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High-quality, diverse data are vital for large language models (LLMs) but remain scarce and costly. Data synthesis is a viable alternative and succeeds on closed tasks, yet the humanities and social sciences (HSS) are overlooked, and their…
Accurate evaluation of multimodal large language models (MLLMs) in dental panoramic radiography (orthopantomogram, OPG) is limited by the lack of fine-grained, clinically reliable benchmarks that reflect expert interpretation. This work…
Using the recently introduced ensemble variational Monte Carlo (VMC), we study optimized wave functions for strongly correlated point defects, including nitrogen-vacancy and silicon-vacancy centers in diamond and substitutional iron and…
In switchback experiments with unequal cluster sizes, outcome dispersion across randomization units inflates estimator variance and limits statistical power. Standard control-using-prediction-as-covariate (CUPAC) adjustment may be…
Structural materials for fusion reactors undergo neutron irradiation, generating defect populations that govern their mechanical response through irradiation hardening. Physically based mesoscale constitutive models require accurate…
Continuous software engineering in regulated domains requires engineering teams to address security throughout the development lifecycle. Yet making security requirements explicit in backlog items is still problematic. Engineers must…
Large language models (LLMs) are becoming increasingly integrated into mainstream development platforms and daily technological workflows, typically behind moderation and safety controls. Despite these controls, preventing prompt-based…
The deep learning revolution, kicked off by AlexNet, taught us that end-to-end training beats decomposing a problem into hand-designed stages. Generative modeling, however, has remained the exception-despite generative models being…
Machine learning methods are increasingly used for traffic prediction in applications such as autonomous driving. Such predictions must be both highly accurate and immediately available, making methods with low computational costs and fast…
Sybil attackers are Blockchain actors that adopt the characteristics of regular users to exploit airdrops or influence governance. Current methods of Sybil actor detection include constructing graphs, which requires token transfers between…
State-of-the-art head-mounted displays (HMDs) enable gaze-based selection in virtual environments. Yet, these HMDs suffer from the vergence-accommodation conflict (VAC), which is known to affect interaction performance. The VAC might…
Many crucial processes are too complex for computational modeling, requiring experimentation to identify promising materials. Here, a methodology for material design is presented, while photocatalysis is presented as a specific case-study.…
We introduce a $B$-decay tagged energy correlator (BTEC) to resolve the angular structure of energy flow in inclusive $B$ decays in the endpoint region, focusing on the direct-photon contribution to $\overline B\to X_s\gamma$. At leading…
While data synthesis for large language models (LLMs) is prevalent, it primarily targets domains with verifiable answers, overlooking open-ended humanities and social sciences (HSS), where nuanced quality judgments matter more than…
Quark stars-hypothetical compact stars made entirely of deconfined quark matter-offer a clean testing ground for gravity beyond general relativity. We study their structure in $f(T,\mathcal{T})$ gravity, a teleparallel theory in which…
Let $K$ be a global function field of characteristic~$p$ and let $G$ be a finite abelian group of exponent $p^e$. We show that the multivariate generating function counting sub-$G$-extensions of $K$ with respect to $e$ specific height…
We present high-resolution dayside spectroscopy of the ultra-hot Jupiter WASP-178b obtained with the Gemini High-resolution Optical SpecTrograph (GHOST) at the Gemini South Observatory. The observations cover pre- and post-eclipse orbital…
Space-time modulations of the electromagnetic response offer new opportunities for wave control. In particular, such systems can emulate moving-medium responses and the associated Fresnel drag in the homogenization limit. Existing…
We study the impact of light spectator axions on the seeding of primordial black holes (PBHs) during inflation in string theory. Primordial black holes exhibit unique and novel phenomenology, and may constitute the observed dark matter.…
Agent self-evolution has primarily focused on learning how to act, while overlooking an equally important capability: learning to discover what an agent does not know. Existing approaches typically assume that failure discovery is given,…