement

Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders

no code implementations4 Mar 2023 Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu

Causal analysis for time series data, in particular estimating individualized treatment effect (ITE), is a key task in many real-world applications, such as finance, retail, healthcare, etc.

Causal Inference Irregular Time Series +2

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks

1 code implementation1 Nov 2022 Yue Yu, Xuan Kan, Hejie Cui, ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang

To better adapt GNNs for fMRI analysis, we propose TBDS, an end-to-end framework based on \underline{T}ask-aware \underline{B}rain connectivity \underline{D}AG (short for Directed Acyclic Graph) \underline{S}tructure generation for fMRI analysis.

Time Series Time Series Analysis

PLOT: Prompt Learning with Optimal Transport for Vision-Language Models

1 code implementation3 Oct 2022 Guangyi Chen, Weiran Yao, Xiangchen Song, Xinyue Li, Yongming Rao, Kun Zhang

To solve this problem, we propose to apply optimal transport to match the vision and text modalities.

TaxoEnrich: Self-Supervised Taxonomy Completion via Structure-Semantic Representations

no code implementations10 Feb 2022 Minhao Jiang, Xiangchen Song, Jieyu Zhang, Jiawei Han

Taxonomies are fundamental to many real-world applications in various domains, serving as structural representations of knowledge.

Position

Learning Multi-granularity User Intent Unit for Session-based Recommendation

1 code implementation25 Dec 2021 Jiayan Guo, Yaming Yang, Xiangchen Song, Yuan Zhang, Yujing Wang, Jing Bai, Yan Zhang

Specifically, we creatively propose Multi-granularity Intent Heterogeneous Session Graph which captures the interactions between different granularity intent units and relieves the burden of long-dependency.

Session-Based Recommendations

Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation

no code implementations5 Sep 2021 Yankai Chen, Yaming Yang, Yujing Wang, Jing Bai, Xiangchen Song, Irwin King

However, simply integrating KGs in current KG-based RS models is not necessarily a guarantee to improve the recommendation performance, which may even weaken the holistic model capability.

Click-Through Rate Prediction Knowledge-Aware Recommendation +1

Who Should Go First? A Self-Supervised Concept Sorting Model for Improving Taxonomy Expansion

no code implementations8 Apr 2021 Xiangchen Song, Jiaming Shen, Jieyu Zhang, Jiawei Han

Taxonomies have been widely used in various machine learning and text mining systems to organize knowledge and facilitate downstream tasks.

Taxonomy Expansion

Taxonomy Completion via Triplet Matching Network

1 code implementation6 Jan 2021 Jieyu Zhang, Xiangchen Song, Ying Zeng, Jiaze Chen, Jiaming Shen, Yuning Mao, Lei LI

Previous approaches focus on the taxonomy expansion, i. e. finding an appropriate hypernym concept from the taxonomy for a new query concept.

Taxonomy Expansion

BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks

no code implementations23 Oct 2020 Di Jin, Xiangchen Song, Zhizhi Yu, Ziyang Liu, Heling Zhang, Zhaomeng Cheng, Jiawei Han

We propose BiTe-GCN, a novel GCN architecture with bidirectional convolution of both topology and features on text-rich networks to solve these limitations.

Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision

no code implementations27 Mar 2020 Xuan Wang, Xiangchen Song, Bangzheng Li, Yingjun Guan, Jiawei Han

We created this CORD-NER dataset with comprehensive named entity recognition (NER) on the COVID-19 Open Research Dataset Challenge (CORD-19) corpus (2020-03-13).

named-entity-recognition Named Entity Recognition +1

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