Max Bartolo

1.1k total citations · 1 hit paper
13 papers, 486 citations indexed

About

Max Bartolo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Max Bartolo has authored 13 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 1 paper in Pulmonary and Respiratory Medicine. Recurrent topics in Max Bartolo's work include Topic Modeling (8 papers), Natural Language Processing Techniques (5 papers) and Multimodal Machine Learning Applications (3 papers). Max Bartolo is often cited by papers focused on Topic Modeling (8 papers), Natural Language Processing Techniques (5 papers) and Multimodal Machine Learning Applications (3 papers). Max Bartolo collaborates with scholars based in United Kingdom, Israel and United States. Max Bartolo's co-authors include Sebastian Riedel, Pontus Stenetorp, Alastair Moore, Yao Lu, Tristan Thrush, Douwe Kiela, Adina Williams, Amanpreet Singh, Candace Ross and Robin Jia and has published in prestigious journals such as Value in Health, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Empirical Methods in Natural Language Processing.

In The Last Decade

Max Bartolo

11 papers receiving 456 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

2022 248 citations Yao Lu, Max Bartolo et al. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Max Bartolo United Kingdom	6	398	164	43	15	13	13	486
Wangchunshu Zhou China	14	382 1.0×	174 1.1×	29 0.7×	11 0.7×	16 1.2×	37	476
Mor Geva United States	11	329 0.8×	85 0.5×	41 1.0×	12 0.8×	9 0.7×	29	383
Segev Shlomov Israel	5	387 1.0×	79 0.5×	50 1.2×	21 1.4×	7 0.5×	11	465
Ryuichi Takanobu China	11	418 1.1×	90 0.5×	67 1.6×	25 1.7×	13 1.0×	16	469
Panupong Pasupat United States	16	545 1.4×	144 0.9×	79 1.8×	25 1.7×	20 1.5×	21	602
Rotem Dror Israel	9	366 0.9×	57 0.3×	51 1.2×	18 1.2×	7 0.5×	13	427
Niklas Muennighoff United States	6	302 0.8×	55 0.3×	37 0.9×	16 1.1×	6 0.5×	8	379
Luu Anh Tuan Singapore	12	432 1.1×	68 0.4×	93 2.2×	16 1.1×	25 1.9×	31	497
Lianhui Qin United States	13	445 1.1×	127 0.8×	26 0.6×	7 0.5×	10 0.8×	20	486
Tu Vu United States	8	276 0.7×	75 0.5×	57 1.3×	7 0.5×	8 0.6×	15	328

Countries citing papers authored by Max Bartolo

Since Specialization

Citations

This map shows the geographic impact of Max Bartolo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Max Bartolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Max Bartolo more than expected).

Fields of papers citing papers by Max Bartolo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Max Bartolo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Max Bartolo. The network helps show where Max Bartolo may publish in the future.

Co-authorship network of co-authors of Max Bartolo

This figure shows the co-authorship network connecting the top 25 collaborators of Max Bartolo. A scholar is included among the top collaborators of Max Bartolo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Max Bartolo. Max Bartolo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

Bartolo, Max, et al.. (2025). Improving Reward Models with Synthetic Critiques. 4506–4520. 1 indexed citations

Baxter, Carl A., et al.. (2024). EE543 Hospital Healthcare Resource Utilization in People With Cystic Fibrosis Treated With Elexacaftor/Tezacaftor/Ivacaftor in Portugal: A Non-Interventional, Retrospective Study. Value in Health. 27(12). S162–S162.

Parrish, Alicia, Oana Inel, Hannah Rose Kirk, et al.. (2024). Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation. 388–406. 3 indexed citations

Land, Sander & Max Bartolo. (2024). Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models. 11631–11646. 1 indexed citations

Bartolo, Max, Andrew Bean, Scott A. Hale, et al.. (2024). The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models. 105236–105344. 1 indexed citations

Thrush, Tristan, Max Bartolo, Amanpreet Singh, et al.. (2022). Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 5228–5238. 98 indexed citations

Lu, Yao, Max Bartolo, Alastair Moore, Sebastian Riedel, & Pontus Stenetorp. (2022). Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 8086–8098. 248 indexed citations breakdown →

Bartolo, Max, Tristan Thrush, Sebastian Riedel, et al.. (2022). Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 9 indexed citations

Thrush, Tristan, Kushal Tirumala, Anmol Gupta, et al.. (2022). Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks. 174–181. 5 indexed citations

10.

Bartolo, Max, Tristan Thrush, Robin Jia, et al.. (2021). Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation. arXiv (Cornell University). 43 indexed citations

11.

Mozes, Maximilian, Max Bartolo, Pontus Stenetorp, Bennett Kleinberg, & Lewis D. Griffin. (2021). Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 8258–8270. 4 indexed citations

12.

Bartolo, Max, et al.. (2020). Beat the AI: Investigating Adversarial Human Annotations for Reading Comprehension. Empirical Methods in Natural Language Processing. 1 indexed citations

13.

Saeidi, Marzieh, Max Bartolo, Patrick Lewis, et al.. (2018). Interpretation of Natural Language Rules in Conversational Machine Reading. 2087–2097. 72 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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