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Feihu Che

Tucker decomposition-based temporal knowledge graph completion
2021 · Pengpeng Shao, Dawei Zhang, et al. · Knowledge-Based Systems · 125
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ParamE: Regarding Neural Network Parameters as Relation Embeddings for Knowledge Graph Completion
2020 · Feihu Che, Dawei Zhang, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 58
Self-supervised graph representation learning via bootstrapping
2021 · Feihu Che, Guohua Yang, et al. · Neurocomputing · 22
Adaptive pseudo-Siamese policy network for temporal knowledge prediction
2023 · Pengpeng Shao, Tong Liu, et al. · Neural Networks · 11
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Multi-aspect self-supervised learning for heterogeneous information network
2021 · Feihu Che, Jianhua Tao, et al. · Knowledge-Based Systems · 11
M 2 ixKG: Mixing for harder negative samples in knowledge graph
2024 · Feihu Che, Jianhua Tao · Neural Networks · 10
Pandora’s Box or Aladdin’s Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models
2025 · Jinyang Wu, Shuai Zhang, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 7
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Self-supervised Graph Representation Learning via Bootstrapping
2020 · Che, Feihu, Yang, Guohua, et al. · arXiv (Cornell University) · 5
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Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS
2024 · Wu, Jinyang, Feng, Mingkuan, et al. · arXiv (Cornell University) · 3
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MixKG: Mixing for harder negative samples in knowledge graph
2022 · Che, Feihu, Yang, Guohua, et al. · arXiv (Cornell University) · 3
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Knowledge graph enhanced recommender system
2021 · Huai, Zepeng, Tao, Jianhua, et al. · arXiv (Cornell University) · 3
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Hard or False: Keep the Balance for Negative Sampling in Knowledge Graphs
2025 · Feihu Che, Jianhua Tao, et al. · IEEE Transactions on Knowledge and Data Engineering · 1
KS-LLM: Knowledge Selection of Large Language Models with Evidence Document for Question Answering
2024 · Zheng, Xinxin, Che, Feihu, et al. · arXiv (Cornell University) · 1
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M 2ixKG: Mixing for Harder Negative Samples in Knowledge Graph
2023 · Feihu Che, Jianhua Tao · SSRN Electronic Journal · 1
Two-Stage Regularization-Based Structured Pruning for LLMs
2026 · Association for Computational Linguistics 2026, Che, Feihu, et al. · Underline Science Inc.
Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models
2026 · Association for Computational Linguistics 2026, Che, Feihu, et al. · Underline Science Inc.
Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models
2026 · Jinyang Wu, Mingkuan Feng, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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Code-switching Mediated Sentence-level Semantic Learning
2025 · Shuai Zhang, Jiangyan Yi, et al. · Proceedings of the AAAI Conference on Artificial Intelligence
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DReSS: Data-driven Regularized Structured Streamlining for Large Language Models
2025 · Feng, Mingkuan, Wu, Jinyang, et al. · arXiv (Cornell University)
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Can Large Language Models Understand Uncommon Meanings of Common Words?
2024 · Jinyang Wu, Feihu Che, et al. · SSRN Electronic Journal
Works count: 22
Citation count: 261
H-index: 7
I10-index: 6
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