Research

Publications and Outputs

Research publications and outputs that used Baskerville are listed below.

2026 16 publications

Bi, S., Brlec, K., Squires, A.G., et al. (2026) Computational Investigation of the Thermoelectric Performance of Environmentally Friendly and Earth-Abundant SrZn₂S₂O (ed.). ACS Applied Energy Materials, 9 (3): 1891–1902. doi:10.1021/acsaem.5c03742
Claes, R., Russell, P.P., Squires, A.G., et al. (2026) Optimizing the Thermoelectric Performance of the Earth-Abundant Layered Phosphide BaCuP through Defect Engineering (ed.). doi:10.26434/chemrxiv.15005826/v1
Cox, P.U., Russell, P.P., Crovetto, A., et al. (2026) Solphin: Photovoltaic efficiency analysis for bulk materials using Python. doi:10.48550/arxiv.2610.10028
Guo, M., Cheng, X., Lu, W., et al. (2026) Foundation-Guided Representation Alignment for Multimodal Medical Image Registration (ed.). Computer Vision – ECCV 2026, pp. 518–535. doi:10.1007/978-3-032-37435-6_28
Hu, H., Lin, D., Hou, Y., et al. (2026) Whence the Voice? Self-supervised Dual-source Audio-Visual Localisation via Selective Convergence (ed.). Computer Vision – ECCV 2026, pp. 210–228. doi:10.1007/978-3-032-37196-6_12
Jia, X., Thorley, A., Gomez, A., et al. (2026) Fourier-Net+: Band-Limited Spatial Representation for Efficient Medical Image Registration (ed.). IEEE Transactions on Neural Networks and Learning Systems, 37 (10): 5712–5726. doi:10.1109/TNNLS.2026.3688245
Juraschko, N., Rocha, F.K. and Khalid, S. (2026) Characterizing the Conformational Dynamics of the Ribose Transporter B Protein inEscherichia coli: Enhanced Sampling via Multiple Force Fields (ed.). Journal of Chemical Theory and Computation, 22 (5): 2156–2169. doi:10.1021/acs.jctc.5c02068
Kirkvold, C. and Gryn’ova, G. (2026) Persistent Homology using Nets: Topologically Informed Machine Learning Descriptors of Framework Materials (ed.). doi:10.26434/chemrxiv.15006213/v1
Leyva, R., Maple, C. and Sanchez, V. (2026) Morph Detection as Anomalies in the Compressed Frequency Domain (ed.). IEEE Transactions on Biometrics, Behavior, and Identity Science, 8 (5): 919–930. doi:10.1109/TBIOM.2026.3692617
Leyva, R., Selvaraj, P., Maple, C., et al. (2026) Leveraging Synthetic Data to Reduce Biases in Face Recognition Systems (ed.). Proceedings of the 2026 ACM Workshop on Information Hiding and Multimedia Security, pp. 213–222. doi:10.1145/3785353.3815072
Li, K., Claes, R., Squires, A.G., et al. (2026) Resonant Doping in Binary Sb(V)-oxide Sb2O5 for High-Mobility Transparent Conductors (ed.). doi:10.26434/chemrxiv.15001890/v1
Ren, F., Spooner, K.B., Han, D., et al. (2026) Thiocyanate Ligands Induce a Trade-Off between Carrier Transport and Nonradiative Relaxation through Halide Tuning in Two-Dimensional Lead Halide Perovskites (ed.). The Journal of Physical Chemistry Letters, 17 (35): 10071–10080. doi:10.1021/acs.jpclett.6c02211
Shymanovich, M., Squires, A.G., Brgoch, J., et al. (2026) Disorder Tolerance in LED Phosphor Host CaAlSiN3 : Correlated Cation Disorder with Minimal Electronic Penalty (ed.). doi:10.26434/chemrxiv.15000720/v1
Ye, Z., Mozafarian, M., Cavallaro, P.A.R., et al. (2026) Automated multi-category tunnel damage detection and report generation from ultra-high-resolution panoramic laser images (ed.). Tunnelling and Underground Space Technology, 168: 107194. doi:10.1016/j.tust.2025.107194
Zhang, S. and Liu, J.K. (2026) SeqProFT: Sequence-Only Protein Property Prediction With LoRA Finetuning (ed.). IEEE Transactions on Artificial Intelligence, 7 (6): 3194–3204. doi:10.1109/TAI.2025.3636109
Zhang, S., Zhang, H., Hong, R., et al. (2026) GPCR Ligand Bioactivity Prediction with Physics-Informed Dual-State Query Learning. doi:10.48550/arxiv.2609.16468

2025 41 publications

Alazraki, L., Chen, L., Brassard, A., et al. (2025) AgentCoMa: A Compositional Benchmark Mixing Commonsense and Mathematical Reasoning in Real-World Scenarios. doi:10.48550/arXiv.2508.19988
Asebiah, D.C., Peters, A.N., Borgia, L., et al. (2025) (NH₃(CH₂)₇NH₃)₂Sn₃I₁₀, a Vacancy-Ordered Three-Dimensional Tin(II) Perovskite-Derived Semiconductor (ed.). Chemistry of Materials, 37 (5): 1983–1994. doi:10.1021/acs.chemmater.4c03411
Bellos, D., Allsopp, J., Ho, E.M.L., et al. (2025) FlowCron - Increasing access to HPC by wrapping Globus into a function-as-a-service (ed.). Wellcome Open Research, 10: 4. doi:10.12688/wellcomeopenres.23491.1
Bi, S., Savory, C.N., Squires, A.G., et al. (2025) Excellent thermoelectric performance of Bi₂MO₄Cl (M = Y, La, and Bi) derived from ultra-low lattice thermal conductivity (ed.). Journal of Materials Chemistry A, 13 (41): 35507–35520. doi:10.1039/D5TA05523G
Cassingham, M.A., Lamahewage, S.N.S., Goh, Y.G., et al. (2025) Ordered Cationic Mixing in a 1D Organic–Inorganic Hybrid (ed.). Chemistry of Materials, 37 (7): 2418–2426. doi:10.1021/acs.chemmater.4c02364
Chan, R.S.-Y., Nanni, F., Lazauskas, T., et al. (2025) Retrieval-augmented reasoning with lean language models. doi:10.48550/arXiv.2508.11386
Cheng, X., Zhang, T., Lu, W., et al. (2025) SACB-Net: Spatial-awareness Convolutions for Medical Image Registration. doi:10.48550/arXiv.2503.19592
Claes, R. and Scanlon, D.O. (2025) New Insights into the Intrinsic Transport Properties of Sb₂O₅and ZnSb₂O₆ (ed.). physica status solidi (RRL) – Rapid Research Letters, 19 (11). doi:10.1002/pssr.202400399
Claes, R., Li, K., Squires, A.G., et al. (2025) Screening ASb2O6 (A = Mg, Ca, Sr, Ba, Cd) for High Performance Transparent Conducting Oxides (ed.). doi:10.26434/chemrxiv-2025-39bbf
Claes, R., Scanlon, D., Rignanese, G.-M., et al. (2025) First-Principles Understanding of Hole Mobility and Intrinsic Transport Mechanisms in Sn(II) Oxides (ed.). doi:10.26434/chemrxiv-2025-x0hmk
Di Francesco, D., Forrest, A., McGarry, F., et al. (2025) Is Your Model Risk ALARP? Evaluating Prospective Safety-Critical Applications of Complex Models. doi:10.48550/arXiv.2507.10817
Drury, B., Machado, I.P., Gao, Z., et al. (2025) Multi-task deep learning for automatic image segmentation and treatment response assessment in metastatic ovarian cancer (ed.). International Journal of Computer Assisted Radiology and Surgery, 20 (9): 1923–1929. doi:10.1007/s11548-025-03484-0
Ftouhi, F., Dsouza, R., Gamboa, L.C.L., et al. (2025) OldJoe at AVeriTeC: In-context learning for fact-checking (ed.). Proceedings of the Eighth Fact Extraction and VERification Workshop (FEVER), pp. 238–246. doi:10.18653/v1/2025.fever-1.18
Hickling, T., MacArt, J.F., Sirignano, J., et al. (2025) OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows. doi:10.48550/arXiv.2507.05149
Hiray, R. and Kovatchev, V. (2025) Storybranch - generating multimedia content from novels (ed.). Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations), pp. 485–493. doi:10.18653/v1/2025.naacl-demo.39
Huang, Q., Ai, H. and Jiao, J. (2025) Structure-Aware Feature Rectification with Region Adjacency Graphs for Training-Free Open-Vocabulary Semantic Segmentation. doi:10.48550/arXiv.2512.07360
Knight, J.C., Jersakova, R. and James Bishop (2025) Practical Perspectives on Black-Box Critical Error Detection for Machine Translation. The Alan Turing Institute. doi:10.5281/zenodo.14639666
Kumar, A., Akbar, A., Lesmes, H., et al. (2025) Machine-Learning-Assisted Discovery of Cr³⁺-Based Near-Infrared Phosphors (ed.). Chemistry of Materials, 37 (19): 7762–7770. doi:10.1021/acs.chemmater.5c01208
Kwan, E., Qureshi, R., Fletcher, L., et al. (2025) Onboard Mission Replanning for Adaptive Cooperative Multi-Robot Systems. doi:10.48550/arXiv.2506.06094
Laganier, C., Fletcher, L., Kwan, E., et al. (2025) Efficient SAR Vessel Detection for FPGA-Based On-Satellite Sensing. doi:10.48550/arXiv.2507.04842
Lam, T.K., Gaido, M., Papi, S., et al. (2025) Prepending or Cross-Attention for Speech-to-Text? An Empirical Comparison. doi:10.48550/arXiv.2501.02370
Leifeld, J., Parsons, A.C., Morscher, A., et al. (2025) Disorder-driven fast Na+ transport: From crystalline to amorphous networks in the mixed-anion NaTaOxCl6−2x oxychlorides (ed.). doi:10.26434/chemrxiv-2025-27tgk
Leyva, R., Gregory, E. and Maple, C. (2025) Attack Vectors for Face Recognition Systems: A Comprehensive Review (ed.). ACM Computing Surveys, 58 (1): 1–37. doi:10.1145/3736753
Li, H. and Jiao, J. (2025) An Exploratory Study on Abstract Images and Visual Representations Learned from Them. doi:10.48550/arXiv.2509.14149
Lin, D., Hu, H. and Jiao, J. (2025) What Time Tells Us? An Explorative Study of Time Awareness Learned from Static Images. doi:10.48550/arXiv.2503.17899
Llewellyn, M., Thornton, I., Bishop, J., et al. (2025) Correcting Prompt Dependence in LLM Benchmarks: A Bayesian Hierarchical Model with Embedding-Space Clustering. doi:10.48550/arXiv.2510.05709
Neep, T., Nikolopoulos, K. and Slater, M. (2025) Accelerating Garfield++ with CUDA. doi:10.48550/arXiv.2509.15377
Qu, C., Chen, H. and Jiao, J. (2025) Exploring Image Representation with Decoupled Classical Visual Descriptors. doi:10.48550/arXiv.2510.14536
Russell, P., Li, K., Claes, R., et al. (2025) Computational prediction of Y-doped Cd2Sb2O7 as a competitive Sb-based n-type Transparent Conducting Oxide (ed.). doi:10.26434/chemrxiv-2025-c1r3l
Sibug-Torres, S.M., Niihori, M., Wyatt, E., et al. (2025) Transient Au–Cl adlayers modulate the surface chemistry of gold nanoparticles during redox reactions (ed.). Nature Chemistry, 18 (2): 294–301. doi:10.1038/s41557-025-01989-4
Song, T., Manche, A., Xie, D., et al. (2025) Breaking the Durability–Power Trade‐Off: Boron‐Directed Faceted O3 Cathodes for High‐Rate Sodium‐Ion Batteries (ed.). Advanced Energy Materials. doi:10.1002/aenm.202505657
Souly, A., Rando, J., Chapman, E., et al. (2025) Poisoning Attacks on LLMs Require a Near-constant Number of Poison Samples. doi:10.48550/arXiv.2510.07192
Streit, J.O., Chan, S.H.S., Burridge, C., et al. (2025) Long-range electrostatic forces govern how proteins fold on the ribosome (ed.). doi:10.1101/2025.02.10.637539
Wolf, F., Chau, T., Han, D., et al. (2025) Oriented Naphthalene-O-propylammonium-Based (NOP)₄AuB^IIII₈ (B = Au, Bi, Sb) Ruddlesden–Popper Two-Dimensional Gold Double Perovskite Thin Films Featuring High Charge-Carrier Mobility (ed.). Journal of the American Chemical Society, 147 (20): 16992–17001. doi:10.1021/jacs.5c01102
Wood, R. and McDonough, K. (2025) MapReader_railspace_London_imago_mundi_2025. doi:10.5281/zenodo.14522925
Xia, X. and Ming, X. (2025) SynxFlow: A GPU-accelerated Python package for multi-hazard simulations (ed.). Journal of Open Source Software, 10 (111): 7586. doi:10.21105/joss.07586
Ye, Z., Lin, W., Faramarzi, A., et al. (2025) SAM4Tun: No-training model for tunnel lining point cloud component segmentation (ed.). Tunnelling and Underground Space Technology, 158: 106401. doi:10.1016/j.tust.2025.106401
Ye, Z., Mozafarian, M., Cavallaro, P.A.R., et al. (2025) Automated Tunnel Damage Report Generation (ed.). doi:10.2139/ssrn.5214957
Zhang, T., Cheng, X., Cheng, J., et al. (2025) Plasticine: A Traceable Diffusion Model for Medical Image Translation. doi:10.48550/arXiv.2512.18455
Zhou, S., Schöner, H., Lyu, H., et al. (2025) BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting. doi:10.48550/arXiv.2509.00622
Zhou, S., Schöner, H., Lyu, H., et al. (2025) BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting (ed.). Proceedings of the 34th ACM International Conference on Information and Knowledge Management, pp. 4498–4508. doi:10.1145/3746252.3761278

2024 60 publications

Ahn, M., Streit, J.O., Waudby, C.A., et al. (2024) Amyloid forming human lysozyme intermediates are stabilised by non-native amide-π interactions (ed.). doi:10.1101/2024.12.20.629167
Aljasem, D. and Howes, A. (2024) Understanding the Effects of Visual Impairment on Visual Search (ed.). Universal Access in Human-Computer Interaction, pp. 363–381. doi:10.1007/978-3-031-60884-1_25
Asebiah, D.C., Mozur, E.M., Koegel, A.A., et al. (2024) Defect-Limited Mobility and Defect Thermochemistry in Mixed A-Cation Tin Perovskites: (CH₃NH₃)_1–xCs_xSnBr₃ (ed.). ACS Applied Energy Materials, 7 (18): 7992–8003. doi:10.1021/acsaem.4c01708
Ball, N.D., MacArt, J.F. and Sirignano, J. (2024) Online Optimisation of Machine Learning Collision Models to Accelerate Direct Molecular Simulation of Rarefied Gas Flows. doi:10.48550/arXiv.2411.13423
Bartlett, J.J., Davey, C.E., Johnston, L.A., et al. (2024) Recovering high‐quality fiber orientation distributions from a reduced number of diffusion‐weighted images using a model‐driven deep learning architecture (ed.). Magnetic Resonance in Medicine, 92 (5): 2193–2206. doi:10.1002/mrm.30187
Baziotis, C., Zhang, B., Birch, A., et al. (2024) When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale (ed.). Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pp. 6297–6324. doi:10.18653/v1/2024.naacl-long.349
Chen, H., Hou, Y., Qu, C., et al. (2024) $360+x$: A Panoptic Multi-modal Scene Understanding Dataset (ed.). 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 19373–19382. doi:10.1109/CVPR52733.2024.01833
Chen, H., Hou, Y., Qu, C., et al. (2024) 360+x: A Panoptic Multi-modal Scene Understanding Dataset. arXiv. doi:10.48550/arXiv.2404.00989
Chen, P., Yu, S., Guo, Z., et al. (2024) Is It Good Data for Multilingual Instruction Tuning or Just Bad Multilingual Evaluation for Large Language Models? (ed.). Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 9706–9726. doi:10.18653/v1/2024.emnlp-main.542
Chen, X., Diggle, P., Zidek, J.V., et al. (2024) Highly Multivariate Large-scale Spatial Stochastic Processes -- A Cross-Markov Random Field Approach. doi:10.48550/arXiv.2408.10396
Cheng, X., Jia, X., Lu, W., et al. (2024) WiNet: Wavelet-Based Incremental Learning for Efficient Medical Image Registration (ed.). Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, pp. 761–771. doi:10.1007/978-3-031-72069-7_71
De Leon, F.A.L., Madabushi, H.T. and Lee, M. (2024) Code-Mixed Probes Show How Pre-Trained Models Generalise On Code-Switched Text. doi:10.48550/arXiv.2403.04872
Dou, W., Spooner, K., Kavanagh, S., et al. (2024) Giant Band Degeneracy via Orbital Engineering Enhances Thermoelectric Performance from Sb2Si2Te6 to Sc2Si2Te6 (ed.). doi:10.26434/chemrxiv-2024-hm6vh
Evans, M.L., Bergsma, J., Merkys, A., et al. (2024) Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange (ed.). Digital Discovery, 3 (8): 1509–1533. doi:10.1039/D4DD00039K
Falck, F., Wang, Z. and Holmes, C. (2024) Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective. doi:10.48550/arXiv.2406.00793
Fonseca, M. and Cohen, S. (2024) Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals? (ed.). Findings of the Association for Computational Linguistics ACL 2024, pp. 8599–8618. doi:10.18653/v1/2024.findings-acl.508
Gerard, L., Scherbela, M., Sutterud, H., et al. (2024) Transferable Neural Wavefunctions for Solids. doi:10.48550/arXiv.2405.07599
Guo, M. (2024) Unsupervised Multi-modal Medical Image Registration via Invertible Translation (ed.). Computer Vision – ECCV 2024, pp. 22–38. doi:10.1007/978-3-031-72751-1_2
Hackenburg, K., Tappin, B.M., Röttger, P., et al. (2024) Evidence of a log scaling law for political persuasion with large language models. doi:10.48550/arXiv.2406.14508
Hu, H., Yu, S., Chen, P., et al. (2024) Fine-tuning Large Language Models with Sequential Instructions. doi:10.48550/arXiv.2403.07794
Hu, J., Squires, A.G., Kondek, J., et al. (2024) Enabling ionic transport in Li3AlP2 the roles of defects and disorder (ed.). doi:10.26434/chemrxiv-2024-3s0kh-v2
Iyer, V., Malik, B., Stepachev, P., et al. (2024) Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation (ed.). Proceedings of the Ninth Conference on Machine Translation, pp. 1393–1409. doi:10.18653/v1/2024.wmt-1.128
Iyer, V., Malik, B., Zhu, W., et al. (2024) Exploring Very Low-Resource Translation with LLMs: The University of Edinburgh’s Submission to AmericasNLP 2024 Translation Task (ed.). Proceedings of the 4th Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP 2024), pp. 209–220. doi:10.18653/v1/2024.americasnlp-1.25
Jiang, D., Fonseca, M. and Cohen, S. (2024) LeanReasoner: Boosting Complex Logical Reasoning with Lean (ed.). Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pp. 7497–7510. doi:10.18653/v1/2024.naacl-long.416
Kavanagh, S.R., Nielsen, R.S., Hansen, J.L., et al. (2024) Intrinsic point defect tolerance in selenium for indoor and tandem photovoltaics (ed.). doi:10.26434/chemrxiv-2024-91h02
Khanuja, S., Iyer, V., He, C., et al. (2024) Towards Automatic Evaluation for Image Transcreation. doi:10.48550/arXiv.2412.13717
Kin Lam, T., Birch, A. and Haddow, B. (2024) Compact Speech Translation Models via Discrete Speech Units Pretraining (ed.). Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024), pp. 114–124. doi:10.18653/v1/2024.iwslt-1.16
Klimaszewski, M., Andruszkiewicz, P. and Birch, A. (2024) Is Modularity Transferable? A Case Study through the Lens of Knowledge Distillation. doi:10.48550/arXiv.2403.18804
Klimaszewski, M., Andruszkiewicz, P. and Birch, A. (2024) No Train but Gain: Language Arithmetic for training-free Language Adapters enhancement. doi:10.48550/arXiv.2404.15737
Ko, S., Dorrell, J., Alter, E., et al. (2024) Extreme Defect Tolerance for Electrochemical Intercalation in Wadsley–Roth Structures Demonstrated by Metastable NaNb7O18 (ed.). doi:10.26434/chemrxiv-2024-z07w1
Kovatchev, V. and Lease, M. (2024) Benchmark Transparency: Measuring the Impact of Data on Evaluation (ed.). Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pp. 1536–1551. doi:10.18653/v1/2024.naacl-long.86
Lazauskas, T. and Llewellyn-Jones, D. (2024) Benchmarking the performance of GPT-2 type applications on GPU-accelerated computing resources. The Alan Turing Institute. doi:10.5281/zenodo.13349540
Li, Z., Yang, X. and Zhang, J. (2024) GAMAFlow: Estimating 3D Scene Flow via Grouped Attention and Global Motion Aggregation (ed.). ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3955–3959. doi:10.1109/ICASSP48485.2024.10447849
Lou, W.T., Sutterud, H., Cassella, G., et al. (2024) Neural Wave Functions for Superfluids (ed.). Physical Review X, 14 (2). doi:10.1103/PhysRevX.14.021030
Machado, I.P., Reithmeir, A., Kogl, F., et al. (2024) A Self-supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer (ed.). Biomedical Image Registration, pp. 295–307. doi:10.1007/978-3-031-73480-9_23
Malik, Z., Broadley, S., Herkelrath, S.J.C., et al. (2024) Observation and enhancement through alkali metal doping of p-type conductivity in the layered oxyselenides Sr₂ZnO₂Cu₂Se₂and Ba₂Zn_1−xO_2−xCu₂Se₂ (ed.). Journal of Materials Chemistry C, 12 (43): 17574–17586. doi:10.1039/D4TC02458C
Malik, Z., Kemp, L., Grosso, B.F., et al. (2024) Transport Properties of Doped Wide Band Gap Layered Oxychalcogenide Semiconductors Sr₂GaO₃CuCh, Sr₂ScO₃CuCh, and Sr₂InO₃CuCh (Ch = S or Se) (ed.). Chemistry of Materials, 36 (22): 11326–11337. doi:10.1021/acs.chemmater.4c02760
McDonough, K., Beelen, K., Wilson, D.C.S., et al. (2024) Reading Maps at a Distance: Texts on Maps as New Historical Data (ed.). Imago Mundi, 76 (2): 296–307. doi:10.1080/03085694.2024.2453336
Mohamed, M., Cunningham, H.J., Barbano, R., et al. (2024) RDM: Recurrent Diffusion Model for Human Motion Generation. doi:10.48550/arXiv.2406.07169
Murdock, B.E., Cen, J., Squires, A.G., et al. (2024) Li‐Site Defects Induce Formation of Li‐Rich Impurity Phases: Implications for Charge Distribution and Performance of LiNi_0.5−_xM_xMn_1.5O₄ Cathodes (M = Fe and Mg; x = 0.05–0.2) (ed.). Advanced Materials, 36 (32). doi:10.1002/adma.202400343
Pal, P., Birch, A. and Heafield, K. (2024) Document-Level Machine Translation with Large-Scale Public Parallel Corpora (ed.). Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 13185–13197. doi:10.18653/v1/2024.acl-long.712
Pfau, D., Axelrod, S., Sutterud, H., et al. (2024) Accurate computation of quantum excited states with neural networks (ed.). Science, 385 (6711). doi:10.1126/science.adn0137
Qiu, Y., Zhao, Z., Ziser, Y., et al. (2024) Spectral Editing of Activations for Large Language Model Alignment. doi:10.48550/arXiv.2405.09719
Qiu, Y., Zhao, Z., Ziser, Y., et al. (2024) Are Large Language Model Temporally Grounded? (ed.). Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pp. 7064–7083. doi:10.18653/v1/2024.naacl-long.391
Ramírez, G., Birch, A. and Titov, I. (2024) Optimising Calls to Large Language Models with Uncertainty-Based Two-Tier Selection. arXiv. doi:10.48550/arXiv.2405.02134
Ramírez, G., Lindemann, M., Birch, A., et al. (2024) Cache & Distil: Optimising API Calls to Large Language Models (ed.). Findings of the Association for Computational Linguistics ACL 2024, pp. 11838–11853. doi:10.18653/v1/2024.findings-acl.704
Rockwell, K., Hirst, J., Ostler, T.A., et al. (2024) Pseudospectral Landau-Lifshitz description of magnetization dynamics (ed.). Physical Review B, 109 (18). doi:10.1103/PhysRevB.109.L180404
Spooner, K.B., Einhorn, M., Davies, D.W., et al. (2024) ThermoParser: Streamlined Analysis of Thermoelectric Properties (ed.). Journal of Open Source Software, 9 (97): 6340. doi:10.21105/joss.06340
Squires, A.G., Ganeshkumar, L., Savory, C.N., et al. (2024) Oxygen Dimerization as a Defect-Driven Process in Bulk LiNiO₂ (ed.). ACS Energy Letters, 9 (8): 4180–4187. doi:10.1021/acsenergylett.4c01307
Streit, J.O., Bukvin, I.V., Chan, S.H.S., et al. (2024) The ribosome lowers the entropic penalty of protein folding (ed.). Nature, 633 (8028): 232–239. doi:10.1038/s41586-024-07784-4
Streit, J.O., Chan, S.H.S., Daya, S., et al. (2024) Rational design of¹⁹F NMR labelling sites to probe protein structure and interactions (ed.). doi:10.1101/2024.12.11.627779
Sun, Z. and Miceli-Barone, A.V. (2024) Scaling Behavior of Machine Translation with Large Language Models under Prompt Injection Attacks. doi:10.48550/arXiv.2403.09832
Wang, W., Haddow, B. and Birch, A. (2024) Retrieval-Augmented Multilingual Knowledge Editing (ed.). Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 335–354. doi:10.18653/v1/2024.acl-long.21
Wang, W., Haddow, B., Wu, M., et al. (2024) Sharing Matters: Analysing Neurons Across Languages and Tasks in LLMs. doi:10.48550/arXiv.2406.09265
Wang, W., Wu, M., Haddow, B., et al. (2024) Bridging the Language Gaps in Large Language Models with Inference-Time Cross-Lingual Intervention. doi:10.48550/arXiv.2410.12462
Włodarski, T., Streit, J.O., Mitropoulou, A., et al. (2024) Bayesian reweighting of biomolecular structural ensembles using heterogeneous cryo-EM maps with the cryoENsemble method (ed.). Scientific Reports, 14 (1). doi:10.1038/s41598-024-68468-7
Xiao, C., Zuo, Z. and Wang, S. (2024) FedGA: Federated Learning with Gradient Alignment for Error Asymmetry Mitigation. doi:10.48550/arXiv.2412.16582
Ye, Z., Lovell, L., Faramarzi, A., et al. (2024) Sam-Based Instance Segmentation Models for the Automation of Structural Damage Detection (ed.). doi:10.2139/ssrn.4750668
Zhang, T., Zheng, S., Cheng, J., et al. (2024) Structure and Intensity Unbiased Translation for 2D Medical Image Segmentation (ed.). IEEE Transactions on Pattern Analysis and Machine Intelligence, 46 (12): 10060–10075. doi:10.1109/TPAMI.2024.3434435
Zhao, Z., Ziser, Y. and Cohen, S.B. (2024) Layer by Layer: Uncovering Where Multi-Task Learning Happens in Instruction-Tuned Large Language Models. doi:10.48550/arXiv.2410.20008

2023 25 publications

Bogoychev, N. and Chen, P. (2023) Terminology-Aware Translation with Constrained Decoding and Large Language Model Prompting (ed.). Proceedings of the Eighth Conference on Machine Translation, pp. 890–896. doi:10.18653/v1/2023.wmt-1.80
Bogoychev, N., van der Linde, J., Nail, G., et al. (2023) OpusCleaner and OpusTrainer, open source toolkits for training Machine Translation and Large language models. doi:10.48550/arXiv.2311.14838
Cassella, G., Sutterud, H., Azadi, S., et al. (2023) Discovering Quantum Phase Transitions with Fermionic Neural Networks (ed.). Physical Review Letters, 130 (3). doi:10.1103/PhysRevLett.130.036401
Chen, H., Qu, C., Zhang, Y., et al. (2023) Multi-view Self-supervised Disentanglement for General Image Denoising (ed.). 2023 IEEE/CVF International Conference on Computer Vision (ICCV), pp. 12247–12257. doi:10.1109/ICCV51070.2023.01128
Chen, P., Ji, S., Bogoychev, N., et al. (2023) Monolingual or Multilingual Instruction Tuning: Which Makes a Better Alpaca. doi:10.48550/arXiv.2309.08958
Deng, Z., Ma, Y., Liu, Y., et al. (2023) MusiLingo: Bridging Music and Text with Pre-trained Language Models for Music Captioning and Query Response. arXiv. doi:10.48550/arXiv.2309.08730
Duan, J., Jia, X., Bartlett, J., et al. (2023) Arbitrary Order Total Variation for Deformable Image Registration (ed.). Pattern Recognition, 137: 109318. doi:10.1016/j.patcog.2023.109318
Falck, F., Williams, C., Danks, D., et al. (2023) A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. doi:10.48550/arXiv.2301.08187
Fonseca, M. and Cohen, S.B. (2023) Can Large Language Models Follow Concept Annotation Guidelines? A Case Study on Scientific and Financial Domains. doi:10.48550/arXiv.2311.08704
Hermann, J., Spencer, J., Choo, K., et al. (2023) Ab initio quantum chemistry with neural-network wavefunctions (ed.). Nature Reviews Chemistry, 7 (10): 692–709. doi:10.1038/s41570-023-00516-8
Hirst, J., Ruta, S., Jackson, J., et al. (2023) Simulations of magnetization reversal in FM/AFM bilayers with THz frequency pulses (ed.). Scientific Reports, 13 (1). doi:10.1038/s41598-023-39175-6
Iyer, V., Barba, E., Birch, A., et al. (2023) Code-Switching with Word Senses for Pretraining in Neural Machine Translation (ed.). Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 12889–12901. doi:10.18653/v1/2023.findings-emnlp.859
Iyer, V., Chen, P. and Birch, A. (2023) Towards Effective Disambiguation for Machine Translation with Large Language Models (ed.). Proceedings of the Eighth Conference on Machine Translation, pp. 482–495. doi:10.18653/v1/2023.wmt-1.44
Jia, X., Bartlett, J., Chen, W., et al. (2023) Fourier-Net: Fast Image Registration with Band-Limited Deformation (ed.). Proceedings of the AAAI Conference on Artificial Intelligence, 37 (1): 1015–1023. doi:10.1609/aaai.v37i1.25182
McGough, W., Buddenkotte, T., Ursprung, S., et al. (2023) Automated Small Kidney Cancer Detection in Non-Contrast Computed Tomography. doi:10.48550/arXiv.2312.05258
Miceli Barone, A.V., Barez, F., Cohen, S.B., et al. (2023) The Larger they are, the Harder they Fail: Language Models do not Recognize Identifier Swaps in Python (ed.). Findings of the Association for Computational Linguistics: ACL 2023, pp. 272–292. doi:10.18653/v1/2023.findings-acl.19
Qiu, Y., Ziser, Y., Korhonen, A., et al. (2023) Detecting and Mitigating Hallucinations in Multilingual Summarisation (ed.). Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 8914–8932. doi:10.18653/v1/2023.emnlp-main.551
Sarkar, S., Thorpe, L., Benetos, E., et al. (2023) Leveraging Synthetic Data for Improving Chamber Ensemble Separation (ed.). 2023 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp. 1–5. doi:10.1109/WASPAA58266.2023.10248118
Wang, H., Oh, J.O., Jin Chang, H., et al. (2023) GazeCaps: Gaze Estimation with Self-Attention-Routed Capsules (ed.). 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2669–2677. doi:10.1109/CVPRW59228.2023.00267
Wang, H., Zhang, Z., Cheng, Y., et al. (2023) High-Fidelity Eye Animatable Neural Radiance Fields for Human Face. doi:10.48550/arXiv.2308.00773
Williams, C., Falck, F., Deligiannidis, G., et al. (2023) A Unified Framework for U-Net Design and Analysis. doi:10.48550/arXiv.2305.19638
Xia, X., Jarsve, K.T., Dijkstra, T., et al. (2023) An integrated hydrodynamic model for runoff-generated debris flows with novel formulation of bed erosion and deposition (ed.). Engineering Geology, 326: 107310. doi:10.1016/j.enggeo.2023.107310
Xiao, C. and Wang, S. (2023) Triplets Oversampling for Class Imbalanced Federated Datasets (ed.). Machine Learning and Knowledge Discovery in Databases: Research Track, pp. 368–383. doi:10.1007/978-3-031-43415-0_22
Zhang, B., Haddow, B. and Birch, A. (2023) Prompting Large Language Model for Machine Translation: A Case Study. doi:10.48550/arXiv.2301.07069
Zhao, Z., Ziser, Y., Webber, B., et al. (2023) A Joint Matrix Factorization Analysis of Multilingual Representations (ed.). Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 12764–12783. doi:10.18653/v1/2023.findings-emnlp.851

2022 9 publications

Grenander, M., Cohen, S.B. and Steedman, M. (2022) Sentence-Incremental Neural Coreference Resolution (ed.). Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 427–443. doi:10.18653/v1/2022.emnlp-main.28
Jia, X., Bartlett, J., Zhang, T., et al. (2022) U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration? (ed.). Machine Learning in Medical Imaging, pp. 151–160. doi:10.1007/978-3-031-21014-3_16
Mould, M. and Gerosa, D. (2022) Gravitational-wave population inference at past time infinity (ed.). Physical Review D, 105 (2). doi:10.1103/PhysRevD.105.024076
Mould, M., Gerosa, D. and Taylor, S.R. (2022) Deep learning and Bayesian inference of gravitational-wave populations: Hierarchical black-hole mergers (ed.). Physical Review D, 106 (10). doi:10.1103/PhysRevD.106.103013
Na, J., Han, D., Chang, H.J., et al. (2022) Contrastive Vicinal Space for Unsupervised Domain Adaptation (ed.). Computer Vision – ECCV 2022, pp. 92–110. doi:10.1007/978-3-031-19830-4_6
Qiu, Y. and Cohen, S.B. (2022) Abstractive Summarization Guided by Latent Hierarchical Document Structure. doi:10.48550/arXiv.2211.09458
Shao, S., Ziser, Y. and Cohen, S.B. (2022) Gold Doesn't Always Glitter: Spectral Removal of Linear and Nonlinear Guarded Attribute Information. doi:10.48550/arXiv.2203.07893
Tse, T.H.E., Kim, K.I., Leonardis, A., et al. (2022) Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution (ed.). 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1654–1664. doi:10.1109/CVPR52688.2022.00171
Tse, T.H.E., Zhang, Z., Kim, K.I., et al. (2022) S$$^2$$Contact: Graph-Based Network for 3D Hand-Object Contact Estimation with Semi-supervised Learning (ed.). Computer Vision – ECCV 2022, pp. 568–584. doi:10.1007/978-3-031-19769-7_33

2021 3 publications

Azadi, S., Drummond, N. D. and Foulkes, W. M. C. (2021) Quasiparticle Effective Mass of the Three-Dimensional Fermi Liquid by Quantum Monte Carlo (ed.). Physical Review Letters, 127 (8). doi:10.1103/PhysRevLett.127.086401
Coavoux, M. and Cohen, S.B. (2021) Learning to Match Mathematical Statements with Proofs. doi:10.48550/arXiv.2102.02110
Xiao, C. and Wang, S. (2021) An Experimental Study of Class Imbalance in Federated Learning (ed.). 2021 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1–7. doi:10.1109/SSCI50451.2021.9660072