Technical Solutions of TsinghuAeolus for Robotic Soccer. - Jinyi Yao; Ni Lao; Fan Yang; Yunpeng Cai; Zengqi Sun (RoboCup, 2003)

Why PCs Are Fragile and What We Can Do About It: A Study of Windows Registry Problems. - Archana Ganapathi; Yi-Min Wang; Ni Lao; Ji-Rong Wen (DSN, 2004)

Combining High Level Symptom Descriptions and Low Level State Information for Configuration Fault Diagnosis. - Ni Lao; Ji-Rong Wen; Wei-Ying Ma; Yi-Min Wang (LISA, 2004)

Probabilistic model for contextual retrieval. - Ji-Rong Wen; Ni Lao; Wei-Ying Ma (SIGIR, 2004)

Automated known problem diagnosis with event traces. - Chun Yuan; Ni Lao; Ji-Rong Wen; Jiwei Li; Zheng Zhang 001; Yi-Min Wang; Wei-Ying Ma (EuroSys, 2006)

Utility-based information distillation over temporally sequenced documents. - Yiming Yang; Abhimanyu Lad; Ni Lao; Abhay Harpale; Bryan Kisiel; Monica Rogati (SIGIR, 2007)

Query Expansion and Machine Translation for Robust Cross-Lingual Information Retrieval. - Ni Lao; Hideki Shima 001; Teruko Mitamura; Eric Nyberg (NTCIR, 2008)

Complex Cross-lingual Question Answering as a Sequential Classification and Multi-Document Summarization Task. - Hideki Shima 001; Ni Lao; Eric Nyberg; Teruko Mitamura (NTCIR, 2008)

Fast query execution for retrieval models based on path-constrained random walks. - Ni Lao; William W. Cohen (KDD, 2010)

Grafting-light: fast, incremental feature selection and structure learning of Markov random fields. - Jun Zhu 001; Ni Lao; Eric P. Xing (KDD, 2010)

Efficient Relational Learning with Hidden Variable Detection. - Ni Lao; Jun Zhu 001; Xinwang Liu; Yandong Liu; William W. Cohen (NIPS, 2010)

Relational retrieval using a combination of path-constrained random walks. - Ni Lao; William W. Cohen (Mach. Learn., 2010)

Random Walk Inference and Learning in A Large Scale Knowledge Base. - Ni Lao; Tom M. Mitchell; William W. Cohen (EMNLP, 2011)

Conditional topical coding: an efficient topic model conditioned on rich features. - Jun Zhu 001; Ni Lao; Ning Chen 002; Eric P. Xing (KDD, 2011)

Reading The Web with Learned Syntactic-Semantic Inference Rules. - Ni Lao; Amarnag Subramanya; Fernando C. N. Pereira; William W. Cohen (EMNLP-CoNLL, 2012)

Knowledge vault: a web-scale approach to probabilistic knowledge fusion. - Xin Dong 001; Evgeniy Gabrilovich; Geremy Heitz; Wilko Horn; Ni Lao; Kevin Murphy 002; Thomas Strohmann; Shaohua Sun; Wei Zhang 152 (KDD, 2014)

Contrastive Feature Induction for Efficient Structure Learning of Conditional Random Fields. - Ni Lao; Jun Zhu 001 (CoRR, 2014)

Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic. - William Yang Wang; Kathryn Mazaitis; Ni Lao; Tom M. Mitchell; William W. Cohen (CoRR, 2014)

Never-Ending Learning. - Tom M. Mitchell; William W. Cohen; Estevam R. Hruschka Jr.; Partha Pratim Talukdar; Justin Betteridge; Andrew Carlson; Bhavana Dalvi Mishra; Matthew Gardner 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; Kathryn Mazaitis; et al. (AAAI, 2015)

Learning Relational Features with Backward Random Walks. - Ni Lao; Einat Minkov; William W. Cohen (ACL (1), 2015)

Efficient inference and learning in a large knowledge base - Reasoning with extracted information using a locally groundable first-order probabilistic logic. - William Yang Wang; Kathryn Mazaitis; Ni Lao; William W. Cohen (Mach. Learn., 2015)

Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version). - Chen Liang; Jonathan Berant; Quoc V. Le; Kenneth D. Forbus; Ni Lao (CoRR, 2016)

Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision. - Chen Liang; Jonathan Berant; Quoc V. Le; Kenneth D. Forbus; Ni Lao (ACL (1), 2017)

Learning to Organize Knowledge with N-Gram Machines. - Fan Yang 058; William W. Cohen; Jiazhong Nie; Ni Lao (AKBC@NIPS, 2017)

Fast Reading Comprehension with ConvNets. - Felix Wu; Ni Lao; John Blitzer; Guandao Yang; Kilian Q. Weinberger (CoRR, 2017)

POIReviewQA: A Semantically Enriched POI Retrieval and Question Answering Dataset. - Gengchen Mai; Krzysztof Janowicz; Cheng He; Sumang Liu; Ni Lao (GIR@SIGSPATIAL, 2018)

Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing. - Chen Liang; Mohammad Norouzi 002; Jonathan Berant; Quoc V. Le; Ni Lao (NeurIPS, 2018)

Never-ending learning. - Tom M. Mitchell; William W. Cohen; Estevam R. Hruschka Jr.; Partha P. Talukdar; Bo Yang 011; Justin Betteridge; Andrew Carlson; Bhavana Dalvi Mishra; Matt Gardner 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; et al. (Commun. ACM, 2018)

Memory Augmented Policy Optimization for Program Synthesis with Generalization. - Chen Liang; Mohammad Norouzi 002; Jonathan Berant; Quoc V. Le; Ni Lao (CoRR, 2018)

Neural Program Planner for Structured Predictions. - Jacob Biloki; Chen Liang; Ni Lao (DeepRLStructPred@ICLR, 2019)

Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs. - Gengchen Mai; Krzysztof Janowicz; Bo Yan 003; Rui Zhu 008; Ling Cai; Ni Lao (K-CAP, 2019)

FastFusionNet: New State-of-the-Art for DAWNBench SQuAD. - Felix Wu; Boyi Li; Lequn Wang; Ni Lao; John Blitzer; Kilian Q. Weinberger (CoRR, 2019)

Integrated Triaging for Fast Reading Comprehension. - Felix Wu; Boyi Li; Lequn Wang; Ni Lao; John Blitzer; Kilian Q. Weinberger (CoRR, 2019)

Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online. - Gengchen Mai; Krzysztof Janowicz; Sathya Prasad; Meilin Shi; Ling Cai; Rui Zhu 008; Blake Regalia; Ni Lao (AGILE Conf., 2020)

Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells. - Gengchen Mai; Krzysztof Janowicz; Bo Yan 003; Rui Zhu 008; Ling Cai; Ni Lao (ICLR, 2020)

Pivot Through English: Reliably Answering Multilingual Questions without Document Retrieval. - Ivan Montero; Shayne Longpre; Ni Lao; Andrew J. Frank; Christopher DuBois (CoRR, 2020)

SE-KGE : A location-aware Knowledge Graph Embedding model for Geographic Question Answering and Spatial Semantic Lifting. - Gengchen Mai; Krzysztof Janowicz; Ling Cai; Rui Zhu 008; Blake Regalia; Bo Yan 003; Meilin Shi; Ni Lao (Trans. GIS, 2020)

Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions. - Gengchen Mai; Krzysztof Janowicz; Rui Zhu 008; Ling Cai; Ni Lao (AGILE Conf., 2021)

Orthographic Transliteration for Kabyle Speech Recognition. - Christopher Haberland; Ni Lao (ICNLSP, 2021)

Narrative Cartography with Knowledge Graphs. - Gengchen Mai; Weiming Huang 001; Ling Cai; Rui Zhu 008; Ni Lao (CoRR, 2021)

Towards a foundation model for geospatial artificial intelligence (vision paper). - Gengchen Mai; Chris Cundy; Kristy Choi; Yingjie Hu; Ni Lao; Stefano Ermon (SIGSPATIAL/GIS, 2022)

Sphere2Vec: Multi-Scale Representation Learning over a Spherical Surface for Geospatial Predictions. - Gengchen Mai; Yao Xuan; Wenyun Zuo; Krzysztof Janowicz; Ni Lao (CoRR, 2022)

Attributed Text Generation via Post-hoc Research and Revision. - Luyu Gao; Zhuyun Dai; Panupong Pasupat; Anthony Chen; Arun Tejasvi Chaganty; Yicheng Fan; Vincent Y. Zhao; Ni Lao; Hongrae Lee; Da-Cheng Juan; Kelvin Guu (CoRR, 2022)

A review of location encoding for GeoAI: methods and applications. - Gengchen Mai; Krzysztof Janowicz; Yingjie Hu; Song Gao 001; Bo Yan 003; Rui Zhu 008; Ling Cai; Ni Lao (Int. J. Geogr. Inf. Sci., 2022)

RARR: Researching and Revising What Language Models Say, Using Language Models. - Luyu Gao; Zhuyun Dai; Panupong Pasupat; Anthony Chen; Arun Tejasvi Chaganty; Yicheng Fan; Vincent Y. Zhao; Ni Lao; Hongrae Lee; Da-Cheng Juan; Kelvin Guu (ACL (1), 2023)

Rethink Geographical Generalizability with Unsupervised Self-Attention Model Ensemble: A Case Study of OpenStreetMap Missing Building Detection in Africa. - Hao Li 019; Jiapan Wang; Johann Maximilian Zollner; Gengchen Mai; Ni Lao; Martin Werner 001 (SIGSPATIAL/GIS, 2023)

CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations. - Gengchen Mai; Ni Lao; Yutong He; Jiaming Song; Stefano Ermon (ICML, 2023)

On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence. - Gengchen Mai; Weiming Huang 001; Jin Sun 011; Suhang Song; Deepak Mishra 005; Ninghao Liu; Song Gao 001; Tianming Liu 001; Gao Cong; Yingjie Hu; Chris Cundy; Ziyuan Li; et al. (CoRR, 2023)

Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions. - Gengchen Mai; Yao Xuan; Wenyun Zuo; Yutong He; Jiaming Song; Stefano Ermon; Krzysztof Janowicz; Ni Lao (CoRR, 2023)

SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution. - Gengchen Mai; Ni Lao; Weiwei Sun; Yuchi Ma; Jiaming Song; Chenlin Meng; Hongxu Ma; Jinmeng Rao; Ziyuan Li; Stefano Ermon (CoRR, 2023)

Towards general-purpose representation learning of polygonal geometries. - Gengchen Mai; Chiyu Jiang 001; Weiwei Sun; Rui Zhu 008; Yao Xuan; Ling Cai; Krzysztof Janowicz; Stefano Ermon; Ni Lao (GeoInformatica, 2023)

Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages. - Yingjie Hu; Gengchen Mai; Chris Cundy; Kristy Choi; Ni Lao; Wei Liu; Gaurish Lakhanpal; Ryan Zhenqi Zhou; Kenneth Joseph (Int. J. Geogr. Inf. Sci., 2023)

TorchSpatial: A Python Package for Spatial Representation Learning and Geo-Aware Model Development. - Qian Cao; Nemin Wu; Zhangyu Wang; Zeping Liu; Yanlin Qi; Jielu Zhang; Joshua Ni; Xiaobai Angela Yao; Hongxu Ma; Lan Mu; Stefano Ermon; Tanuja Ganu; et al. (GeoIndstry@SIGSPATIAL, 2024)

SRL: Towards a General-Purpose Framework for Spatial Representation Learning. - Gengchen Mai; Xiaobai Angela Yao; Yiqun Xie; Jinmeng Rao; Hao Li 019; Qing Zhu; Ziyuan Li; Ni Lao (SIGSPATIAL/GIS, 2024)

MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations. - Zhangyu Wang; Gengchen Mai; Krzysztof Janowicz; Ni Lao (ICML, 2024)

TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning. - Nemin Wu; Qian Cao; Zhangyu Wang; Zeping Liu; Yanlin Qi; Jielu Zhang; Joshua Ni; Xiaobai Angela Yao; Hongxu Ma; Lan Mu; Stefano Ermon; Tanuja Ganu; et al. (NeurIPS, 2024)

Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation. - Zhongliang Zhou; Jielu Zhang; Zihan Guan 001; Mengxuan Hu; Ni Lao; Lan Mu; Sheng Li 001; Gengchen Mai (SIGIR, 2024)

On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper). - Gengchen Mai; Weiming Huang 001; Jin Sun 011; Suhang Song; Deepak Mishra 005; Ninghao Liu; Song Gao 001; Tianming Liu 001; Gao Cong; Yingjie Hu; Chris Cundy; Ziyuan Li; et al. (ACM Trans. Spatial Algorithms Syst., 2024)

Towards the next generation of Geospatial Artificial Intelligence. - Gengchen Mai; Yiqun Xie; Xiaowei Jia; Ni Lao; Jinmeng Rao; Qing Zhu; Zeping Liu; Yao-Yi Chiang; Junfeng Jiao (Int. J. Appl. Earth Obs. Geoinformation, 2025)

GAIR: Improving Multimodal Geo-Foundation Model with Geo-Aligned Implicit Representations. - Zeping Liu; Fan Zhang; Junfeng Jiao; Ni Lao; Gengchen Mai (CoRR, 2025)

LocDiffusion: Identifying Locations on Earth by Diffusing in the Hilbert Space. - Zhangyu Wang; Jielu Zhang; Zhongliang Zhou; Qian Cao; Nemin Wu; Zeping Liu; Lan Mu; Yang Song; Yiqun Xie; Ni Lao; Gengchen Mai (CoRR, 2025)

GeoFM: how will geo-foundation models reshape spatial data science and GeoAI? - Krzysztof Janowicz; Gengchen Mai; Weiming Huang 001; Rui Zhu 008; Ni Lao; Ling Cai (Int. J. Geogr. Inf. Sci., 2025)