🧑‍🔬 Who cites Xiaoming Shi

110 citations of their works from 107 papers of our library (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · ← Xiaoming Shi

1. Revolutionizing Finance with LLMs: An Overview of Applications and InsightsarXiv:2401.11641Huaqin Zhao, Zhengliang Liu, Zihao Wu, et al.2024 · 63 citations
2. SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity RecognitionConference on Empirical Methods in Natural Language Processing (EMNLP)Zechen Li, Shohreh Deldari, Linyao Chen, et al.2025 · 27 citations
3. How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled BenchmarkMinglai Yang, Ethan Huang, Liang Zhang, et al.2025 · 25 citations
4. Time-MQA: Time Series Multi-Task Question Answering with Context EnhancementAnnual Meeting of the Association for Computational Linguistics (ACL)Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, et al.2025 · 21 citations
5. Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Tingchen Fu, Yafu Li, Jiawei Gu, et al.2026 · 12 citations
6. STReasoner: Empowering LLMs for Spatio-Temporal Reasoning in Time Series via Spatial-Aware Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Juntong Ni, Shiyu Wang, Qi He, et al.2026 · 3 citations
7. CaTS-Bench: Can Language Models Describe Time Series?Findings of the Association for Computational LinguisticsLuca Zhou, Pratham Yashwante, Marshall Fisher, et al.2026 · 1 citation
8. Clutch or Cry at SemEval-2026 Task 12: Offline Retrieval-Augmented Generation with Frozen DeBERTa for Abductive Event ReasoningInternational Workshop on Semantic Evaluation (SemEval)Aayush Prasad, Rudra Trivedi, Arshad Khatib, et al.2026 · 1 citation
9. Deconstructing Instruction-Following: A New Benchmark for Granular Evaluation of Large Language Model Instruction Compliance AbilitiesConference of the European Chapter of the Association for Computational Linguistics (EACL)Alberto Purpura, Li Wang, Sahil Badyal, et al.2026
10. Enhancing Zero-Shot Time Series Forecasting in Off-the-Shelf LLMs via Noise Injection PromptingFindings of the Association for Computational LinguisticsXingyou Yin, Ceyao Zhang, Min Hu, et al.2026
11. From Implicit Graph Encoding to Explicit Evidence: A Training-Free LLM Framework for Temporal Knowledge Graph ReasoningFindings of the Association for Computational LinguisticsGuo Tang, Ke Cheng, Huiming Fan, et al.2026
12. ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Yuancheng Yang, Lin Yang, Xu Wang, et al.2026
13. LENS: LLM-Enabled Narrative Synthesis for Mental Health by Aligning Multimodal Sensing with Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Wenxuan Xu, Arvind Pillai, Subigya Nepal, et al.2026
14. Markovian Linguistic-Temporal Bridge: Unlocking the Potential of LLMs for Time Series ForecastingAnnual Meeting of the Association for Computational Linguistics (ACL)Siming Sun, Kai Zhang, Xuejun Jiang, et al.2026
15. TimeSAF: Towards LLM-Guided Semantic Asynchronous Fusion for Time Series ForecastingAnnual Meeting of the Association for Computational Linguistics (ACL)Fan Zhang, Shiming Fan, Hua Wang2026
16. We Are What We Repeatedly Do: Improving Long Context Instruction FollowingFindings of the Association for Computational LinguisticsPreston K Robinette, Andrew Hard, Swaroop Ramaswamy, et al.2026

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