---
title: "Who cites Tianjun Xiao — 319 papers of our library"
description: "319 papers of the Elamur Research library cite the works of Tianjun Xiao, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/tianjun-xiao/cited-by/"
---
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# Who cites Tianjun Xiao

320 citations of their works from 319 papers of our library (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · [← Tianjun Xiao](https://md.research.elamur.ai/free/en/authors/tianjun-xiao/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. [**AllenNLP: A Deep Semantic Natural Language Processing Platform arXiv:1803.07640**Matt Gardner, Joel Grus, Mark Neumann, et al.*2018 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2018-allennlp-deep-semantic-natural-language/)
3. [**TVM: An Automated End-to-End Optimizing Compiler for Deep Learning arXiv:1802.04799**Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al.*2018 · 1,384 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/)
4. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
5. **[ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs](https://md.research.elamur.ai/free/en/papers/yin-2016-abcnn-attention-based-convolutional-neural/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Wenpeng Yin, Hinrich Schütze, Bing Xiang, et al.*2016 · 1,055 citations*
6. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations MAPL 2019**Philippe Tillet, H. T. Kung, David Cox*2019 · 729 citations*](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/)
7. [**DyNet: The Dynamic Neural Network Toolkit arXiv:1701.03980**Graham Neubig, Chris Dyer, Yoav Goldberg, et al.*2017 · 489 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2017-dynet-dynamic-neural-network-toolkit/)
8. **[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/beck-2018-graph-sequence-learning-gated-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Beck, Gholamreza Haffari, Trevor Cohn*2018 · 459 citations*
9. [**Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions arXiv:1802.04730**Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, et al.*2018 · 323 citations*](https://md.research.elamur.ai/free/en/papers/vasilache-2018-tensor-comprehensions-framework-agnostic-high/)
10. [**Beyond Data and Model Parallelism for Deep Neural Networks SysML 2019**Zhihao Jia, Matei Zaharia, Alex Aiken*2018 · 280 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/)
11. [**Learning to Optimize Tensor Programs arXiv:1805.08166**Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.*2019 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-learning-optimize-tensor-programs/)
12. [**Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads arXiv:1901.05758**Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, et al.*2019 · 179 citations*](https://md.research.elamur.ai/free/en/papers/jeon-2019-analysis-large-scale-multi-tenant/)
13. [**PipeDream: Fast and Efficient Pipeline Parallel DNN Training arXiv:1806.03377**Aaron Harlap, Deepak Narayanan, Amar Phanishayee, et al.*2018 · 162 citations*](https://md.research.elamur.ai/free/en/papers/harlap-2018-pipedream-fast-efficient-pipeline-parallel/)
14. [**Online normalizer calculation for softmax arXiv 2018 (NVIDIA)**Maxim Milakov, Natalia Gimelshein*2018 · 123 citations*](https://md.research.elamur.ai/free/en/papers/milakov-2018-online-normalizer-calculation-softmax/)
15. [**vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design MICRO 2016**Minsoo Rhu, Natalia Gimelshein, Jason Clemons, et al.*2016 · 81 citations*](https://md.research.elamur.ai/free/en/papers/rhu-2016-vdnn-virtualized-deep-neural-networks/)
16. **[Exploring Different Dimensions of Attention for Uncertainty Detection](https://md.research.elamur.ai/free/en/papers/adel-2017-exploring-different-dimensions-attention-uncertainty/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Heike Adel, Hinrich Schütze*2017 · 63 citations*
17. **[Mispronunciation Detection in Non-native (L2) English with Uncertainty Modeling](https://md.research.elamur.ai/free/en/papers/korzekwa-2021-mispronunciation-detection-non-native-l2/) [IEEE International Conference on Acoustics Speech and Signal Processing](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-acoustics-speech-and-signal-processing/)**Daniel Korzekwa, Jaime Lorenzo-Trueba, Szymon Zaporowski, et al.*2021 · 27 citations*
18. **[Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention](https://md.research.elamur.ai/free/en/papers/korzekwa-2020-detection-lexical-stress-errors-non/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Daniel Korzekwa, Roberto Barra-Chicote, Szymon Zaporowski, et al.*2020 · 16 citations*
19. **[Weakly-supervised word-level pronunciation error detection in non-native English speech](https://md.research.elamur.ai/free/en/papers/korzekwa-2021-weakly-supervised-word-level-pronunciation/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Daniel Korzekwa, Jaime Lorenzo-Trueba, Thomas Drugman, et al.*2021 · 15 citations*
20. **[Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?](https://md.research.elamur.ai/free/en/papers/mei-2026-reasoning-about-uncertainty-do-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiting Mei, Christina Zhang, Tenny Yin, et al.*2026 · 14 citations*
21. **[What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations](https://md.research.elamur.ai/free/en/papers/liu-2025-what-is-that-talk-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongqi Liu, Chenxi Whitehouse, Xi Yu, et al.*2025 · 13 citations*
22. **[Revealing and Enhancing Core Visual Regions: Harnessing Internal Attention Dynamics for Hallucination Mitigation in LVLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-revealing-enhancing-core-visual-regions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangtao Lyu, Qi Liu, Chenghao Xu, et al.*2026 · 5 citations*
23. [**Uncertainty Distillation: Teaching Language Models to Express Semantic Confidence arXiv:2503.14749**Sophia Hager; David Mueller; Kevin Duh;, Nicholas Andrews*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/hager-2025-uncertainty-distillation-teaching-language-models/)
24. **[Can Large Language Models Infer Causal Relationships from Real-World Text?](https://md.research.elamur.ai/free/en/papers/saklad-2026-can-large-language-models-infer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ryan Saklad, Aman Chadha, Oleg V. Pavlov, et al.*2026 · 2 citations*
25. **[Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-do-images-speak-louder-than/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chi Zhang, Wenxuan Ding, Jiale Liu, et al.*2026 · 2 citations*
26. **[SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/lv-2026-spd-faith-bench-diagnosing-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weijiang Lv, Yaoxuan Feng, Xiaobo Xia, et al.*2026 · 1 citation*
27. **[Visually-Guided Policy Optimization for Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-visually-guided-policy-optimization-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zengbin Wang, Feng Xiong, Liang Lin, et al.*2026 · 1 citation*
28. [**Automated detection of pronunciation errors in non-native English speech employing deep learning arXiv:2209.06265**Daniel Korzekwa*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/korzekwa-2022-automated-detection-pronunciation-errors-non/)
29. **[Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-deep-reporter-deep-research-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangda Ye, Kuicai Dong, Xie Zhifei, et al.*2026*
30. **[GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-gameplayqa-benchmarking-framework-decision-dense/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunzhe Wang, Runhui Xu, Kexin Zheng, et al.*2026*
31. **[Journey Before Destination: On the importance of Visual Faithfulness in Slow Thinking](https://md.research.elamur.ai/free/en/papers/uppaal-2026-journey-before-destination-importance-visual/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rheeya Uppaal, Phu Mon Htut, Min Bai, et al.*2026*
32. **[Latent Attention Denoising: A Training-Free Energy-Based Framework for Mitigating Hallucinations in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-latent-attention-denoising-training-free/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiwen Luo, Siyu Jiang, Weilong Jiang, et al.*2026*
33. **[Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation](https://md.research.elamur.ai/free/en/papers/zhu-2026-mitigating-hallucinations-large-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Zhu, Junfeng Fang, Shuo Wang, et al.*2026*
34. **[Spotlight and Shadow: Attention-Guided Dual-Anchor Introspective Decoding for MLLM Hallucination Mitigation](https://md.research.elamur.ai/free/en/papers/wu-2026-spotlight-shadow-attention-guided-dual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yebo Wu, Han Jin, Zhijiang Guo, et al.*2026*
35. **[Taming Object Hallucinations with Verified Atomic Confidence Estimation](https://md.research.elamur.ai/free/en/papers/liu-2026-taming-object-hallucinations-verified-atomic/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jiarui Liu, Weihao Xuan, Zhijing Jin, et al.*2026*
36. **[When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise](https://md.research.elamur.ai/free/en/papers/shin-2026-when-relations-break-analyzing-relation/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Philip Wootaek Shin, Ajay Narayanan Sridhar, Lakshmi Sivani Devarapalli, et al.*2026*

283 more citing papers of our library have no page here yet.

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