Programme

Mapping the Old World Graphosphere, and Beyond

Charting the world before print as a totality, from many traditions and many witnesses: writing above all, but also material remains, environments, and whatever holds across time in language, mind and body.

Chair: Roger Martínez-Dávila (University of Colorado & Plus Ultra Collective)

What records are available to LLMs to reveal the world before print? Working across written evidence, languages, and any other forms of witness, the panel asks how surviving material becomes usable evidence, both within traditions and across them, considered as a totality or Gestalt. A proper mapping would show, within a culture, what was written, where and when, and how much of it survives; across cultures, it would allow the comparisons that only a totality permits, from the travels of scripts and genres to the shape of loss itself. Machine-Scale History, on Saturday, comes at the same problem from the other side: not what the evidence is, but what can be inferred from it.

• Marieke Meelen (University of Cambridge)

  Title to be announced

  Live Keynote In-Person

• Irina A. Zhilina (Russian State University of Justice, Voronezh)

  When Beauty Was a Ribbon: Can Large Language Models Read Church Slavonic Lexicography Without Inventing Semantic Continuity?

  Pre-Recorded Talk Online

  Abstract

  In the Regional Great Russian Dictionary of 1852, красота ('beauty') denotes a bride's ribbon, placed by the priest into the Gospel book during the wedding rite. In the Suprasl Codex of the 10th–11th centuries, its root renders Greek κόσμος 'ornament, order, universe'. The familiar aesthetic sense—'attractiveness'—is a late and derived development. Historical lexicography preserves this stratigraphy; large language models, trained overwhelmingly on post-print text, may not. This pilot study tests whether LLMs can read pre-print-era dictionary definitions without projecting modern semantics backwards.

  The material comprises entries for красота in eleven Church Slavonic and historical Russian dictionaries documenting the language of the pre-print era—from the earliest Slavonic manuscripts of the 10th–11th centuries onwards—in editions from the eighteenth to the twenty-first century. The pre-print past becomes machine-readable only through this later lexicographic mediation, which is precisely where models may substitute their own training distribution for the historical record. A completed manual componential and Greek–Slavonic analysis of these sources serves as the gold standard: humanistic scholarship as the evaluation benchmark for AI. Definitions are presented to frontier models under three conditions—unattributed, source-attributed, and with an explicit question about the relation to modern meaning—separating inference from the text, recognition of the source, and knowledge of later semantics. Errors are classified as epistemic upgrades, anachronisms, fabricated components, fabricated Greek glosses, and invented continuity narratives.

  Two single-model series (42 responses) show fabrication migrating to the continuity condition: the model refused to reproduce unseen dictionary content in direct probes, read the authentic regional label correctly, yet invented two contradictory expansions for its corrupted variant, produced an anachronistic attribution, and inserted a nonexistent word into a Septuagint quote. The paper proposes an anti-fabrication protocol for LLM-assisted work with historical lexicography—a contribution to defending pre-print scholarship against dangerously plausible AI output.

• Dmitri Sitchinava (University of Potsdam)

  From Variant Place-Names to Machine-Readable Borderlands: LLM-Assisted Extraction of Slavic Toponymy in Livonia before 1700

  Pre-Recorded Talk In-Person

  Abstract

  This paper presents an experiment in using a commercially available frontier LLM to extract, normalize, and critically verify Slavic toponymic evidence for Livonia and its adjoining eastern Baltic borderlands before 1700. The corpus belongs to a transitional manuscript and early-print ecology, in which Latvian and Estonian vernacular textual traditions remained comparatively sparse while German, Latin, Polish, Ruthenian, and Russian documentary practices intersected.

  The Slavic evidence comes principally from three early modern traditions—Middle Russian, Polish, and Ruthenian—with a smaller Old East Slavic chronicle layer. Place-names survive in chronicles, legal acts, boundary descriptions, maps and atlases, and later editions of manuscript material. The workflow combines candidate extraction, scholarly transliteration, separation of attested historical forms from modern translations, geographical filtering, duplicate detection, and comparison with an existing historical-toponymic database. The current working table contains 538 attestations and preserves uncertain identifications, competing normalizations, and editorial decisions.

  A preliminary normalized-Levenshtein analysis asks whether orthographic affinity between Slavic forms and German or modern local comparison forms varies geographically and by source tradition. Aggregated by identified place, Slavic forms are significantly closer to German comparison forms in Estonia (paired p=.003) and the Daugava corridor (p=.028), while northern Latvia shows no comparable asymmetry. The balance between German and local affinity also differs significantly among Middle Russian, Polish, and Ruthenian groups (Kruskal–Wallis p=.004), with Polish forms showing the strongest German affinity. The smaller Old East Slavic layer is treated separately.

  The paper examines LLM failure modes including hallucinated identifications, over-inclusion, confusion between ethnonyms and toponyms, and false equivalence between historical and modern forms. The LLM serves as an interface for querying a fragmented multilingual archive under explicit linguistic control.

• Sarah Bowen Savant (Aga Khan University)

  Work References across the OpenITI

  Pre-Recorded Talk In-Person

  Abstract

  This paper discusses an in-progress project to create a list of works cited in Arabic books in the period 700-1800. The goal is to create a list for every book in the OpenITI corpus (8,810 Arabic books, exceeding 1 billion word-tokens) detailing citations, including of titled books and more ephemeral texts (such as notes). Such compiled lists will function as new metadata to accompany the books that survive today in the OpenITI corpus, and will also contain further information per work cited, including authorship attribution, where possible; frequency of citation in the OpenITI book; locations within the OpenITI book of the work citations; and judgments about the certitude of identifications. These lists can be used to address crucial questions about the Arabic tradition as a whole, such as:

  1. Authorial practices. For example, which works, and which types of works, do book authors cite most frequently? For which authors do we have the most citations – and do they cite differently in different works that they wrote?
  2. Survival. The book citations can be compared to titles in the OpenITI corpus, as well as to historical and modern book lists and catalogues. To what extent is the OpenITI corpus itself representative of the works its authors cited?
  3. Lost texts. There are many texts embedded in later texts, for which we have no surviving independent witness. The titles and authorial attributions can assist scholars now working on retrieval of passages in their proximity.

  The project will be iterative — producing, reproducing and improving the lists over time. All items on a list should be considered candidates, requiring subsequent scholarly judgment. Datasets will be released with the OpenITI corpus and can be ingested into the KITAB/OpenITI web application (kitab-project.org/explore) and other applications.

  The method is a pipeline that teaches a model to recognise work references, treating detection — does this span refer to a specific written work? — separately from identification of which work it is, and evaluating the two separately. The pipeline will be discussed in the presentation, and likewise, the contribution that conversations with Claude made to its development.

• Colin Brisson (École Pratique des Hautes Études (EPHE))

  The CHAT models and the Numerica Sinologica work on Dunhuang material

  Pre-Recorded Talk Online

• Amba Kulkarni (IIT Hyderabad)

  Title to be announced

  Pre-Recorded Talk Online

• Xuelong Li, with Zheng Liu, Tieshan Zhang & Yu Weng (Minzu University of China)

  Reassembling Dunhuang: Reading Old World Written Cultures at LLM Scale

  Pre-Recorded Talk Online

  Abstract

  The Dunhuang manuscripts are among the richest sources for the written cultures of medieval Central Asia and the Silk Road, yet more than ninety percent survive only as fragments scattered across collections worldwide. For a century, rejoining them has relied on the chance encounters of scholarly memory. We turn reassembly into a reproducible computational process: it first perceives what survives on each fragment, then synthesises the pieces into whole pages, with a large language model proposing layouts and scholars making the final decision. We first build a perception layer to make fragments machine-readable. Boundary-geometry matching identifies sibling fragments; patch-level handwriting recognition groups leaves by scribal hand; a codebook of 512 learnable visual primitives captures fine-grained style; and glyph-augmentation networks restore damaged characters into readable form. Where material is lost, a diffusion-based simulator, Fate Twin, generates plausible degradation paths, so each reassembly decision rests on simulated evidence rather than intuition. From these fragment-level signals, SRP performs global reassembly. It fuses fragment images, edge maps and OCR text to predict adjacency and relative direction, then a large language model reasons under placement constraints to reconstruct whole-page layouts. Reassembly is thus lifted from local pairwise matching to constrained whole-document inference. Every proposed placement is then scrutinised by domain experts, who make the final determination. Our methods extend beyond Chinese manuscripts to the endangered Khotanese script, for which we have assembled a dataset of 256 character classes and 201,452 images through self-supervised contrastive learning and iterative clustering. This human-machine collaborative approach offers a reproducible and generalisable path toward the digital reassembly of scattered manuscripts worldwide.

• David Owen (Harvard University)

  The Saharan Archive as Stress Test: Confabulation and Paleographic Possibility in a Neglected Manuscript Tradition

  Pre-Recorded Talk Online

  Abstract

  The Saharan manuscript tradition inverts misguided intuitions about "low-resource" regions of intellectual production. In fact, the Sahara is a region of extraordinary manuscript wealth and scholarly production, with thousands of volumes across family libraries and a nomadic civilization rooted in mobile knowledge transmission. Notwithstanding, the Saharan archive remains minimally catalogued, scarcely digitized, virtually unattested in LLM training corpora. This poverty of learning is the machine's, not the archive's. Drawing on in situ research on Saharan intellectual history, this paper reports two lines of inquiry conducted with frontier models, set against an exemplary archive of digitized microfilms at the University of Illinois Urbana-Champaign.

  I begin with a stress test. Trained overwhelmingly on printed and born-digital text, models probed on reception history, scholarly networks, and bibliography in this tradition fail in a characteristic way: fluency inversely tracks reliability. They produce inauthentic if mimetic Islamicate prose, plausible-enough transmission chains, and confected dialectic precisely where training data is thinnest. In a field of plausible-sounding lineages and attributions, deadly nonsense can escape notice. The philologist's inherited disciplines of source criticism and transmission-evaluation turn out to be the working method for using these systems at all, after all.

  Moreover, the Stewart microforms of Mauritanian mss at Urbana-Champaign, now digitized and with (occasionally) attributed hands, make a paleographic pilot testable. Can vision-capable models, taught explicit diagnostic criteria, triage manuscripts by regional script type (Andalusī, Maghribī, ṣaḥrāwī/shinqīṭī)? Harder still, can they sort unattributed leaves by scribal hand better than chance, at measurable levels of confidence, against adversarial cases like teacher-student stylistic continuity? What becomes findable matters: women's copying and annotation, legal-network geographies, visual graphs of modal logic applied to theology. I present this as experiment design and early probing, not results, offered by a scholar still learning how to put models to work beyond the chat window, and arguing that neglected traditions are the true test of whether a pre-print AI ecosystem serves the whole pre-print world or only its well-digitized provinces.

• Victoria Fendel (University of Oxford)

  Universality and diversity inter- and intra-lingually: Adapting the PARSEME 2.0 guidelines for Multi-Word Expressions to corpus languages (Greek, Latin)

  Pre-Recorded Talk In-Person

  Abstract

  How do you apply universal, categorical, and computationally inspired annotation guidelines to language varieties that are historical, fragmented, and abound with variation? This is the question we, the PARSEME Ancient Greek team, have been faced with for years. In a nutshell, we use an existing Universal Dependencies treebank and make manual adjustments where necessary for the task at hand. We then enhance this treebank by means of manual annotation based on the PARSEME 2.0 universal annotation guidelines for multi-word expressions (MWEs). MWEs are expressions made up of multiple words, such as in front of or to make a suggestion. For PARSEME, words are orthographically defined; linguistically, the question is more complicated (see e.g. Taylor 2014; Dixon & Aikhenvald 2021; Haspelmath 2023). The PARSEME 2.0 guidelines are universal, in that they provide comparative concepts which can be applied to a range of language varieties (cf. Haspelmath 2010). Decision-trees based on the hypothesis that semantic idiomaticity goes hand in hand with morpho-syntactic inflexibility ensure replicability. Thus, diversity can be measured inter-lingually, but what about intra-lingual diversity? This is where even high-resource corpus varieties like classical Greek (5th c. BCE) and Latin (1st c. BCE to 1st c. CE) have challenged us (e.g. Fendel 2025). From sampling, through finding the so-called neutral form of each MWE token, to assessing the (in)flexibility of this neutral form during annotation by means of corpus queries, we have had to adapt (see Fendel, Squeri & Platanou 2026). As an illustrative example, I will draw on the Shared Task 2025 GRC data (classical literary Attic Greek courtroom oratory) (cf. Savary et al. 2026) and the UniDive WG1 Sub-task 1.6 Latin data (classical literary Latin historiography). Both datasets show a significant skew in the MWE tokens towards verbal MWEs rather than nominal, adverbial, adjectival, or functional MWEs. Both samples also have faced us with significant issues when distinguishing between categories of MWEs and between MWEs and fully compositional, flexible structures. The skew towards verbal MWEs can be explained diachronically in the languages’ history. The difficulties in distinguishing between structures can be explained not only synchronically in each language but also based on the annotation process. Finally, I will raise open questions that relate to future work we are planning.

Machine-Scale History

LLMs are opening up the reconstruction of lives, networks and societies at dramatically new scales, bringing closer the visions of macro-historians such as Peter Turchin. However, their access to the pre-print past is overwhelmingly filtered through later editions, translations and historical interpretations, as is material and environmental evidence. Machine-Scale History asks not only what can be inferred at scale and how such inferences are tested, but also how the field might be transformed by mining the world's untapped primary evidence about the world before print.

• Peter Turchin (Complexity Science Hub Vienna & University of Oxford)

  Title to be announced

  Live Keynote Online

• David Zbíral, with Zoltan Brys, Robert L. J. Shaw & Gideon Kotzé (Masaryk University)

  Recovering Dispersed Dissent: LLM-Assisted Extraction of Religious Authority Contestation from Medieval Inquisition Archives (1243–1522)

  Pre-Recorded Talk In-Person

  Abstract

  The contestation of religious authorities – direct verbal challenges to ecclesiastical legitimacy, clerical conduct, and sacramental power – is dispersed thinly across medieval inquisition records and overshadowed by other topics. Scholarship recognizes its presence in dissident milieus but has never quantified its frequency or examined the social and temporal factors shaping its expression. This dispersal across thousands of documents in dozens of registers made systematic analysis technically unreachable for unassisted scholarship.

  We deployed Anthropic's Claude Sonnet 4 to classify and extract relevant passages from 4,357 testimonies spanning 20 inquisition registers (South-Western France, North-Central Italy, Switzerland, England; 1243–1522). LLM classification was validated against independent human coding on random samples of 200 testimonies per variable, achieving 85–99% agreement. We then examined whether four factors correlate with contestation frequency: religious culture, urban versus rural setting, temporal period, and gender.

  Results reveal distinct patterns: reformistic dissidents (Waldensians, Beguins, Lollards) articulated authority contestation much more frequently than separatistic groups (Cathars, Apostles, Guglielmites). Urban-dominated registers paradoxically contain fewer such contestations. Temporal analysis demonstrates genuine growth in authority contestation toward the Reformation, affirming expanding lay engagement with ecclesiastical legitimacy. Gender showed no significant effect.

  This study illustrates how LLM-assisted extraction, when grounded in rigorous prompt design and human validation, transforms what was previously dispersed beyond scholarly reach into a dataset amenable to quantitative cultural-historical analysis.

• Eltjo Buringh, with Auke Rijpma (Utrecht University)

  The Prevalence of Medieval Capital Goods from Manuscript Illustrations, 800–1600

  Pre-Recorded Talk In-Person

  Abstract

  A database of some 75,000 picture descriptions from nearly 11,000 European manuscripts (800–1600), used to estimate the prevalence of medieval capital goods. Deliberately non-LLM, manual-extraction work — the baseline the machine-assisted programmes must beat.

• Roger Martínez-Dávila (University of Colorado & Plus Ultra Collective)

  Across the Archive and the Atlantic: Reconstructing Jewish and Converso Kinship Networks with LLMs

  Pre-Recorded Talk Online

  Abstract

  Drawing on ongoing research with the St. Augustine Jewish Historical Society, this paper explores how large language models can assist in reconstructing Jewish and converso kinship networks connecting Iberia, Spanish Florida, Mexico City, and the Caribbean during the sixteenth and early seventeenth centuries.

  Military musters, inquisitorial proceedings, wills, and genealogical inquiries provide the basis for investigating relationships sustained through marriage, patronage, and officeholding. LLM-assisted transcription, translation, and comparison help identify possible connections across dispersed records, which require verification against original manuscripts. The inquiry distinguishes documented kinship from plausible association, and Jewish ancestry from religious practice or accusation.

  Collaboration between historians and volunteer researchers grounds these methods in shared questions of belonging and historical memory. The paper considers how AI can support historical inquiry while preserving uncertainty and the complexity of lives shaped by migration, conversion, and colonization.

• Stephen Pink (Plus Ultra Collective)

  Title to be announced

  Pre-Recorded Talk In-Person

  Abstract

  The convenor's own talk: QUINCUNX as registered falsification for historical inference — pre-registration, inference/evidence firewalls, kill criteria, synthetic written worlds as calibration (public article: arsinq.com/articles/quincunx/).

• Radek Stefanski (University of St Andrews)

  Title to be announced

  Pre-Recorded Talk In-Person

• Remy Levin, with Daniela Vidart (University of Connecticut)

  The Yeoman's Portfolio: Measuring Historical Risk Preferences Using Crop Choice

  Pre-Recorded Talk In-Person

  Abstract

  We design a method for measuring the risk preferences of agents in the deep past. The method combines a structural model of crop choice as a portfolio allocation with machine-learning prediction of expected crop returns, using historic agronomic and climate data. We estimate county-level risk preferences for the United States and farmer-level preferences in Kansas from 1889 to 1929. More risk averse farmers leveraged less, were less likely to purchase novel WWI Liberty Bonds, and were more likely to participate in local risk-sharing institutions. We show that higher risk aversion predicts slower tractor adoption and farm mechanization during the 1920s.

• Xuelong Li (Minzu University of China), with Zimeng Qu (Renmin University of China)

  A Pre-Print Information System in Qing Governance: Computational History of the Yongzheng Vermilion-Rescript Memorials

  Pre-Recorded Talk Online

  Abstract

  The palace-memorial (zouzhe) system reached its fullest articulation under the Yongzheng emperor (1723–1735): memorials bearing vermilion rescripts (zhupi) circulated between the throne and provincial officials, forming a vast administrative record. Historians have relied on close reading of selected exemplars. We ask what changes when the corpus becomes computable. In a system whose bottleneck was imperial attention itself, these documents record how a state managed overflow: prioritisation, verification, and the reproduction of administrative knowledge. We present a computational-history framework that fuses SikuBERT, a BERT model pre-trained on classical and historical Chinese, with the three-level coding of grounded theory. SikuBERT supplies dense semantic representations of memorial texts; open, axial and selective coding organises these into historically meaningful categories, from genre and subject to the tone and urgency of imperial feedback. The two components run iteratively, not sequentially: codings are checked against model outputs and re-derived from the representations, keeping distant reading accountable to close reading. The framework makes systematic analysis of massive historical collections tractable, and keeps interpretation firmly in the historians' hands, replacing exemplar-driven narrative with corpus-scale evidence. Applied to the Yongzheng corpus, the framework traces how information was generated, fed back and reproduced under the memorial system, offering new empirical evidence for information behaviour in Qing state governance. The framework is designed to extend across reigns and document types; we outline how large language models will enter the pipeline next, through assisted coding, corpus-wide hypothesis generation, and dialogue with the archive. The memorial system thus offers an instructive precedent for the computational study of pre-print cultures: a state-run information regime whose “language model” was the emperor himself.

• Benjamin James Riddle (Independent researcher)

  The Invisible House: Agentic Prosopography and the Recovery of Dispersed Medieval Kinship

  Pre-Recorded Talk In-Person

  Abstract

  Medieval genealogy is exceptionally vulnerable to the structure of its archive. Surviving documents privilege inheritance, title, property and institutional continuity, while cadets, cousins, wives, clerics, household associates, witnesses, patrons and other lateral actors frequently disappear from conventional narratives. Later pedigrees can therefore impose linearity upon relationships that may once have been experienced as far more distributed communities of kinship, obligation, patronage and memory.

  This paper asks whether generative AI can make a longstanding but previously impractical form of historical inquiry more achievable: reconstructing relationships dispersed across people, places, archives and documentary traditions without collapsing possibility into proof. Developed through The Invisible House, a study of Ridel/Rudel networks across eleventh- and twelfth-century western France, southern Italy and England, the method treats the aristocratic family not simply as a succession of inheritors but as a distributed social system.

  An LLM-assisted research environment interrogates charters, cartularies, editions, prosopographical databases, spatial relationships and scholarship iteratively and at scale, allowing weak connections between otherwise separated actors and archives to become visible. Rather than treating nominal similarity as evidence of identity, the method distinguishes source assertions, relational inferences and identity hypotheses, preserving the epistemic status of each claim. Generated hypotheses must survive human source inspection and attempts at falsification before entering the historical argument.

  The paper argues that generative AI's most productive role in medieval prosopography is therefore not automated genealogy, but an interrogative layer between archive and scholar. By recovering overlooked actors and relationships, it may also expose the limits of later pedigree traditions themselves: beneath the linear genealogies through which medieval families were subsequently remembered lie older, dispersed networks whose surviving traces suggest that kinship, identity and family memory followed more complicated paths.

• Maxim Romanov (University of Hamburg)

  Title to be announced

  Pre-Recorded Talk Online

• Fabio Celli (Maggioli S.p.A.)

  Title to be announced

  Pre-Recorded Talk Online