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Recent inverse rendering methods have greatly improved shape, material, and illumination reconstruction by utilizing polarization cues. However, existing methods only support dielectrics, ignoring conductors that are found everywhere in life. Since conductors and dielectrics have different reflection properties, using previous conductor methods will lead to obvious errors. In addition, conductors are glossy, which may cause strong specular reflection and is hard to reconstruct. To solve the above issues, we propose NeISF++, an inverse rendering pipeline that supports conductors and dielectrics. The key ingredient for our proposal is a general pBRDF that describes both conductors and dielectrics. As for the strong specular reflection problem, we propose a novel geometry initialization method using DoLP images. This physical cue is invariant to intensities and thus robust to strong specular reflections. Experimental results on our synthetic and real datasets show that our method surpasses the existing polarized inverse rendering methods for geometry and material decomposition as well as downstream tasks like relighting.

The VLT Survey Telescope Survey of Mass Assembly and Structural Hierarchy (VST-SMASH) aims to detect tidal features and remnants around very nearby galaxies, a unique and essential diagnostic of the hierarchical nature of galaxy formation. Leveraging optimal sky conditions at ESO's Paranal Observatory, combined with the VST's multi-band optical filters, VST-SMASH aims to be the definitive survey of stellar streams and tidal remnants in the Local Volume, targeting a low surface-brightness limit of $\mu \sim$ 30 mag arcsec$^{-2}$ in the g and r bands, and $\mu \sim$ 28 mag arcsec$^{-2}$ in the i band, in a volume-limited sample of local galaxies within 11 Mpc and the Euclid footprint., Comment: 4 pages, 2 figures, 1 table, published in the ESO Messenger 193

Since the COVID-19 pandemic, clinicians have seen a large and sustained influx in patient portal messages, significantly contributing to clinician burnout. To the best of our knowledge, there are no large-scale public patient portal messages corpora researchers can use to build tools to optimize clinician portal workflows. Informed by our ongoing work with a regional hospital, this study introduces an LLM-powered framework for configurable and realistic patient portal message generation. Our approach leverages few-shot grounded text generation, requiring only a small number of de-identified patient portal messages to help LLMs better match the true style and tone of real data. Clinical experts in our team deem this framework as HIPAA-friendly, unlike existing privacy-preserving approaches to synthetic text generation which cannot guarantee all sensitive attributes will be protected. Through extensive quantitative and human evaluation, we show that our framework produces data of higher quality than comparable generation methods as well as all related datasets. We believe this work provides a path forward for (i) the release of large-scale synthetic patient message datasets that are stylistically similar to ground-truth samples and (ii) HIPAA-friendly data generation which requires minimal human de-identification efforts., Comment: Findings paper presented at Machine Learning for Health (ML4H) symposium 2024, December 15-16, 2024, Vancouver, Canada, 8 pages

We present a search for long-lived particles (LLPs) produced from kaon decay that decay to two muons inside the ICARUS neutrino detector. This channel would be a signal of hidden sector models that can address outstanding issues in particle physics such as the strong CP problem and the microphysical origin of dark matter. The search is performed with data collected in the Neutrinos at the Main Injector (NuMI) beam at Fermilab corresponding to $2.41\times 10^{20}$ protons-on-target. No new physics signal is observed, and we set world-leading limits on heavy QCD axions, as well as for the Higgs portal scalar among dedicated searches. Limits are also presented in a model-independent way applicable to any new physics model predicting the process $K\to \pi+S(\to\mu\mu)$, for a long-lived particle S. This result is the first search for new physics performed with the ICARUS detector at Fermilab. It paves the way for the future program of long-lived particle searches at ICARUS.

Multi-label classification is a type of supervised machine learning that can simultaneously assign multiple labels to an instance. To solve this task, some methods divide the original problem into several sub-problems (local approach), others learn all labels at once (global approach), and others combine several classifiers (ensemble approach). Regardless of the approach used, exploring and learning label correlations is important to improve the classifier predictions. Ensemble of Classifier Chains (ECC) is a well-known multi-label method that considers label correlations and can achieve good overall performance on several multi-label datasets and evaluation measures. However, one of the challenges when working with ECC is the high dimensionality of the label space, which can impose limitations for fully-cascaded chains as the complexity increases regarding feature space expansion. To improve classifier chains, we propose a method to chain disjoint correlated label clusters obtained by applying a partition method in the label space. During the training phase, the ground truth labels of each cluster are used as new features for all of the following clusters. During the test phase, the predicted labels of clusters are used as new features for all the following clusters. Our proposal, called Label Cluster Chains for Multi-Label Classification (LCC-ML), uses multi-label Random Forests as base classifiers in each cluster, combining their predictions to obtain a final multi-label classification. Our proposal obtained better results compared to the original ECC. This shows that learning and chaining disjoint correlated label clusters can better explore and learn label correlations., Comment: The article was submitted prematurely, and after it was published on arXiv, we identified aspects that require attention, adjustments, and improvements. We are working to review and significantly improve the content. Therefore, we request its temporary withdrawal to avoid the dissemination of information that may be incomplete or incorrectly interpreted

The Clifford algebra of the endomorphisms of the exterior algebra of a countably dimensional vector space induces natural bosonic shadows, i.e. families of linear maps between the cohomologies of complex grassmannians. The main result of this paper is to provide a determinantal formula expressing generating functions of such endomorphisms unifying several classical special cases. For example the action over a point recovers the Jacobi-Trudy formula in the theory of symmetric functions or the Giambelli's one in classical Schubert calculus, whereas the action of degree preserving endomorphisms take into account the finite type version of the Date-Jimbo-Kashiwara-Miwa bosonic vertex operator representation of the Lie algebra $gl(\infty)$. The fermionic actions on (finite type) bosonic spaces is described in terms of the classical theory of symmetric functions. The main guiding principle is the fact that the exterior algebra is a (non irreducible) representation of the ring of symmetric functions, which is the way we use to spell the ``finite type'' Boson-Fermion correspondence., Comment: 25 pages, no figures

An analysis of the Ultra Long Period Cepheids (ULPs) properties could significantly contribute to understanding the Hubble constant tension, e.g. the current discrepancy between determinations based on local distance indicators and those relying on cosmic microwave background measurements. These highly luminous variables are observable beyond 100 Mpc, so if they were confirmed to behave as standard candles, they would allow us a direct measurement of cosmological distances without any secondary distance indicator, thus reducing potential systematic errors in the calibration of the cosmic distance scale. This paper presents an analysis of the largest known sample of 73 ULPs, including 15 objects in nearby galaxies, with new accurate and homogeneous photometry obtained by Gaia DR3, and a new object, in our Galaxy, identified as Long Period Variable in Gaia DR3, but recently reclassified as ULP. The obtained results suggest that, by improving photometric accuracy, the ULP Period-Wesenheit relation shows a smaller dispersion than that obtained in literature and is in better agreement with the Classical Cepheid (CC) one, supporting the hypothesis that ULPs are the extension of the CCs at higher period, mass and luminosity. However, to reach this aim, it is necessary to enrich the sample with high-quality data. The Rubin-LSST survey offers the possibility to achieve this thanks to its photometric characteristics and time extension. In particular, we will explore the capabilities of the Rubin-LSST survey to recover ULP theoretical light-curves by using a new tool called PulsationStarRecovery, built by our group for this type of analysis., Comment: Accepted, ApJS (Rubin Cadence Focus Issues), 17 pages, 12 figures

The influence of Active Galactic Nuclei (AGN) on star formation within their host galaxies remains a topic of intense debate. One of the primary challenges in quantifying the star formation rate (SFR) within AGN hosts arises from the prevalent assumption in most methodologies, which attribute gas excitation to young stars alone. However, this assumption does not consider the contribution of the AGN to the ionization of the gas in their environment. To address this issue, we evaluate the use of strong optical emission lines to obtain the SFR surface density ($\Sigma{{\rm SFR_{AGN}}}$) in regions predominantly ionized by an AGN, using a sample of 293 AGN hosts from the MaNGA survey, with SFR measurements available through stellar population fitting. We propose calibrations involving the H$\alpha$ and [O\,{\sc iii}]$\lambda$5007 emission lines, which can be used to determine $\Sigma{{\rm SFR_{AGN}}}$, resulting in values consistent with those estimated through stellar population fitting., Comment: Accepted for publication in MNRAS

Prior works formulate the extraction of event-specific arguments as a span extraction problem, where event arguments are explicit -- i.e. assumed to be contiguous spans of text in a document. In this study, we revisit this definition of Event Extraction (EE) by introducing two key argument types that cannot be modeled by existing EE frameworks. First, implicit arguments are event arguments which are not explicitly mentioned in the text, but can be inferred through context. Second, scattered arguments are event arguments that are composed of information scattered throughout the text. These two argument types are crucial to elicit the full breadth of information required for proper event modeling. To support the extraction of explicit, implicit, and scattered arguments, we develop a novel dataset, DiscourseEE, which includes 7,464 argument annotations from online health discourse. Notably, 51.2% of the arguments are implicit, and 17.4% are scattered, making DiscourseEE a unique corpus for complex event extraction. Additionally, we formulate argument extraction as a text generation problem to facilitate the extraction of complex argument types. We provide a comprehensive evaluation of state-of-the-art models and highlight critical open challenges in generative event extraction. Our data and codebase are available at https://omar-sharif03.github.io/DiscourseEE., Comment: Accepted in EMNLP-2024 (Main). 21 pages, 8 figures, and 11 tables

Modern biological research is increasingly data-intensive, leading to a growing demand for effective training in biological data science. In this article, we provide an overview of key resources and best practices available within the Bioconductor project - an open-source software community focused on omics data analysis. This guide serves as a valuable reference for both learners and educators in the field., Comment: 16 pages, 2 figures, 1 table, 1 supplemental table

We compute the real corrections to the impact factor for the production of a forward Higgs boson, retaining full top-mass dependence. We demonstrate that the rapidity divergence is the one predicted by the BFKL factorization and perform the explicit subtraction in the BFKL scheme. We show that the IR-structure of the impact factor is the expected one and that, in the infinite-top-mass approximation, the previously known result is recovered. We also verify that the impact factor vanishes when the transverse momenta of the $t$-channel Reggeon goes to zero, in agreement with its gauge-invariant definition, exploiting the $m_t \rightarrow \infty$ expansion up to the next-to-next-to-leading order., Comment: 29 pages, 6 figures

New, deep HST photometry allowed us to identify and study eight compact and bright (M_V< -5.8) star clusters in the outskirts of the star-forming isolated dwarf galaxy NGC5238 (M_*= 10^8 M_sun). Five of these clusters are new discoveries, and six appear projected onto, and/or aligned with the tidal tails recently discovered around this galaxy. The clusters are partially resolved into stars and their colour magnitude diagrams reveal a well developed red giant branch, implying ages older than 1-2~Gyr. Their integrated luminosity and structural parameters are typical of classical globular clusters and one of them has M_V=-10.56 +/- 0.07, as bright as Omega Cen, the brightest globular cluster of the Milky Way. Since the properties of this cluster are in the range spanned by those of nuclear star clusters we suggest that it may be the nuclear remnant of the disrupted satellite of NGC5238 that produced the observed tidal tails., Comment: Accepted for publication by A&A Letters. Latex, 10 pages, 6 figures, 5 appendices

We present novel predictions for rapidity and transverse-momentum distributions sensitive to the emission of a Higgs boson accompanied by a jet in proton collisions, calculated within the NLO fixed order in QCD and matched with the next-to leading energy-logarithmic accuracy. We also highlight first advancements in the extension of our analysis to the $Z$-boson case. We come out with the message that the improvement of fixed-order calculations on Higgs- and $Z$-boson plus jet distributions is a required step to reach the precision level of the description of observables relevant for Higgs and electroweak physics at current LHC energies and nominal FCC ones., Comment: 5 pages, 1 figure, proceedings of the 31st International Workshop on Deep Inelastic Scattering (DIS2024), 8-12 April 2024, Grenoble, France

Precision physics in the Higgs sector has been one of the main challenges of particle physics in the recent years. The pure fixed-order calculations entering the collinear factorization framework, which have been pushed up to next-cube-leading-order, are not able to describe the entire kinematic spectrum. In particular sectors, they have to be necessarily enhanced by all-order resummations. In the so-called semi-hard regime, large energy-type logarithms spoil the perturbative convergence of the series and must be resummed to all orders. This resummation is a core ingredient for a correct description of the inclusive hadroproduction of a forward Higgs boson in the limit of small Bjorken $x$, as well as for a precision study of inclusive forward emissions of a Higgs boson in association with a backward identified object. A complete resummation for these processes can be achieved at the at next-to-leading logarithmic accuracy thanks to the Balitsky-Fadin-Kuraev-Lipatov approach. In the present work we present and discuss a series of recent phenomenological results within a partial next-to-leading accuracy. They include the analysis of rapidity and azimuthal-angle differential rates for Higgs plus jet and Higgs plus charm reactions in forward and ultraforward directions of rapidity at the LHC., Comment: 5 pages, 1 figure, proceedings of the 31st International Workshop on Deep Inelastic Scattering (DIS2024), 8-12 April 2024, Grenoble, France

We present preliminary findings from the photometric survey "Yes, Magellanic Clouds Again" (YMCA, PI: V. Ripepi), covering 110 square degrees in the outer regions of the Magellanic Clouds (MCs), a pair of interacting galaxies and the most massive dwarf satellites of the Milky Way. %The survey achieves a notable photometric depth, allowing us to resolve faint, old stellar populations. Among the key results, we discovered four star clusters (SCs) within the Large Magellanic Cloud (LMC) exhibiting ages within the so-called "age gap", a period deemed so far devoid of SCs. Additionally, we unveiled an ancient stellar system associated with the LMC, featuring structural properties in between the globular clusters and the ultra-faint dwarf galaxies of the Local Group. These discoveries significantly contribute to our understanding of the MCs' evolution and their complex interaction history., Comment: 5 Pages, 1 figure, accepted for publication in "Il Nuovo Cimento - Colloquia and Communications in Physics."

This paper reports on a measurement of electron-ion recombination in liquid argon in the ICARUS liquid argon time projection chamber (LArTPC). A clear dependence of recombination on the angle of the ionizing particle track relative to the drift electric field is observed. An ellipsoid modified box (EMB) model of recombination describes the data across all measured angles. These measurements are used for the calorimetric energy scale calibration of the ICARUS TPC, which is also presented. The impact of the EMB model is studied on calorimetric particle identification, as well as muon and proton energy measurements. Accounting for the angular dependence in EMB recombination improves the accuracy and precision of these measurements.

The ICARUS liquid argon time projection chamber (LArTPC) neutrino detector has been taking physics data since 2022 as part of the Short-Baseline Neutrino (SBN) Program. This paper details the equalization of the response to charge in the ICARUS time projection chamber (TPC), as well as data-driven tuning of the simulation of ionization charge signals and electronics noise. The equalization procedure removes non-uniformities in the ICARUS TPC response to charge in space and time. This work leverages the copious number of cosmic ray muons available to ICARUS at the surface. The ionization signal shape simulation applies a novel procedure that tunes the simulation to match what is measured in data. The end result of the equalization procedure and simulation tuning allows for a comparison of charge measurements in ICARUS between Monte Carlo simulation and data, showing good performance with minimal residual bias between the two.

The Magellanic Clouds (MCs) are the Milky Way's most massive dwarf satellites. As they also represent the closest pair of galaxies in an ongoing tidal interaction, while simultaneously infalling into the Milky Way halo, they provide a unique opportunity to study in detail an ongoing three-body encounter. We present the ``YMCA (Yes, Magellanic Clouds Again) survey: probing the outer regions of the Magellanic system with VST'' based on deep optical photometry carried out with the VLT Survey Telescope (VST). YMCA targeted 110 square degrees, in the g and i filters, in the periphery of both the MCs, including a long strip in between the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC). The photometry of YMCA is sufficiently deep (50\% complete down to $g \simeq 23.5-24.0$~mag) to allow for a detailed analysis of main-sequence stars in regions of the MCs remained relatively unexplored at these faint magnitudes. The resulting colour-magnitude diagrams reveal that the outskirts of the MCs are predominantly characterized by intermediate-age and old stellar populations, with limited or negligible evidence of recent star formation. The analysis of the age distribution of star clusters (SCs) within the surveyed area, both already known and newly discovered candidates, hints at a close fly-by between the LMC and SMC that occurred $\simeq 2.5-3.0$~Gyr ago, in agreement with previous results. We also report the discovery of candidate SCs with ages within the so-called ``age-gap'', questioning its real existence., Comment: 28 pages, 21 figures. Accepted for publication on A&A

We evaluate the resource efficiency of Mode Group Division Multiplexing (MGDM) with shared path protection (SPP) in optical networks. On our case studies, SPP with MGDM obtains significant savings in terms of both additional backup spectrum occupation and MIMO-computing resources compared to other few-mode-transmission scenarios.

This paper introduces Generalized Quantum-assisted Digital Signature (GQaDS), an improved version of a recently proposed scheme whose information theoretic security is inherited by adopting QKD keys for digital signature purposes. Its security against forging is computed considering a trial-and-error approach taken by the malicious forger and GQaDS parameters are optimized via an analytical approach balancing between forgery and repudiation probabilities. The hash functions of the previous implementation are replaced with Carter-Wegman Message Authentication Codes (MACs), strengthening the scheme security and reducing the signature length. For particular scenarios where the second verifier has a safe reputation, a simplified version of GQaDS, namely deterministic GQaDS, can further reduce the required signature length, keeping the desired security strength.

Recent evaluations of cross-domain text classification models aim to measure the ability of a model to obtain domain-invariant performance in a target domain given labeled samples in a source domain. The primary strategy for this evaluation relies on assumed differences between source domain samples and target domain samples in benchmark datasets. This evaluation strategy fails to account for the similarity between source and target domains, and may mask when models fail to transfer learning to specific target samples which are highly dissimilar from the source domain. We introduce Depth $F_1$, a novel cross-domain text classification performance metric. Designed to be complementary to existing classification metrics such as $F_1$, Depth $F_1$ measures how well a model performs on target samples which are dissimilar from the source domain. We motivate this metric using standard cross-domain text classification datasets and benchmark several recent cross-domain text classification models, with the goal of enabling in-depth evaluation of the semantic generalizability of cross-domain text classification models.

We investigate the inclusive production of fully charmed tetraquarks, $T_{4c}(0^{++})$ or $T_{4c}(2^{++})$ radial excitations, in high-energy proton collisions. We build our study upon the collinear fragmentation of a single parton in a variable-flavor number scheme, suited to describe the tetraquark formation mechanism from moderate to large transverse-momentum regimes. To this extent, we derive a novel set of DGLAP-evolving collinear fragmentation functions, named TQ4Q1.0 determinations. They encode initial-scale inputs corresponding to both gluon and heavy-quark fragmentation channels, defined within the context of quark-potential and spin-physics inspired models, respectively. We work within the NLL/NLO$^+$ hybrid factorization and make use of the JETHAD numeric interface along with the symJETHAD symbolic calculation plugin. With these tools, we provide predictions for high-energy observables sensitive to $T_{4c}$ plus jet emissions at center-of-mass energies ranging from 14 TeV at the LHC to the 100 TeV nominal energy of the FCC., Comment: 56 pages, 13 figures, version published in EPJC

Classical Cepheids (DCEPs) are crucial for calibrating the extragalactic distance ladder, ultimately enabling the determination of the Hubble constant through the PL and PW relations they exhibit. Hence it's vital to understand how the PL and PW relations depend on metallicity. This is the purpose of the C-MetaLL survey within which this work is situated. DCEPs are also very important tracers of the young populations placed along the Galactic disc. We aim to enlarge the sample of DCEPs with accurate abundances from high-resolution spectroscopy. Our goal is to extend the range of measured metallicities towards the metal-poor regime to better cover the parameter space. We observed objects in a wide range of Galactocentric radii, allowing us to study in detail the abundance gradients present in the Galactic disc. We present the results of the analysis of 331 spectra obtained for 180 individual DCEPs with a variety of high-resolution spectrographs. We derived accurate atmospheric parameters, radial velocities, and abundances for up to 29 different species. The iron abundances range between 0.5 and -1 dex with a rather homogeneous distribution in metallicity. The sample presented in this paper was complemented with that already published in the context of the C-MetaLL survey, resulting in a total of 292 pulsators whose spectra have been analysed in a homogeneous way. These data were used to study the abundance gradients of the Galactic disc in a range of Galactocentric radii spanning the range 5-20 kpc. For most of the elements we found a clear negative gradient, with a slope of -0.071\pm0.003 dex kpc^-1 for [Fe/H] case. Through a qualitative fit with the Galactic spiral arms we shown how our farthest targets (R_GC>10 kpc) trace both the Outer and OSC arms. The homogeneity of the sample will be of pivotal importance for the study of the metallicity dependance of the DCEP PL relations., Comment: 16 pages, 16 figures, 4 tables, accepted to be published in A&A, version post layout and language editor corrections

We study the ionised gas kinematics of 293 Active Galactic Nuclei (AGN) hosts as compared to that of 485 control galaxies from the MaNGA-SDSS survey using measurements of the [OIII]$\lambda$5007\AA emission-line profiles, presenting flux, velocity and W$_{80}$ maps. In 45% of the AGN, a broad component was needed to fit the line profiles wings within the inner few kpc, that we have identified with an outflow. But in most AGN, the profiles are broader than that of their controls over a much more extended region, identified as the "kinematically disturbed regions" (KDRs). We find a positive correlation between the mean $\langle$W$_{80}\rangle$ and L[OIII], supporting that the KDR is due to heating and turbulence of the ISM by outflows and radiation from the AGN. The extent R$_{KDR}$ reaches up to 24kpc, with a mean ratio to that of the ENLR of 57%. We estimate ionised gas mass flow rates ($\dot{M}_{\rm out}$) and kinetic powers ($\dot{E}_{\rm out}$) both from the AGN broad components and from the W$_{80}$ values, that can be obtained for the whole AGN sample. We find values for $\dot{M}_{\rm out}$ and $\dot{E}_{\rm out}$ that correlate with the AGN luminosity $L_{bol}$, populating the low luminosity end of these known correlations. The mean coupling efficiency between $\dot{E}_{\rm out}$ and AGN luminosity is $\approx$ 0.02% from the W$_{80}$ values and lower from the broad component. But the large extent of the KDR shows that even low-luminosity AGN can impact the host galaxy along several kpc in a "maintenance mode" feedback.

A recently developed approach to the thermodynamics of open quantum systems, on the basis of the principle of minimal dissipation, is applied to the spin-boson model. Employing a numerically exact quantum dynamical treatment based on the hierarchical equations of motion (HEOM) method, we investigate the influence of the environment on quantities such as work, heat and entropy production in a range of parameters which go beyond the weak-coupling limit and include both the non-adiabatic and the adiabatic regimes. The results reveal significant differences to the weak-coupling forms of work, heat and entropy production, which are analyzed in some detail.

Large language models (LLMs) have been shown to be proficient in correctly answering questions in the context of online discourse. However, the study of using LLMs to model human-like answers to fact-driven social media questions is still under-explored. In this work, we investigate how LLMs model the wide variety of human answers to fact-driven questions posed on several topic-specific Reddit communities, or subreddits. We collect and release a dataset of 409 fact-driven questions and 7,534 diverse, human-rated answers from 15 r/Ask{Topic} communities across 3 categories: profession, social identity, and geographic location. We find that LLMs are considerably better at modeling highly-rated human answers to such questions, as opposed to poorly-rated human answers. We present several directions for future research based on our initial findings., Comment: 4 pages, 2 figures

Structurally anisotropic materials are ubiquitous in several application fields, yet their accurate optical characterization remains challenging due to the lack of general models linking their scattering coefficients to the macroscopic transport observables, and the need to combine multiple measurements to retrieve their direction-dependent values. Here, we present an improved method for the experimental determination of light transport tensor coefficients from the diffusive rates measured along all three directions, based on transient transmittance measurements and a generalized Monte Carlo model. We apply our method to the characterization of light transport properties in two common anisotropic materials - polytetrafluoroethylene (PTFE) tape and paper - highlighting the magnitude of systematic deviations that are typically incurred when neglecting anisotropy.

In this paper, we develop an LLM-powered framework for the curation and evaluation of emerging opinion mining in online health communities. We formulate emerging opinion mining as a pairwise stance detection problem between (title, comment) pairs sourced from Reddit, where post titles contain emerging health-related claims on a topic that is not predefined. The claims are either explicitly or implicitly expressed by the user. We detail (i) a method of claim identification -- the task of identifying if a post title contains a claim and (ii) an opinion mining-driven evaluation framework for stance detection using LLMs. We facilitate our exploration by releasing a novel test dataset, Long COVID-Stance, or LC-stance, which can be used to evaluate LLMs on the tasks of claim identification and stance detection in online health communities. Long Covid is an emerging post-COVID disorder with uncertain and complex treatment guidelines, thus making it a suitable use case for our task. LC-Stance contains long COVID treatment related discourse sourced from a Reddit community. Our evaluation shows that GPT-4 significantly outperforms prior works on zero-shot stance detection. We then perform thorough LLM model diagnostics, identifying the role of claim type (i.e. implicit vs explicit claims) and comment length as sources of model error.

Event Argument Extraction (EAE) is an extremely difficult information extraction problem -- with significant limitations in few-shot cross-domain (FSCD) settings. A common solution to FSCD modeling is data augmentation. Unfortunately, existing augmentation methods are not well-suited to a variety of real-world EAE contexts including (i) The need to model long documents (10+ sentences) (ii) The need to model zero and few-shot roles (i.e. event roles with little to no training representation). In this work, we introduce two novel LLM-powered data augmentation frameworks for synthesizing extractive document-level EAE samples using zero in-domain training data. Our highest performing methods provide a 16-pt increase in F1 score on extraction of zero shot role types. To better facilitate analysis of cross-domain EAE, we additionally introduce a new metric, Role-Depth F1 (RDF1), which uses statistical depth to identify roles in the target domain which are semantic outliers with respect to roles observed in the source domain. Our experiments show that LLM-based augmentation can boost RDF1 performance by up to 11 F1 points compared to baseline methods., Comment: Paper in submission (8 pages)

Anisotropic light transport is extremely common among scattering materials, yet a comprehensive picture of how macroscopic diffusion is determined by microscopic tensor scattering coefficients is not fully established yet. In this work, we present a theoretical and experimental study of diffusion in structurally anisotropic media with uniaxially symmetric scattering coefficients. Exact analytical relations are derived in the case of index-matched turbid media, unveiling the general relation between microscopic scattering coefficients and the resulting macroscopic diffusion tensor along different directions. Excellent agreement is found against anisotropic Monte Carlo simulations up to high degrees of anisotropy, in contrast with previously proposed approaches. The obtained solutions are used to analyze experimental measurements of anisotropic light transport in polystyrene foam samples under different degrees of uniaxial compression, providing a practical example of their applicability.