Browse by UCL people
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Number of items: 60.
Article
Aguilera, Quinton;
Lombardo, Luigi;
Tanyas, Hakan;
Lipani, Aldo;
(2022)
On the prediction of landslide occurrences and sizes via Hierarchical Neural Networks.
Stochastic Environmental Research and Risk Assessment
10.1007/s00477-022-02215-0.
(In press).
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Anderson-Bell, J;
Schillaci, C;
Lipani, A;
(2021)
Predicting Non-Residential Building Fire Risk Using Geospatial Information and Convolutional Neural Networks.
Remote Sensing Applications: Society and Environment
, 21
, Article 100470. 10.1016/j.rsase.2021.100470.
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Anim-Ayeko, Alberta Odamea;
Schillaci, Calogero;
Lipani, Aldo;
(2023)
Automatic Blight Disease Detection in Potato (Solanum tuberosum L.) and Tomato (Solanum lycopersicum, L. 1753) Plants using Deep Learning.
Smart Agricultural Technology
, 4
, Article 100178. 10.1016/j.atech.2023.100178.
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Dutta, Ujjal KR;
Lipani, Aldo;
Wang, Chuan;
Hu, Yukun;
(2025)
Hottel Zone Physics-Constrained Networks for Industrial Furnaces.
IEEE Access
, 13
pp. 75130-75152.
10.1109/ACCESS.2025.3563413.
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Gezici, G;
Lipani, A;
Saygin, Y;
Yilmaz, E;
(2021)
Evaluation metrics for measuring bias in search engine results.
Information Retrieval Journal
, 24
pp. 85-113.
10.1007/s10791-020-09386-w.
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Ibrahim, MR;
Haworth, J;
Lipani, A;
Aslam, N;
Cheng, T;
Christie, N;
(2021)
Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe.
PLoS One
, 16
(1)
, Article e0246120. 10.1371/journal.pone.0246120.
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James, T;
Schillaci, C;
Lipani, A;
(2021)
Convolutional Neural Networks for Water segmentation using Sentinel-2 Red, Green, Blue (RGB) composites and derived Spectral Indices.
International Journal of Remote Sensing (TRES)
, 42
(14)
pp. 5338-5365.
10.1080/01431161.2021.1913298.
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Kizilcec, V;
Spataru, C;
Lipani, A;
Parikh, P;
(2022)
Forecasting Solar Home System Customers’ Electricity Usage with a 3D Convolutional Neural Network to Improve Energy Access.
Energies
, 15
(3)
, Article 857. 10.3390/en15030857.
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Kusa, Wojciech;
Lipani, Aldo;
Knoth, Petr;
Hanbury, Allan;
(2023)
An Analysis of Work Saved over Sampling in the Evaluation of Automated Citation Screening in Systematic Literature Reviews.
Intelligent Systems with Applications
, Article 200193. 10.1016/j.iswa.2023.200193.
(In press).
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Lipani, A;
Carterette, B;
Yilmaz, E;
(2021)
How Am I Doing?: Evaluating Conversational Search Systems Offline.
ACM Transactions on Information Systems
, 39
(4)
, Article 51. 10.1145/3451160.
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Lipani, A;
Losada, D;
Zuccon, G;
Lupu, M;
(2019)
Fixed-Cost Pooling Strategies.
IEEE Transactions on Knowledge and Data Engineering
10.1109/TKDE.2019.2947049.
(In press).
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Lipani, A;
Roelleke, T;
Lupu, M;
Hanbury, A;
(2018)
A systematic approach to normalization in probabilistic models.
Information Retrieval Journal
, 21
(6)
pp. 565-566.
10.1007/s10791-018-9334-1.
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Lu, Yichen;
James, Thomas;
Schillaci, Calogero;
Lipani, Aldo;
(2022)
Snow detection in alpine regions with Convolutional Neural Networks: discriminating snow from cold clouds and water body.
GIScience & Remote Sensing
, 59
(1)
pp. 1321-1343.
10.1080/15481603.2022.2112391.
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Luft, Harrison;
Schillaci, Calogero;
Ceccherini, Guido;
Vieira, Diana;
Lipani, Aldo;
(2022)
Deep Learning Based Burnt Area Mapping Using Sentinel 1 for the Santa Cruz Mountains Lightning Complex (CZU) and Creek Fires 2020.
Fire
, 5
(5)
, Article 163. 10.3390/fire5050163.
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Olsen, Frederik;
Schillaci, Calogero;
Ibrahim, Mohamed;
Lipani, Aldo;
(2022)
Borough-level COVID-19 forecasting in London using deep learning techniques and a novel MSE-Moran’s I loss function.
Results in Physics
, 35
, Article 105374. 10.1016/j.rinp.2022.105374.
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Panella, Fabio;
Lipani, Aldo;
Boehm, Jan;
(2022)
Semantic segmentation of cracks: Data challenges and architecture.
Automation in Construction
, 135
, Article 104110. 10.1016/j.autcon.2021.104110.
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Priscillia, Stela;
Schillaci, Calogero;
Lipani, Aldo;
(2021)
Flood susceptibility assessment using artificial neural networks in Indonesia.
Artificial Intelligence in Geosciences
, 2
pp. 215-222.
10.1016/j.aiig.2022.03.002.
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Roegiest, A;
Lipani, A;
Beutel, A;
Olteanu, A;
Lucic, A;
Stoica, A-A;
Das, A;
... Kamishima, T; + view all
(2019)
FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval.
SIGIR Forum
, 53
(2)
pp. 20-43.
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Schillaci, C;
Perego, A;
Valkama, E;
Märker, M;
Saia, S;
Veronesi, F;
Lipani, A;
... Acutis, M; + view all
(2021)
New pedotransfer approaches to predict soil bulk density using WoSIS soil data and environmental covariates in Mediterranean agro-ecosystems.
Science of The Total Environment
, 780
, Article 146609. 10.1016/j.scitotenv.2021.146609.
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Schillaci, C;
Acutis, M;
Lombardo, L;
Lipani, A;
Fantappie, M;
Maerker, M;
Saia, S;
(2017)
Spatio-temporal topsoil organic carbon mapping of a semi-arid Mediterranean region: The role of land use, soil texture, topographic indices and the influence of remote sensing data to modelling.
Science of The Total Environment
, 601
pp. 821-832.
10.1016/j.scitotenv.2017.05.239.
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Schillaci, C;
Saia, S;
Lipani, A;
Perego, A;
Zaccone, C;
Acutis, M;
(2021)
Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands.
Carbon Balance and Management
, 16
(1)
, Article 19. 10.1186/s13021-021-00182-7.
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Wang, Z;
French, N;
James, T;
Schillaci, C;
Chan, F;
Feng, M;
Lipani, A;
(2023)
Climate and environmental data contribute to the prediction of grain commodity prices using deep learning.
Journal of Sustainable Agriculture and Environment
, 2
(3)
pp. 251-265.
10.1002/sae2.12041.
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Zhao, J;
Lipani, A;
Schillaci, C;
(2024)
Fallen apple detection as an auxiliary task: Boosting robotic apple detection performance through multi-task learning.
Smart Agricultural Technology
, 8
, Article 100436. 10.1016/j.atech.2024.100436.
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Proceedings paper
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Acharya, Praveen;
Jones, Gareth JF;
Fu, Xiao;
Lipani, Aldo;
Crestani, Fabio;
Kando, Noriko;
(2024)
Preface: The First Workshop on User Modelling in Conversational Information Retrieval (UM-CIR).
In: Acharya, Praveen and Clarke, Charles LA and Crestani, Fabio and Fu, Xiao and Jones, Gareth JF and Kando, Noriko and Kato, Makoto P and Lipani, Aldo and Liu, Yiqun, (eds.)
CEUR Workshop Proceedings.
CEUR: Tokyo, Japan.
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Bulathwela, S;
Pérez-Ortiz, M;
Lipani, A;
Yilmaz, E;
Shawe-Taylor, J;
(2020)
Predicting Engagement in Video Lectures.
In:
Proceedings of The 13th International Conference on Educational Data Mining (EDM 2020).
(pp. pp. 50-60).
Educational Data Mining (EDM)
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Feng, Yue;
Lipani, Aldo;
Ye, Fanghua;
Zhang, Qiang;
Yilmaz, Emine;
(2022)
Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Tracking.
In:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
(pp. pp. 115-126).
ACL Anthology: Dublin, Ireland.
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Fu, X;
Lipani, A;
Kando, N;
(2024)
An Evaluation Framework for Conversational Information Retrieval Using User Simulation.
In: Acharya, Praveen and Clarke, Charles LA and Crestani, Fabio and Fu, Xiao and Jones, Gareth JF and Kando, Noriko and Kato, Makoto P and Lipani, Aldo and Liu, Yiqun, (eds.)
CEUR Workshop Proceedings.
CEUR-WS.org: Tokyo, Japan.
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Fu, Xiao;
Bedi, Navdeep Singh;
Kando, Noriko;
Crestani, Fabio;
Lipani, Aldo;
(2025)
UCLWI at the NTCIR-18 AEOLLM Task: A Low-Cost Comparison of RAGs.
In: Kato, Makoto P and Kando, Noriko and Clarke, Charles LA and Liu, Yiqun, (eds.)
NTCIR.
National Institute of Informatics (NII)
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Fu, Xiao;
Lipani, Aldo;
(2023)
Priming and Actions: An Analysis in Conversational Search Systems.
In:
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval.
(pp. pp. 2277-2281).
ACM
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Fu, Xiao;
Yilmaz, Emine;
Lipani, Aldo;
(2022)
Evaluating the Cranfield Paradigm for Conversational Search Systems.
In:
Proceedings of the 2022 ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR ’22).
Association for Computing Machinery (ACM): New York, NY, USA.
(In press).
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Hofstatter, S;
Lipani, A;
Althammer, S;
Zlabinger, M;
Hanbury, A;
(2021)
Mitigating the Position Bias of Transformer Models in Passage Re-Ranking.
In:
Advances in Information Retrieval. ECIR 2021.
(pp. pp. 238-253).
Springer, Cham
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Hofstätter, S;
Lipani, A;
Zlabinger, M;
Hanbury, A;
(2020)
Learning to Re-Rank with Contextualized Stopwords.
In:
Proceedings of the 29th ACM International Conference on Information & Knowledge Management.
(pp. pp. 2057-2060).
Association for Computing Machinery (ACM)
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Izzo, C;
Lipani, A;
Okhrati, R;
Medda, F;
(2021)
A Baseline for Shapley Values in MLPs: from Missingness to Neutrality.
In:
ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learnin.
(pp. pp. 605-610).
i6doc publication: Online.
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Kim, To Eun;
Lipani, Aldo;
(2022)
A Multi-Task Based Neural Model to Simulate Users in Goal-Oriented Dialogue Systems.
In:
Proceedings of The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
(pp. pp. 2115-2119).
ACM
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Kusa, Wojciech;
Lipani, Aldo;
Knoth, Petr;
Hanbury, Allan;
(2023)
VoMBaT: A Tool for Visualising Evaluation Measure Behaviour in High-Recall Search Tasks.
In: Chen, Hsin-Hsi and Duh, Wei-Jou (Edward) and Huang, Hen-Hsen and Kato, Makoto P and Mothe, Josiane and Poblete, Barbara, (eds.)
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval.
Association for Computing Machinery (ACM): New York, NY, USA.
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Lipani, A;
Carterette, B;
Yilmaz, E;
(2019)
From a User Model for Query Sessions to Session Rank Biased Precision (sRBP).
In:
The 5th ACM SIGIR International Conference on the Theory of Information Retrieval.
(pp. pp. 109-116).
ACM: Santa Clara, CA, USA.
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Lipani, A;
Lupu, M;
Hanbury, A;
(2017)
Visual Pool: A tool to visualize and interact with the pooling method.
In:
SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval.
(pp. pp. 1321-1324).
ACM: USA: New York.
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Lipani, A;
Lupu, M;
Palotti, J;
Zuccon, G;
Hanbury, A;
(2017)
Fixed budget pooling strategies based on fusion methods.
In: Shin, SY and Shin, D and Lencastre, M, (eds.)
SAC '17: Proceedings of the Symposium on Applied Computing.
(pp. pp. 919-924).
ACM
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Lipani, A;
Palotti, J;
Lupu, M;
Piroi, F;
Zuccon, G;
Hanbury, A;
(2017)
Fixed-Cost Pooling Strategies Based on IR Evaluation Measures.
In: Jose, JM and Hauff, C and Altingovde, IS and Song, D and Albakour, D and Watt, S and Tait, J, (eds.)
Advances in Information Retrieval, 39th European Conference on IR Research: Proceedings.
(pp. pp. 357-368).
Springer: Cham, Switzerland.
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Lipani, A;
Zuccon, G;
Lupu, M;
Koopman, B;
Hanbury, A;
(2016)
The impact of fixed-cost pooling strategies on test collection bias.
In: Carterette, B and Fang, H and Lalmas, M and Nie, J-Y, (eds.)
ICTIR '16: Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval.
(pp. pp. 105-108).
ACM: New York, USA.
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Mungmeeprued, Thisanaporn;
Ma, Yuxin;
Mehta, Nisarg;
Lipani, Aldo;
(2022)
Tab this Folder of Documents: Page Stream Segmentation of Business Documents.
In:
Proceedings of the 22th ACM Symposium on Document Engineering.
Association for Computing Machinery (ACM)
(In press).
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Okhrati, R;
Lipani, A;
(2021)
A Multilinear Sampling Algorithm to Estimate Shapley Values.
In:
Proceedings of the 25th International Conference on Pattern Recognition (ICPR).
IEEE
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Radmard, P;
Fathullah, Y;
Lipani, A;
(2021)
Subsequence Based Deep Active Learning for Named Entity Recognition.
In: Zong, C and Xia, F and Li, W and Navigli, R, (eds.)
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing.
(pp. pp. 4310-4321).
Association for Computational Linguistics
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Rahmani, HA;
Wang, X;
Feng, Y;
Zhang, Q;
Yilmaz, E;
Lipani, A;
(2023)
A Survey on Asking Clarification Questions Datasets in Conversational Systems.
In:
Proceedings of the Annual Meeting of the Association for Computational Linguistics.
(pp. pp. 2698-2716).
Association for Computational Linguistics: Toronto, ON, Canada.
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Salutari, F;
Ramos, J;
Rahmani, HA;
Linguaglossa, L;
Lipani, A;
(2023)
Quantifying the Bias of Transformer-Based Language Models for African American English in Masked Language Modeling.
In:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
(pp. pp. 532-543).
Springer Nature
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Sanchez, L;
He, J;
Manotumruksa, J;
Albakour, D;
Martinez, M;
Lipani, A;
(2020)
Easing Legal News Monitoring with Learning to Rank and BERT.
In:
Proceedings of the European Conference on Information Retrieval ECIR 2020: Advances in Information Retrieval.
(pp. pp. 336-343).
Springer, Cham: Cham, Switzerland.
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Shelbourne, C;
Linguaglossa, L;
Zhang, T;
Lipani, A;
(2021)
Inference of virtual network functions' state via analysis of the CPU behavior.
In:
(Proceedings) International Teletraffic Congress.
(In press).
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Shelbourne, C;
Linguaglossa, L;
Lipani, A;
Zhang, T;
Geyer, F;
(2019)
On the Learnability of Software Router Performance via CPU Measurements.
In:
CoNEXT '19: Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies.
(pp. pp. 23-25).
ACM
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Shi, Z;
Lipani, A;
(2024)
DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning.
In:
12th International Conference on Learning Representations, ICLR 2024.
International Conference on Learning Representations (ICLR): Vienna, Austria.
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Shi, Z;
Sen, P;
Lipani, A;
(2023)
Lexical Entrainment for Conversational Systems.
In: Bouamor, Houda and Pino, Juan and Bali, Kalika, (eds.)
Findings of the Association for Computational Linguistics: EMNLP 2023.
(pp. pp. 278-293).
Association for Computational Linguistics: Singapore.
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Shi, Z;
Yang, AX;
Wu, B;
Aitchison, L;
Yilmaz, E;
Lipani, A;
(2024)
Instruction Tuning With Loss Over Instructions.
In: Globersons, Amir and Mackey, Lester and Belgrave, Danielle and Fan, Angela and Paquet, Ulrich and Tomczak, Jakub M and Zhang, Cheng, (eds.)
Advances in Neural Information Processing Systems 37.
Neural Information Processing Systems Foundation, Inc. (NeurIPS): Vancouver, Canada.
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Shi, Z;
Zhang, Q;
Lipani, A;
(2022)
StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts.
In:
Proceedings of 36th AAAI conference on Artificial intelligence.
(pp. pp. 11321-11329).
AAAI (Association for the Advancement of Artificial Intelligence): Palo Alto, CA, USA.
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Shi, Zhengxiang;
Lipani, Aldo;
(2023)
Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner.
In:
Proceedings of the 37th Conference on Neural Information Processing Systems.
NeurIPS: New Orleans, New Orleans, USA.
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Shi, Zhengxiang;
Lipani, Aldo;
(2023)
Rethink the Effectiveness of Text Data Augmentation: An Empirical
Analysis.
In:
ESANN 2023 proceedings: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
(pp. pp. 169-174).
ESANN
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Shi, Zhengxiang;
Wang, Xi;
Lipani, Aldo;
(2024)
Self Contrastive Learning for Session-Based Recommendation.
In: Goharian, Nazli and Tonellotto, Nicola and He, Yulan and Lipani, Aldo and McDonald, Graham and Macdonald, Craig and Ounis, Iadh, (eds.)
Advances in Information Retrieval (ECIR 2024).
(pp. pp. 3-20).
Springer: Cham, Switzerland.
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Yu, Youjing;
Shi, Zhengxiang;
Lipani, Aldo;
(2024)
Understanding Users’ Confidence in Spoken Queries for Conversational Search Systems.
In: Iliadis, Lazaros S and Maglogiannis, Ilias and Papaleonidas, Antonios and Pimenidis, Elias and Jayne, Chrisina, (eds.)
Communications in Computer and Information Science.
(pp. pp. 405-418).
Springer: Cham, Switzerland.
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Zhan, Q;
Liang, S;
Lipani, A;
Ren, Z;
Yilmaz, E;
(2019)
From Stances' Imbalance to Their Hierarchical Representation and Detection.
In: Liu, Ling and White, Ryen, (eds.)
Proceedings of WWW '19: The World Wide Web Conference.
(pp. pp. 2323-2332).
ACM: New York, USA.
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Zhang, Q;
Lipani, A;
Kirnap, O;
Yilmaz, E;
(2020)
Self-Attentive hawkes process.
In:
Proceedings of the 37th International Conference on Machine Learning.
(pp. pp. 11183-11193).
PMLR
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Zhang, Q;
Lipani, A;
Liang, S;
Yilmaz, E;
(2019)
Reply-Aided Detection of Misinformation via Bayesian Deep Learning.
In: Liu, Ling and White, Ryen, (eds.)
Proceedings of WWW '19 The World Wide Web Conference.
(pp. pp. 2333-2343).
ACM: New York, USA.
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Zhang, Q;
Lipani, A;
Yilmaz, E;
(2021)
Learning Neural Point Processes with Latent Graphs.
In:
WWW '21: Proceedings of the Web Conference 2021.
(pp. pp. 1495-1505).
ACM
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