Miracle-dz/UniFAR-FTUs huggingface dataset:
Verifiable Reinforcement Learning Systems via Compositionality

We propose a framework for verifiable and compositional reinforcement learning (RL) in which a collection of RL subsystems, each of which learns to accomplish a separate subtask, are composed to achieve an overall task. The framework consists of a high-level model, represented as a parametric Markov decision process, which is used to plan and analyze compositions of subsystems, and of the collection of low-level subsystems themselves. The subsystems are implemented as deep RL agents operating under partial observability. By defining interfaces between the subsystems, the framework enables automatic decompositions of task specifications, e.g., reach a target set of states with a probability of at least 0.95, into individual subtask specifications, i.e. achieve the subsystem's exit conditions with at least some minimum probability, given that its entry conditions are met. This in turn allows for the independent training and testing of the subsystems. We present theoretical results guaranteeing that if each subsystem learns a policy satisfying its subtask specification, then their composition is guaranteed to satisfy the overall task specification. Conversely, if the subtask specifications cannot all be satisfied by the learned policies, we present a method, formulated as the problem of finding an optimal set of parameters in the high-level model, to automatically update the subtask specifications to account for the observed shortcomings. The result is an iterative procedure for defining subtask specifications, and for training the subsystems to meet them. Experimental results demonstrate the presented framework's novel capabilities in environments with both full and partial observability, discrete and continuous state and action spaces, as well as deterministic and stochastic dynamics.
Anisotropic Diffusion Stencils: From Simple Derivations over Stability Estimates to ResNet Implementations

Anisotropic diffusion processes with a diffusion tensor are important in image analysis, physics, and engineering. However, their numerical approximation has a strong impact on dissipative artefacts and deviations from rotation invariance. In this work, we study a large family of finite difference discretisations on a 3 x 3 stencil. We derive it by splitting 2-D anisotropic diffusion into four 1-D diffusions. The resulting stencil class involves one free parameter and covers a wide range of existing discretisations. It comprises the full stencil family of Weickert et al. (2013) and shows that their two parameters contain redundancy. Furthermore, we establish a bound on the spectral norm of the matrix corresponding to the stencil. This gives time step size limits that guarantee stability of an explicit scheme in the Euclidean norm. Our directional splitting also allows a very natural translation of the explicit scheme into ResNet blocks. Employing neural network libraries enables simple and highly efficient parallel implementations on GPUs.
Elucidating the solution space of extended reverse-time SDE for diffusion models

Diffusion models (DMs) demonstrate potent image generation capabilities in various generative modeling tasks. Nevertheless, their primary limitation lies in slow sampling speed, requiring hundreds or thousands of sequential function evaluations through large neural networks to generate high-quality images. Sampling from DMs can be seen alternatively as solving corresponding stochastic differential equations (SDEs) or ordinary differential equations (ODEs). In this work, we formulate the sampling process as an extended reverse-time SDE (ER SDE), unifying prior explorations into ODEs and SDEs. Leveraging the semi-linear structure of ER SDE solutions, we offer exact solutions and arbitrarily high-order approximate solutions for VP SDE and VE SDE, respectively. Based on the solution space of the ER SDE, we yield mathematical insights elucidating the superior performance of ODE solvers over SDE solvers in terms of fast sampling. Additionally, we unveil that VP SDE solvers stand on par with their VE SDE counterparts. Finally, we devise fast and training-free samplers, ER-SDE-Solvers, achieving state-of-the-art performance across all stochastic samplers. Experimental results demonstrate achieving 3.45 FID in 20 function evaluations and 2.24 FID in 50 function evaluations on the ImageNet $64\times64$ dataset.
A correction function-based kernel-free boundary integral method for elliptic PDEs with implicitly defined interfaces

This work addresses a novel version of the kernel-free boundary integral (KFBI) method for solving elliptic PDEs with implicitly defined irregular boundaries and interfaces. We focus on boundary value problems and interface problems, which are reformulated into boundary integral equations and solved with the matrix-free GMRES method. In the KFBI method, evaluating boundary and volume integrals only requires solving equivalent but much simpler interface problems in a bounding box, for which fast solvers such as FFTs and geometric multigrid methods are applicable. For the simple interface problem, a correction function is introduced for both the evaluation of right-hand side correction terms and the interpolation of a non-smooth potential function. A mesh-free collocation method is proposed to compute the correction function near the interface. The new method avoids complicated derivation for derivative jumps of the solution and is easy to implement, especially for the fourth-order method in three space dimensions. Various numerical examples are presented, including challenging cases such as high-contrast coefficients, arbitrarily close interfaces and heterogeneous interface problems. The reported numerical results verify that the proposed method is both accurate and efficient.
All symmetries of near-horizon scattering

Asymptotic symmetries are known to constrain the infrared behaviour of scattering processes in asymptotically flat spacetimes. By the same token, one expects symmetries of the black hole horizon to constrain near-horizon gravitational scattering. In this paper, we make an important advance towards establishing this connection. We find all near-horizon symmetries relevant for gravitational scattering near the horizon of the Schwarzschild black hole. We study large diffeomorphisms of linearised perturbations of the Schwarzschild black hole in a partial wave basis and in gauge that allows for gravitational radiation crossing the event horizon. This setup is ideally suited to study processes involving near-horizon gravitons like scattering and black hole evaporation. We find the most general near-horizon symmetries that are consistent with the perturbations being finite at the horizon. With no further restriction on the boundary conditions than regularity on the horizon, we find the associated covariant charges to be finite and non-zero. These symmetries are therefore physical. The complete symmetry algebra, however, does not close. The maximal subset of symmetries that forms a closed algebra turns out to be $ {\rm Diff}(S^2) $ in a semi-direct sum with two supertranslations. Our boundary conditions in fact allow us to extend the asymptotic Killing vectors everywhere outside the horizon and we show that a sub-algebra closes to all orders in the near-horizon expansion parameter. Interestingly, for a large black hole, the dominant symmetries are just two copies of $ u(1)$, one of which is not present in the maximal closed sub-algebra.
Energy-Consumption Advantage of Quantum Computation

Energy consumption in solving computational problems has been gaining growing attention as a part of the performance measures of computers. Quantum computation is known to offer advantages over classical computation in terms of various computational resources; however, its advantage in energy consumption has been challenging to analyze due to the lack of a theoretical foundation to relate the physical notion of energy and the computer-scientific notion of complexity for quantum computation with finite computational resources. To bridge this gap, we introduce a general framework for studying the energy consumption of quantum and classical computation based on a computational model that has been conventionally used for studying query complexity in computational complexity theory. With this framework, we derive an upper bound for the achievable energy consumption of quantum computation. We also develop techniques for proving a nonzero lower bound of energy consumption of classical computation based on the energy-conservation law and Landauer's principle. With these general bounds, we rigorously prove that quantum computation achieves an exponential energy-consumption advantage over classical computation for solving a specific computational problem, Simon's problem. Furthermore, we clarify how to demonstrate this energy-consumption advantage of quantum computation in an experimental setting. These results provide a fundamental framework and techniques to explore the physical meaning of quantum advantage in the query-complexity setting based on energy consumption, opening an alternative way to study the advantages of quantum computation.
Towards Visual Taxonomy Expansion

Taxonomy expansion task is essential in organizing the ever-increasing volume of new concepts into existing taxonomies. Most existing methods focus exclusively on using textual semantics, leading to an inability to generalize to unseen terms and the "Prototypical Hypernym Problem. " In this paper, we propose Visual Taxonomy Expansion (VTE), introducing visual features into the taxonomy expansion task. We propose a textual hypernymy learning task and a visual prototype learning task to cluster textual and visual semantics. In addition to the tasks on respective modalities, we introduce a hyper-proto constraint that integrates textual and visual semantics to produce fine-grained visual semantics. Our method is evaluated on two datasets, where we obtain compelling results. Specifically, on the Chinese taxonomy dataset, our method significantly improves accuracy by 8.75%. Additionally, our approach performs better than ChatGPT on the Chinese taxonomy dataset.
Optoelectronic and transport properties of vacancy-ordered double-perovskite halides: A first-principles study

In the search for stable lead (Pb) free perovskites, Vacancy ordered double perovskite (VODP), A$_2$BX$_6$ has emerged as a promising class of materials for solar harvesting owing to their nontoxicity, better stability, and unique optoelectronic properties. Here, we present the stability and the key physical attributes of few selected compounds in a systematic manner using state-of-the-art first-principle calculations. A careful structural and stability analysis via simulating convex hull and compositional phase diagrams for different structural prototypes discloses 14 stable and 1 metastable compounds in this class. The electronic structure calculations using hybrid functional reveals six compounds to acquire band gap in the ideal visible region. These six compounds, namely Cs$_2$SnI$_6$, Cs$_2$PdI$_6$, Cs$_2$TeI$_6$, Cs$_2$TiI$_6$, Cs$_2$PtI$_6$, and Cs$_2$PdBr$_6$, show high optical absorption ($\approx$ 10$^{5}$ cm $^{-1}$) giving rise to high spectroscopic limited maximum efficiency, SLME (15-23\%) in the thin-film thickness range. Close inspection of transport properties reveals polar optical phonon scattering to be the dominant mechanism limiting the overall mobility. Further analysis of the polaron excitations discloses the possibility of large polaron formation at low to moderate defect concentrations. At high defect concentrations, ionized impurity scattering takes over. This suggests that, a simulation based guided control of defect concentrations during synthesis can yield a desired candidate for promissing device application. Additionally, few selected compounds show moderate to high electron mobility values ($\sim$13-63 cm$^2$V$^{-1}$ s$^{-1}$) at room temperature. Overall, the present study paves an important path to help design VODP as Pb-free potential candidates for future optoelectronic applications.
Cited Text Spans for Citation Text Generation

An automatic citation generation system aims to concisely and accurately describe the relationship between two scientific articles. To do so, such a system must ground its outputs to the content of the cited paper to avoid non-factual hallucinations. Due to the length of scientific documents, existing abstractive approaches have conditioned only on cited paper abstracts. We demonstrate empirically that the abstract is not always the most appropriate input for citation generation and that models trained in this way learn to hallucinate. We propose to condition instead on the cited text span (CTS) as an alternative to the abstract. Because manual CTS annotation is extremely time- and labor-intensive, we experiment with distant labeling of candidate CTS sentences, achieving sufficiently strong performance to substitute for expensive human annotations in model training, and we propose a human-in-the-loop, keyword-based CTS retrieval approach that makes generating citation texts grounded in the full text of cited papers both promising and practical.
The GRAVITY Young Stellar Object survey. VII. The inner dusty disks of T Tauri stars

These protoplanetary disks in T Tauri stars play a central role in star and planet formation. We spatially resolve at sub-au scales the innermost regions of a sample of T Tauri's disks to better understand their morphology and composition. We extended our homogeneous data set of 27 Herbig stars and collected near-IR K-band observations of 17 T Tauri stars, spanning effective temperatures and luminosities in the ranges of ~4000-6000 K and ~0.4-10 Lsun. We focus on the continuum emission and develop semi-physical geometrical models to fit the interferometric data and search for trends between the properties of the disk and the central star. The best-fit models of the disk's inner rim correspond to wide rings. We extend the Radius-luminosity relation toward the smallest luminosities (0.4-10 Lsun) and find the R~L^(1/2) trend is no longer valid, since the K-band sizes measured with GRAVITY are larger than the predicted sizes from sublimation radius computation. No clear correlation between the K-band half-flux radius and the mass accretion rate is seen. Having magnetic truncation radii in agreement with the K-band GRAVITY sizes would require magnetic fields as strong as a few kG, which should have been detected, suggesting that accretion is not the main process governing the location of the half-flux radius of the inner dusty disk. Our measurements agree with models that take into account the scattered light. The N-to-K band size ratio may be a proxy for disentangling disks with silicate features in emission from disks with weak and/or in absorption silicate features. When comparing inclinations and PA of the inner disks to those of the outer disks (ALMA) in nine objects of our sample, we detect misalignments for four objects.
Modelling the anisotropic inelastic response of polymeric scaffolds for in situ tissue engineering applications

In situ tissue engineering offers an innovative solution for replacement valves and grafts in cardiovascular medicine. In this approach, a scaffold, which can be obtained by polymer electrospinning, is implanted into the human body and then infiltrated by cells, eventually replacing the scaffold with native tissue. In silico simulations of the whole process in patient-specific models, including implantation, growth and degradation, are very attractive to study the factors that might influence the end result. In our research, we focused on the mechanical behaviour of the polymeric scaffold and its short-term response. Following a recently proposed constitutive model for the anisotropic inelastic behaviour of fibrous polymeric materials, we present here its numerical implementation in a finite element framework. The numerical model is developed as user material for commercial finite element software. The verification of the implementation is performed for elementary deformations. Furthermore, a parallel-plate test is proposed as a large-scale representative example, and the model is validated by comparison with experiments.
Kin selection of time travel: the social evolutionary causes and consequences of dormancy

A basic mechanism of kin selection is limited dispersal, whereby individuals remain close to their place of origin such that even indiscriminate social interaction tends to modify the fitness of genealogical kin. Accordingly, the causes and consequences of dispersal have received an enormous amount of attention in the social evolution literature. This work has focused on dispersal of individuals in space, yet similar logic should apply to dispersal of individuals in time (e.g. dormancy). We investigate how kin selection drives the evolution of dormancy and how dormancy modulates the evolution of altruism. We recover dormancy analogues of key results that have previously been given for dispersal, showing that: (1) kin selection favours dormancy as a means of relaxing competition between relatives; (2) when individuals may adjust their dormancy behaviour to local density, they are favoured to do so, resulting in greater dormancy in high-density neighbourhoods and a concomitant ‘constant non-dormant principle’; (3) when dormancy is constrained to be independent of density, there is no relationship between the rate of dormancy and the evolutionary potential for altruism; and (4) when dormancy is able to evolve in a density-dependent manner, a greater potential for altruism is expected in populations with lower dormancy.
Collections of small urban parks consistently support higher species richness but not higher phylogenetic or functional diversity

When prioritizing regions for conservation protection, decisions are often based on the principle that a single large reserve should support more species than several small reserves of the same total area (SLOSS). This principle remains a central paradigm in conservation planning despite conflicting empirical evidence and methodological concerns. In urban areas where small parks tend to dominate and policies to promote biodiversity are becoming increasingly popular, determining the most appropriate prioritization method is critical. Here, we document the role of SLOSS in defining the seasonal diversity of birds in 475 parks in 21 US cities. Collections of small parks were consistently associated with higher species richness, spatial turnover and rarity. Collections of both small and large parks were associated with higher phylogenetic and functional diversity whose patterns varied across seasons and cities. Thus, collections of small parks are a reliable source of species richness driven by higher spatial turnover and rarity, whereas collections of both small and large parks contain the potential to support higher phylogenetic and functional diversity. The presence of strong intra-annual and geographical variation emphasizes the need for regional prioritization strategies, where multiple diversity metrics are examined across parks and seasons.
Therapists’ beliefs about excessive reassurance seeking and helping manage it: does experience play a role?

Abstract Excessive reassurance seeking (ERS) is believed to play an important role in maintaining mental health problems, in particular anxiety disorders such as obsessive-compulsive disorder and health anxiety. Despite this, therapists commonly give into patients’ requests for reassurance in clinical settings and are generally unsure how to handle the issue both in therapy itself and concerning advice to the patient’s loved ones. In order to increase our understanding of therapists’ perception of ERS and how interventions for ERS are managed, we examined therapists’ perception and understanding of ERS, including its function, which emotional problems therapists associate it with, and what treatment interventions they consider important for managing ERS. Qualified therapists (n=197) were benchmarked against international expert consensus (n=20) drawn from leading clinical researchers. There was evidence that clinical experience right up to the expert level may result in less reassurance giving within treatment settings. Still, there were enough inconsistencies between the experts and other clinicians to suggest that ERS remains poorly understood and is not consistently dealt with clinically. Results are discussed in terms of how current treatment interventions may be limited for treating ERS, highlighting the need to consider new approaches for dealing with this complicated interpersonal behaviour. Key learning aims (1) To describe the role of excessive reassurance seeking in checking behaviour, including its negative personal and interpersonal consequences. (2) To learn that therapists commonly report finding it difficult to manage reassurance seeking. (3) To learn that therapists’ beliefs about excessive reassurance seeking may play a key role in helping us understand how to tackle this complicated behaviour. (4) To consider what therapeutic interventions may be appropriate and helpful for treating excessive reassurance seeking.
Quantitative electrocardiographic measures and long-term mortality in exercise test patients with clinically normal resting electrocardiograms

Background Currently, the only function of the resting electrocardiogram (ECG) in patients referred for exercise testing is to determine whether imaging is mandated. It is unknown if subtle ECG findings in those patients with clinically normal resting ECGs have prognostic significance. Methods We performed a single-center cohort study of 18,964 patients without known cardiovascular disease who had a clinically normal resting ECG and who underwent treadmill exercise testing for evaluation of suspected coronary artery disease. Eleven quantitative ECG measures relating to heart rate, conduction, left ventricular mass, or repolarization were collected digitally. The primary outcome was all-cause mortality. The prognostic importance of a composite ECG score was assessed by measuring its impact on the c-index (analogous to area under receiver operating characteristic curve) and by measures of reclassification. Results During a median follow-up of 10.7 years, 1,585 patients died. The 4 most predictive digital ECG variables were higher ventricular rate, more leftward QRS axis, more downward ST-segment deviation, and longer QT interval. The ECG score was independently associated with mortality (75th vs 25th percentile hazard ratio 1.36, 95% confidence interval 1.25-1.49, P b .0001). The ECG score had modest impact on discrimination (change in c-index 0.04) and reclassification of risk (3.0% decrease of relative integrated discrimination improvement, P b .001). Conclusions Subtle ECG findings relating to heart rate, conduction, left ventricular mass, or repolarization in patients with clinically normal ECGs referred for exercise testing may provide modest additional prognostic information over and above clinical and exercise measures. (Am Heart J 2009;158:61-70.e1.)