Recent advances in large language models (LLMs) enable agentic systems trained with reinforcement learning (RL) over multi-turn interaction trajectories, but practical deployment is bottlenecked by rapidly growing textual histories that inflate token budgets and memory usage. We introduce AgentOCR, a framework that exploits the superior information density of visual tokens by representing the accumulated observation-action history as a compact rendered image. To make multi-turn rollouts scalable, AgentOCR proposes segment optical caching. By decomposing history into hashable segments and maintaining a visual cache, this mechanism eliminates redundant re-rendering. Beyond fixed rendering, AgentOCR introduces agentic self-compression, where the agent actively emits a compression rate and is trained with compression-aware reward to adaptively balance task success and token efficiency. We conduct extensive experiments on challenging agentic benchmarks, ALFWorld and search-based QA. Remarkably, results demonstrate that AgentOCR preserves over 95\% of text-based agent performance while substantially reducing token consumption (>50\%), yielding consistent token and memory efficiency. Our further analysis validates a 20x rendering speedup from segment optical caching and the effective strategic balancing of self-compression.
Wikipedia's founders could not have dreamed they were creating the most important laboratory for social scientific and computing research in history but that is exactly what happened. Hill and Shaw take account of Wikipedia's enormous effect on academic scholarship
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.
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.
Abinash Kumar Shaw, Raghunath Ghara, Paz Beniamini
et al.
We propose different estimators to probe the intergalactic medium (IGM) during epoch of reionization (EoR) using the dispersion measure (${\rm DM}$) of the fast radio bursts. We consider three different reionization histories, which we can distinguish with a total of $\lesssim 1000\,{\rm DM}$ measurements during EoR if their redshifts are known. We note that the redshift derivatives of ${\rm DM}$ are also directly sensitive to the reionization history. The major point of this work is to explore the variance in the ${\rm DM}$ measurements and the information encoded in them. We find that the all-sky average $\overline{\rm DM}(z)$ gets biased from the line-of-sight (LoS) fluctuations in the ${\rm DM}$ measurements introduced by the ionization of IGM during EoR. We find that the ratio $σ_{\rm DM}/\overline{\rm DM}$ depends directly on the ionization bubble sizes as well as the reionization history. On the other hand, we also find that angular variance (coined as $\textit{structure function}$) of ${\rm DM}$ encodes the information about the duration of reionization and the typical bubble sizes as well. We establish the usefulness of variances in ${\rm DM}$ using toy models of reionization and later verify it with the realistic reionization simulations.
Lekshmi Thulasidharan, Elena D'Onghia, Robert Benjamin
et al.
The prevailing model of galaxy formation proposes that galaxies like the Milky Way are built through a series of mergers with smaller galaxies over time. However, the exact details of the Milky Way's assembly history remain uncertain. In this study, we show that the Milky Way's merger history is uniquely encoded in the vertical thickness of its stellar disk. By leveraging age estimates from the value-added LAMOST DR8 catalog and the StarHorse ages from SDSS-IV DR12 data, we investigate the relationship between disk thickness and stellar ages in the Milky Way using a sample comprising Red Giants (RG), Red Clump Giants (RCG), and metal-poor stars (MPS). Guided by the IllustrisTNG50 simulations, we show that an increase in the dispersion of the vertical displacement of stars in the disk traces its merger history. This analysis reveals the epoch of a major merger event that assembled the Milky Way approximately 11.13 billion years ago, as indicated by the abrupt increase in disk thickness among stars of that age, likely corresponding to the Gaia-Sausage Enceladus (GSE) event. The data do not exclude an earlier major merger, which may have occurred about 1.3 billion years after the Big Bang. Furthermore, the analysis suggests that the geometric thick disk of the Milky Way was formed around 11.13 billion years ago, followed by a transition period of approximately 2.6 billion years leading to the formation of the geometric thin disk, illustrating the galaxy's structural evolution. Additionally, we identified three more recent events -- 5.20 billion, 2.02 billion, and 0.22 billion years ago -- potentially linked to multiple passages of the Sagittarius dwarf galaxy. Our study not only elucidates the complex mass assembly history of the Milky Way and highlights its past interactions but also introduces a refined method for examining the merger histories of external galaxies.
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.
As the final stage of the multi-stage recommender system (MRS), reranking directly affects users' experience and satisfaction, thus playing a critical role in MRS. Despite the improvement achieved in the existing work, three issues are yet to be solved. First, users' historical behaviors contain rich preference information, such as users' long and short-term interests, but are not fully exploited in reranking. Previous work typically treats items in history equally important, neglecting the dynamic interaction between the history and candidate items. Second, existing reranking models focus on learning interactions at the item level while ignoring the fine-grained feature-level interactions. Lastly, estimating the reranking score on the ordered initial list before reranking may lead to the early scoring problem, thereby yielding suboptimal reranking performance. To address the above issues, we propose a framework named Multi-level Interaction Reranking (MIR). MIR combines low-level cross-item interaction and high-level set-to-list interaction, where we view the candidate items to be reranked as a set and the users' behavior history in chronological order as a list. We design a novel SLAttention structure for modeling the set-to-list interactions with personalized long-short term interests. Moreover, feature-level interactions are incorporated to capture the fine-grained influence among items. We design MIR in such a way that any permutation of the input items would not change the output ranking, and we theoretically prove it. Extensive experiments on three public and proprietary datasets show that MIR significantly outperforms the state-of-the-art models using various ranking and utility metrics.
We consider the model of history-deterministic one-counter nets (OCNs). History-determinism is a property of transition systems that allows for a limited kind of non-determinism which can be resolved 'on-the-fly'. Token games, which have been used to characterise history-determinism over various models, also characterise history-determinism over OCNs. By reducing 1-token games to simulation games, we are able to show that checking for history-determinism of OCNs is decidable. Moreover, we prove that this problem is PSPACE-complete for a unary encoding of transitions, and EXPSPACE-complete for a binary encoding. We then study the language properties of history-deterministic OCNs. We show that the resolvers of non-determinism for history-deterministic OCNs are eventually periodic. As a consequence, for a given history-deterministic OCN, we construct a language equivalent deterministic one-counter automaton. We also show the decidability of comparing languages of history-deterministic OCNs, such as language inclusion and language universality.
Dhiraj Kumar Hazra, Daniela Paoletti, Fabio Finelli
et al.
Cosmic Microwave Background temperature and polarization anisotropies from Planck have estimated a lower value of the optical depth to reionization ($τ$) compared to WMAP. A significant period in the reionization history would then fall within $6<z< 10$, where detection of galaxies with Hubble Frontier Fields program and independent estimation of neutral hydrogen in the inter galactic medium by Lyman-$α$ observations are also available. This overlap allows an analysis of cosmic reionization which utilizes a direct combination of CMB and these astrophysical measurements and potentially breaks degeneracies in parameters describing the physics of reionization. For the first time we reconstruct reionization histories by assuming photo-ionization and recombination rates to be free-form and by allowing underlying cosmological parameters to vary with CMB (temperature and polarization anisotropies and lensing) data from Planck 2018 release and a compilation of astrophysical data. We find an excellent agreement between the low-$\ell$ Planck 2018 HFI polarization likelihood and astrophysical data in determining the integrated optical depth. By combining both data, we report for a minimal reconstruction $τ=0.051^{+0.001+0.002}_{-0.0012-0.002}$ at 68\% and 95\% CL, which, for the errors in the current astrophysical measurements quoted in the literature, is nearly twice better than the projected cosmic variance limited CMB measurements. For the duration of reionization, redshift interval between 10\% and complete ionization, we get $2.9^{+0.12+0.29}_{-0.16-0.26}$ at 68\% and 95\% CL, which improves significantly on the corresponding result obtained by using Planck 2015 data. By a Bayesian analysis of the combined results we do not find evidence beyond monotonic reionization histories, therefore multi-phase reionization scenario is disfavored compared to minimal alternatives.
We develop a formalism to calculate the merger rate density of primordial black hole binaries with a general mass function, by taking into account the merger history of primordial black holes. We apply the formalism to three specific mass functions, monochromatic, power-law and log-normal cases. In the former case, the merger rate density is dominated by the single-merger events, while in the latter two cases, the contribution of the multiple-merger events on the merger rate density can not be ignored. The effects of the merger history on the merger rate density depend on the mass function.
According to what has become a standard history of quantum mechanics, in 1932 von Neumann persuaded the physics community that hidden variables are impossible as a matter of principle, after which leading proponents of the Copenhagen interpretation put the situation to good use by arguing that the completeness of quantum mechanics was undeniable. This state of affairs lasted, so the story continues, until Bell in 1966 exposed von Neumann's proof as obviously wrong. The realization that von Neumann's proof was fallacious then rehabilitated hidden variables and made serious foundational research possible again. It is often added in recent accounts that von Neumann's error had been spotted almost immediately by Grete Hermann, but that her discovery was of no effect due to the dominant Copenhagen Zeitgeist. We shall attempt to tell a story that is more historically accurate and less ideologically charged. Most importantly, von Neumann never claimed to have shown the impossibility of hidden variables tout court, but argued that hidden-variable theories must possess a structure that deviates fundamentally from that of quantum mechanics. Both Hermann and Bell appear to have missed this point, moreover, both raised unjustified technical objections to the proof. Von Neumann's argument was basically that hidden-variables schemes must violate the "quantum principle" that physical quantities are to be represented by operators in a Hilbert space. As a consequence, hidden-variables schemes, though possible in principle, necessarily exhibit a certain kind of contextuality.
We investigate the formation history of the stellar disk component in the Milky Way (MW) based on our new chemical evolution model. Our model considers several fundamental baryonic processes, including gas infall, re-accretion of outflowing gas, and radial migration of disk stars. Each of these baryonic processes in the disk evolution is characterized by model parameters, which are determined by fitting to various observational data of the stellar disk in the MW, including the radial dependence of the metallicity distribution function (MDF) of the disk stars, which has recently been derived in the APOGEE survey. We succeeded to obtain the best set of model parameters, which well reproduces the observed radial dependences of the mean, standard deviation, skewness, and kurtosis of the MDFs for the disk stars. We analyze the basic properties of our model results in detail to get new insights into the important baryonic processes in the formation history of the MW. One of the remarkable findings is that outflowing gas, containing much heavy elements, preferentially re-accretes onto the outer disk parts, and this recycling process of metal-enriched gas is a key ingredient to reproduce the observed narrower MDFs at larger radii. Moreover, important implications for the radial dependence of gas infall and the influence of radial migration on the MDFs are also inferred from our model calculation. Thus, the MDF of disk stars is a useful clue for studying the formation history of the MW.
The 60th birthday of Johann Rafelski was celebrated during the Strangeness in Quark Matter 2011 in Krakow. Johann was born in Krakow and he initiated the series of the SQM conferences. This report, which briefly presents my personal view on a history of multi-particle production in high energy collisions, is dedicated to Johann.
We carefully analyze how the abundance of Nitrogen over Oxygen evolves when dependent on metallicity stellar yields with a primary component of N proceeding from AGBs stars are used. We show the results obtained with a chemical evolution models grid, calculated with variable star formation efficiencies, which produce different star formation histories. Finally we see how the N/O abundance is related on the evolutionary history.
There will be a review of the history of polarized proton beams, and a discussion of the unexpected and still unexplained large transverse spin effects found in several high energy proton-proton spin experiments at the ZGS, AGS, Fermilab and RHIC. Next there will be a discussion of possible future experiments on the violent collisions elastic collisions of polarized protons at the 70 GeV U-70 accelerator at IHEP-Protvino in Russia and the new high intensity 50 GeV J-PARC at Tokai in Japan.
In this brief article I review the history of astronomical photometry, touching on observations made by the ancient Chinese, Hipparchus and Ptolemy, the development of the concept (and definition) of magnitude, the endeavors of Argelander and Zoellner, work at Harvard at the end of the 19th century, and the development of photography, photomultipliers, and CCD's and their application to astronomy.