Hasil untuk "History"

D. Chakrabarty

L. W. Parr

Serin Kim, Sangam Lee, Dongha Lee

Large language models have advanced web agents, yet current agents lack personalization capabilities. Since users rarely specify every detail of their intent, practical web agents must be able to interpret ambiguous queries by inferring user preferences and contexts. To address this challenge, we present Persona2Web, the first benchmark for evaluating personalized web agents on the real open web, built upon the clarify-to-personalize principle, which requires agents to resolve ambiguity based on user history rather than relying on explicit instructions. Persona2Web consists of: (1) user histories that reveal preferences implicitly over long time spans, (2) ambiguous queries that require agents to infer implicit user preferences, and (3) a reasoning-aware evaluation framework that enables fine-grained assessment of personalization. We conduct extensive experiments across various agent architectures, backbone models, history access schemes, and queries with varying ambiguity levels, revealing key challenges in personalized web agent behavior. For reproducibility, our codes and datasets are publicly available at https://anonymous.4open.science/r/Persona2Web-73E8.

KaiWen Wei, Kejun He, Xiaomian Kang et al.

Generative recommendation, which directly generates item identifiers, has emerged as a promising paradigm for recommendation systems. However, its potential is fundamentally constrained by the reliance on purely autoregressive training. This approach focuses solely on predicting the next item while ignoring the rich internal structure of a user's interaction history, thus failing to grasp the underlying intent. To address this limitation, we propose Masked History Learning (MHL), a novel training framework that shifts the objective from simple next-step prediction to deep comprehension of history. MHL augments the standard autoregressive objective with an auxiliary task of reconstructing masked historical items, compelling the model to understand ``why'' an item path is formed from the user's past behaviors, rather than just ``what'' item comes next. We introduce two key contributions to enhance this framework: (1) an entropy-guided masking policy that intelligently targets the most informative historical items for reconstruction, and (2) a curriculum learning scheduler that progressively transitions from history reconstruction to future prediction. Experiments on three public datasets show that our method significantly outperforms state-of-the-art generative models, highlighting that a comprehensive understanding of the past is crucial for accurately predicting a user's future path. The code will be released to the public.

Jakub Fusiak, Andreas Wolkenstein, Verena S. Hoffmann

BackgroundPatient preferences are a critical component of shared decision-making (SDM), particularly when choosing between treatment options with differing risks and outcomes. Many methods exist to elicit these preferences, but their complexity, usability, and acceptance vary.ObjectiveWe aim to gain insight into the acceptance, effort and preferences of participants regarding five different methods of preference assessment. Additionally, we investigate the influence of health status, experiences within the health system and of demographic factors on the results.MethodsWe conducted a cross-sectional online survey including five preference elicitation Methods: best-worst scaling, direct weighting, PAPRIKA (Potentially All Pairwise Rankings of all Possible Alternatives), time trade-off, and standard gamble. The questionnaire was distributed via academic and patient advocacy mailing lists, reaching both healthy individuals and those with acute or chronic illnesses. Participants rated each method using six standardized statements on a 5-point Likert scale. Additional items assessed general acceptance of algorithm-assisted preference assessments and the clarity of the questionnaire.ResultsOf 258 initiated questionnaires, 123 (48%) were completed and included in the analysis. Participants were diverse in age, gender, and health status, but predominantly highly educated and digitally literate. Across all measures, the PAPRIKA method received the highest ratings for clarity, usability, and perceived ability to express preferences. Simpler methods (best-worst scaling, direct weighting) were rated as less useful for capturing nuanced preferences, while abstract utility-based methods (standard gamble, time trade-off) were seen as cognitively demanding. Subgroup analyses showed minimal variation across demographic groups. Most participants (82%) could imagine using at least one of the presented methods in real clinical settings, but also emphasized the importance of physician involvement in interpreting results.ConclusionThe interactive PAPRIKA method best balanced cognitive demand and expressiveness and was preferred by most participants. Structured methods for preference elicitation may enhance SDM when integrated into clinical workflows and supported by healthcare professionals. Further research is needed to evaluate their use in real-world decisions and among more diverse patient populations.

P. Wright

Christoph Draxler, Henk van den Heuvel, Arjan van Hessen et al.

Oral history is about oral sources of witnesses and commentors on historical events. Speech technology is an important instrument to process such recordings in order to obtain transcription and further enhancements to structure the oral account In this contribution we address the transcription portal and the webservices associated with speech processing at BAS, speech solutions developed at LINDAT, how to do it yourself with Whisper, remaining challenges, and future developments.

VanJessica Gladney, Breanna Moore, Kathleen Brown

In 2006 and 2016, the University of Pennsylvania denied any ties to slavery. In 2017, a group of undergraduate researchers, led by Professor Kathleen Brown, investigated this claim. Initial research, focused on 18th century faculty and trustees who owned slaves, revealed deep connections between the university's history and the institution of slavery. These findings, and discussions amongst the researchers shaped the Penn and Slavery Project's goal of redefining complicity beyond ownership. Breanna Moore's contributions in PSP's second semester expanded the project's focus to include generational wealth gaps. In 2018, VanJessica Gladney served as the PSP's Public History Fellow and spread the project outreach in the greater Philadelphia area. That year, the PSP team began to design an augmented reality app as a Digital Interruption and an attempt to display the truth about Penn's history on its campus. Unfortunately, PSP faced delays due to COVID 19. Despite setbacks, the project persisted, engaging with activists and the wider community to confront historical injustices and modern inequalities.

Володимир Ятченко

У статті піддаються розгляду процеси генези феномену колективного самоусвідомлення предків сучасних українців на етапі переходу від тотемного до антропоморфічного типів світогляду в текстах українського фольклору. При цьому основна увага переноситься на дослідження метафізичного виміру цього процесу. Підкреслено, що особливо рельєфно виділяються фази переходу від одного типу світогляду до іншого на прикладах порівняння текстів первісних міфів і народної казки. В українській народній казці, на відміну від первісного міфу, на просценіум виходять мотиви, моральна позиція персонажів. У казках людина перебуває в напружених рефлексіях про суперечності між загальноприйнятим і особистісним, а вже пізніші міфологічні тексти «заземлюють» просторові і часові горизонти діяльності героя, поміщуючи їх у контекст співвіднесення правового й морального, світського й релігійного. В горизонті генези форм колективної самосвідомості казка виявляє свою історично зумовлену амбівалентність: у ній фігурують герої давніх міфів, в сюжети казок вживлені лінії і структурна будова первісних міфів, окрушини тотемного світогляду. Однак приявність у казках моральних регулятивів, зародків свободи особистості виказує на прорив духовності людини за межі тотемізму й зоолатрії первісного міфу на простір антропоморфізму. На цьому новому етапі розвитку колективної свідомості істотною ознакою самосвідомості постає поєднання свободи і моральності, особливо рельєфно це проступає в сюжетах казок, у яких йдеться про стосунки між людиною і смертю.  

R. S. Shurguchinov

The study of the nomads of the South of Russia still arouses continued interest among Russian and foreign scholars, who study nomad, local historians, whose works reflect the history of nomads in Central Asia. However, we think that there are not enough works covering this topic and chronological framework, studying the history of the Turkmen nomadic people living within modern borders in the administrative-territorial composition of the Stavropol Territory, is somewhat more modest. Historically, Turkmens roamed the steppes of the Eastern Caspian region. In the middle of the 17th century. Several groups of Turkmen moved to the northwestern Caspian region, where they were included in the uluses of the Kalmyk Khanate. According to archival material, the Turkmens were first mentioned in 1653, when more than 1.5 thousand Turkmen families, under the threat of invasion by the Khiva khans, named the peninsula Mangyshlak and arrived in the Lower Volga region, where they joined the Kalmyks. Also, Turkmens continued to arrive from Mangyshlak throughout the 18th and early 19th centuries.The relevance of the study is explained by modern trends in actively turning to the historical past of both individual and entire nations, returning to the traditions and customs of their ancestors, primarily in the education of the younger generation. Despite all the developments in the historiography of the Turkmen people, economic issues have not been sufficiently studied and require more detailed study. In the framework of this work, the author has attempted to expand the scope of the study of the problem.

Cocić Nikola Z.

This study examines the relationship between self-efficacy , perceived organizational support, and job satisfaction, with pay satisfaction as a mediator. The sample is convenient and consists of 269 respondents (139 male and 136 female), aged 19 to 43 (M= 25.8, Sd= 4.3), working in an organizational or industrial environment. Out of the 269 respondents, 223 indicated their monthly income was average, 45 reported it as above average, and 1 stated it was below average. The instruments used for data collection were Minnesota Satisfaction Questionnaire (MSQ), General Self-Efficacy Scale (GSE), Perceived Organizational Support Scale, and respondents' pay satisfaction was assessed using a single question. A statistically significant correlation was found between all the variables included in the study (p < 0.01). Pay satisfaction had a mediating influence on the relationship between self-efficacy and job satisfaction, while perceived organizational support was a direct, statistically significant predictor of job satisfaction. The model proved to be sustainable. The study results are discussed in relation to relevant theoretical assumptions and their practical applications. The limitations of the study, such as sample adequacy, online administration, and the work environments, are stated. Recommendations are made for further research, including the exploration of additional variables to enhance the current model.

R. Nisbet

V. Goldberg, S. Stevenson

Seong Jin Kim, Tomotsugu Goto, Chih-Teng Ling et al.

With the advent of the James Webb Space Telescope (JWST), extra-galactic source count studies were conducted down to sub-microJy in the mid-infrared (MIR), which is several tens of times fainter than what the previous-generation infrared (IR) telescopes achieved in the MIR. In this work, we aim to interpret the JWST source counts and constrain cosmic star-formation history (CSFH) and black hole accretion history (BHAH). We employ the backward evolution of local luminosity functions (LLFs) of galaxies to reproduce the observed source counts from sub-microJy to a few tens of mJy in the MIR bands of the JWST. The shapes of the LLFs at the MIR bands are determined using the model templates of the spectral energy distributions (SEDs) for five representative galaxy types (star-forming galaxies, starbursts, composite, AGN type 2 and 1). By simultaneously fitting our model to all the source counts in the six MIR bands, along with the previous results, we determine the best-fit evolutions of MIR LFs for each of the five galaxy types, and subsequently estimate the CSFH and BHAH. Thanks to the JWST, our estimates are based on several tens of times fainter MIR sources, the existence of which was merely an extrapolation in previous studies.

Kai Wang, H. J. Mo, Yangyao Chen et al.

We propose a novel method to quantify the assembly histories of dark matter halos with the redshift evolution of the mass-weighted spatial variance of their progenitor halos, i.e. the protohalo size history. We find that the protohalo size history for each individual halo at z~0 can be described by a double power-law function. The amplitude of the fitting function strongly correlates to the central-to-total stellar mass ratios of descendant halos. The variation of the amplitude of the protohalo size history can induce a strong halo assembly bias effect for massive halos. This effect is detectable in observation using the central-to-total stellar mass ratio as a proxy of the protohalo size. The correlation to the descendant central-to-total stellar mass ratio and the halo assembly bias effect seen in the protohalo size are much stronger than that seen in the commonly adopted half-mass formation time derived from the mass accretion history. This indicates that the information loss caused by the compression of halo merger trees to mass accretion histories can be captured by the protohalo size history. Protohalo size thus provides a useful quantity to connect protoclusters across cosmic time and to link protoclusters with their descendant clusters in observations.

Víctor CUBILLO MEDINA

En este artículo se estudia la obra de Juan de Sobiñas, vecino de Medina del Campo, a través de la documentación conservada. Se detallan las obras contratadas con este bordador desde 1577 a 1593.

D. Carter, D. Carter

L. Partridge, P. Harvey

Andrew Iskauskas, Ian Vernon, Michael Goldstein et al.

Modelling complex real-world situations such as infectious diseases, geological phenomena, and biological processes can present a dilemma: the computer model (referred to as a simulator) needs to be complex enough to capture the dynamics of the system, but each increase in complexity increases the evaluation time of such a simulation, making it difficult to obtain an informative description of parameter choices that would be consistent with observed reality. While methods for identifying acceptable matches to real-world observations exist, for example optimisation or Markov chain Monte Carlo methods, they may result in non-robust inferences or may be infeasible for computationally intensive simulators. The techniques of emulation and history matching can make such determinations feasible, efficiently identifying regions of parameter space that produce acceptable matches to data while also providing valuable information about the simulator's structure, but the mathematical considerations required to perform emulation can present a barrier for makers and users of such simulators compared to other methods. The hmer package provides an accessible framework for using history matching and emulation on simulator data, leveraging the computational efficiency of the approach while enabling users to easily match to, visualise, and robustly predict from their complex simulators.