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ORCIDKe Shen 0003
Person information
- affiliation: University of Southern California, Marina del Rey, CA, USA
- affiliation (former): Chongqing University of Posts and Telecommunications, Chongqing, China
Other persons with the same name
- Ke Shen — disambiguation page
- Ke Shen 0001
![[0000-0003-2979-410X]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-2979-410X")
— Northwestern Polytechnical University, Xi'an, China - Ke Shen 0002 — Purdue University, West Lafayette, IN, USA
- Ke Shen 0004 — Huazhong University of Science and Technology, Wuhan, China
- Ke Shen 0005 — Ghent University/IMEC, Ghent, Belgium
Other persons with a similar name
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2020 – today
- 2024
[j5]Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness:
A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense. Data Intell. 6(1): 1-28 (2024)- [c9]Ke Shen:
The Generalization and Robustness of Transformer-Based Language Models on Commonsense Reasoning. AAAI 2024: 23419-23420 - [c8]Adin Aberbach, Mayank Kejriwal, Ke Shen:
Multipartite Entity Resolution: Motivating a K-Tuple Perspective (Student Abstract). AAAI 2024: 23434-23435 - [i10]Zhisheng Tang, Ke Shen, Mayank Kejriwal:
An Evaluation of Estimative Uncertainty in Large Language Models. CoRR abs/2405.15185 (2024) - [i9]Ke Shen, Mayank Kejriwal:
Defining and Evaluating Decision and Composite Risk in Language Models Applied to Natural Language Inference. CoRR abs/2408.01935 (2024) - [i8]Ke Shen, Mayank Kejriwal:
SelECT-SQL: Self-correcting ensemble Chain-of-Thought for Text-to-SQL. CoRR abs/2409.10007 (2024) - 2023
- [j4]Ke Shen, Mayank Kejriwal:
An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks. Expert Syst. J. Knowl. Eng. 40(5) (2023) - [c7]Mayank Kejriwal, Henrique Santos, Ke Shen, Alice M. Mulvehill, Deborah L. McGuinness:
Context-Rich Evaluation of Machine Common Sense. AGI 2023: 167-176 - [c6]Ke Shen, Mayank Kejriwal:
An Analytical Approximation of Simplicial Complex Distributions in Communication Networks. COMPLEX NETWORKS (4) 2023: 16-26 - [c5]Ke Shen, Mayank Kejriwal:
Substructure Discovery in Commonsense Relations Using Graph Representation Learning. IntelliSys (1) 2023: 714-734 - [d4]Henrique Santos, Alice M. Mulvehill, Ke Shen, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR Annotations. Zenodo, 2023
- [d3]Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. Zenodo, 2023 - [d2]Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. Zenodo, 2023 - [d1]Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. Zenodo, 2023 - [i7]Ke Shen, Mayank Kejriwal:
A Formalism and Approach for Improving Robustness of Large Language Models Using Risk-Adjusted Confidence Scores. CoRR abs/2310.03283 (2023) - 2022
- [j3]Mayank Kejriwal, Ke Shen, Chien-Chun Ni, Nicolas Torzec:
Transfer-based taxonomy induction over concept labels. Eng. Appl. Artif. Intell. 108: 104548 (2022) - [i6]Mayank Kejriwal, Ke Shen:
Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks? CoRR abs/2203.06491 (2022) - [i5]Henrique Santos, Ke Shen, Alice M. Mulvehill, Yasaman Razeghi, Deborah L. McGuinness, Mayank Kejriwal:
A Theoretically Grounded Benchmark for Evaluating Machine Commonsense. CoRR abs/2203.12184 (2022) - [i4]Ke Shen, Mayank Kejriwal:
Understanding Prior Bias and Choice Paralysis in Transformer-based Language Representation Models through Four Experimental Probes. CoRR abs/2210.01258 (2022) - [i3]Ke Shen, Mayank Kejriwal:
Understanding Substructures in Commonsense Relations in ConceptNet. CoRR abs/2210.01263 (2022) - 2021
- [j2]Mayank Kejriwal, Ke Shen, Chien-Chun Ni, Nicolas Torzec:
An evaluation and annotation methodology for product category matching in e-commerce. Comput. Ind. 131: 103497 (2021) - [c4]Mayank Kejriwal, Ke Shen:
Unsupervised real-time induction and interactive visualization of taxonomies over domain-specific concepts. ASONAM 2021: 301-304 - [c3]Ke Shen, Mayank Kejriwal:
On the Generalization Abilities of Fine-Tuned Commonsense Language Representation Models. SGAI Conf. 2021: 3-16 - 2020
- [i2]Mayank Kejriwal, Ke Shen:
Do Fine-tuned Commonsense Language Models Really Generalize? CoRR abs/2011.09159 (2020) - [i1]Ke Shen, Mayank Kejriwal:
A Data-Driven Study of Commonsense Knowledge using the ConceptNet Knowledge Base. CoRR abs/2011.14084 (2020)
2010 – 2019
- 2019
- [j1]Zhixing Li, Shiya Ren, Huaming Wang, Ke Shen:
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). 计算机科学 46(11): 209-215 (2019) - 2018
- [c2]Shiya Ren, Zhixing Li, Huaming Wang, Yuan Li, Ke Shen, Sijie Cheng:
NEARM: Natural Language Enhanced Association Rules Mining. ICDM Workshops 2018: 438-445 - 2017
- [c1]Xi Yang, Shiya Ren, Yuan Li, Ke Shen, Zhixing Li, Guoyin Wang:
Relation Linking for Wikidata Using Bag of Distribution Representation. NLPCC 2017: 652-661
Coauthor Index
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