Relation Linking for Wikidata Using Bag of Distribution Representation. - Xi Yang; Shiya Ren; Yuan Li 050; Ke Shen 003; Zhixing Li; Guoyin Wang 001 (NLPCC, 2017)

NEARM: Natural Language Enhanced Association Rules Mining. - Shiya Ren; Zhixing Li; Huaming Wang; Yuan Li 050; Ke Shen 003; Sijie Cheng (ICDM Workshops, 2018)

基于非结构化文本增强关联规则的知识推理方法 (Knowledge Reasoning Method Based on Unstructured Text-enhanced Association Rules). - Zhixing Li; Shiya Ren; Huaming Wang; Ke Shen 003 (计算机科学, 2019)

Do Fine-tuned Commonsense Language Models Really Generalize? - Mayank Kejriwal; Ke Shen 003 (CoRR, 2020)

A Data-Driven Study of Commonsense Knowledge using the ConceptNet Knowledge Base. - Ke Shen 003; Mayank Kejriwal (CoRR, 2020)

Unsupervised real-time induction and interactive visualization of taxonomies over domain-specific concepts. - Mayank Kejriwal; Ke Shen 003 (ASONAM, 2021)

On the Generalization Abilities of Fine-Tuned Commonsense Language Representation Models. - Ke Shen 003; Mayank Kejriwal (SGAI Conf., 2021)

An evaluation and annotation methodology for product category matching in e-commerce. - Mayank Kejriwal; Ke Shen 003; Chien-Chun Ni; Nicolas Torzec (Comput. Ind., 2021)

Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks? - Mayank Kejriwal; Ke Shen 003 (CoRR, 2022)

A Theoretically Grounded Benchmark for Evaluating Machine Commonsense. - Henrique Santos 002; Ke Shen 003; Alice M. Mulvehill; Yasaman Razeghi; Deborah L. McGuinness; Mayank Kejriwal (CoRR, 2022)

Understanding Prior Bias and Choice Paralysis in Transformer-based Language Representation Models through Four Experimental Probes. - Ke Shen 003; Mayank Kejriwal (CoRR, 2022)

Understanding Substructures in Commonsense Relations in ConceptNet. - Ke Shen 003; Mayank Kejriwal (CoRR, 2022)

Transfer-based taxonomy induction over concept labels. - Mayank Kejriwal; Ke Shen 003; Chien-Chun Ni; Nicolas Torzec (Eng. Appl. Artif. Intell., 2022)

Context-Rich Evaluation of Machine Common Sense. - Mayank Kejriwal; Henrique Santos 002; Ke Shen 003; Alice M. Mulvehill; Deborah L. McGuinness (AGI, 2023)

An Analytical Approximation of Simplicial Complex Distributions in Communication Networks. - Ke Shen 003; Mayank Kejriwal (COMPLEX NETWORKS (4), 2023)

Substructure Discovery in Commonsense Relations Using Graph Representation Learning. - Ke Shen 003; Mayank Kejriwal (IntelliSys (1), 2023)

A Formalism and Approach for Improving Robustness of Large Language Models Using Risk-Adjusted Confidence Scores. - Ke Shen 003; Mayank Kejriwal (CoRR, 2023)

TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. - Henrique Santos 002; Ke Shen 003; Alice M. Mulvehill; Mayank Kejriwal; Deborah L. McGuinness (Zenodo, 2023)

TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. - Henrique Santos 002; Ke Shen 003; Alice M. Mulvehill; Mayank Kejriwal; Deborah L. McGuinness (Zenodo, 2023)

TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. - Henrique Santos 002; Ke Shen 003; Alice M. Mulvehill; Mayank Kejriwal; Deborah L. McGuinness (Zenodo, 2023)

TG-CSR Annotations. - Henrique Santos 002; Alice M. Mulvehill; Ke Shen 003; Mayank Kejriwal; Deborah L. McGuinness (Zenodo, 2023)

An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks. - Ke Shen 003; Mayank Kejriwal (Expert Syst. J. Knowl. Eng., 2023)

The Generalization and Robustness of Transformer-Based Language Models on Commonsense Reasoning. - Ke Shen 003 (AAAI, 2024)

Multipartite Entity Resolution: Motivating a K-Tuple Perspective (Student Abstract). - Adin Aberbach; Mayank Kejriwal; Ke Shen 003 (AAAI, 2024)

An Evaluation of Estimative Uncertainty in Large Language Models. - Zhisheng Tang; Ke Shen 003; Mayank Kejriwal (CoRR, 2024)

Defining and Evaluating Decision and Composite Risk in Language Models Applied to Natural Language Inference. - Ke Shen 003; Mayank Kejriwal (CoRR, 2024)

SelECT-SQL: Self-correcting ensemble Chain-of-Thought for Text-to-SQL. - Ke Shen 003; Mayank Kejriwal (CoRR, 2024)

A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense. - Henrique Santos 002; Ke Shen 003; Alice M. Mulvehill; Mayank Kejriwal; Deborah L. McGuinness (Data Intell., 2024)