Search Results for author: Dachun Sun

Found 9 papers, 2 papers with code

SCRAG: Social Computing-Based Retrieval Augmented Generation for Community Response Forecasting in Social Media Environments

no code implementations18 Apr 2025 Dachun Sun, You Lyu, Jinning Li, Yizhuo Chen, Tianshi Wang, Tomoyoshi Kimura, Tarek Abdelzaher

This paper introduces SCRAG, a prediction framework inspired by social computing, designed to forecast community responses to real or hypothetical social media posts.

Articles Public Relations +2

Uncovering Cross-Domain Recommendation Ability of Large Language Models

no code implementations10 Mar 2025 Xinyi Liu, Ruijie Wang, Dachun Sun, Dilek Hakkani-Tur, Tarek Abdelzaher

To bridge this gap, we propose LLM4CDR, a novel CDR pipeline that constructs context-aware prompts by leveraging users' purchase history sequences from a source domain along with shared features between source and target domains.

Recommendation Systems

Perturbation-based Graph Active Learning for Weakly-Supervised Belief Representation Learning

no code implementations24 Oct 2024 Dachun Sun, Ruijie Wang, Jinning Li, Ruipeng Han, Xinyi Liu, You Lyu, Tarek Abdelzaher

This paper addresses the problem of optimizing the allocation of labeling resources for semi-supervised belief representation learning in social networks.

Active Learning Data Augmentation +2

Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning

no code implementations13 Jun 2023 Ruijie Wang, Baoyu Li, Yichen Lu, Dachun Sun, Jinning Li, Yuchen Yan, Shengzhong Liu, Hanghang Tong, Tarek F. Abdelzaher

State-of-the-art methods fall short in the speculative reasoning ability, as they assume the correctness of a fact is solely determined by its presence in KG, making them vulnerable to false negative/positive issues.

Knowledge Graphs World Knowledge

Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs

no code implementations16 Oct 2022 Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek Abdelzaher

Second, the potentially dynamic distributions from the initially observable facts to the future facts ask for explicitly modeling the evolving characteristics of new entities.

Knowledge Graphs Meta-Learning

Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders

1 code implementation1 Oct 2021 Jinning Li, Huajie Shao, Dachun Sun, Ruijie Wang, Yuchen Yan, Jinyang Li, Shengzhong Liu, Hanghang Tong, Tarek Abdelzaher

Inspired by total correlation in information theory, we propose the Information-Theoretic Variational Graph Auto-Encoder (InfoVGAE) that learns to project both users and content items (e. g., posts that represent user views) into an appropriate disentangled latent space.

Representation Learning Stance Detection

Analyzing the Design Space of Re-opening Policies and COVID-19 Outcomes in the US

1 code implementation30 Apr 2020 Chaoqi Yang, Ruijie Wang, Fangwei Gao, Dachun Sun, Jiawei Tang, Tarek Abdelzaher

We further compare policies that rely on partial venue closure to policies that espouse wide-spread periodic testing instead (i. e., in lieu of social distancing).

Physics and Society Computers and Society Social and Information Networks

paper2repo: GitHub Repository Recommendation for Academic Papers

no code implementations13 Apr 2020 Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek Abdelzaher

Motivated by this trend, we describe a novel item-item cross-platform recommender system, $\textit{paper2repo}$, that recommends relevant repositories on GitHub that match a given paper in an academic search system such as Microsoft Academic.

Recommendation Systems

ControlVAE: Controllable Variational Autoencoder

no code implementations ICML 2020 Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher

Variational Autoencoders (VAE) and their variants have been widely used in a variety of applications, such as dialog generation, image generation and disentangled representation learning.

Diversity Image Generation +3

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