arXiv subjects

Christian E. Matt

Publications and source records attributed to Christian E. Matt.

10 recordsLinked to original sources

arXiv2025

Efficient Domain-adaptive Continual Pretraining for the Process Industry in the German Language

Domain-adaptive continual pretraining (DAPT) is a state-of-the-art technique that further trains a language model (LM) on its pretraining task, e.g., masked language modeling (MLM), when common domain adaptation via LM fine-tuning is not possible due to a lack of labeled task data. Although popular, MLM requires a significant corpus of domain-related data, which is difficult to obtain for specific domains in languages other than English, such as the process industry in the German language. This paper introduces an efficient approach called ICL-augmented pretraining or ICL-APT that leverages in-context learning (ICL) and k-nearest neighbors (kNN) to augment target data with domain-related and in-domain texts, significantly reducing GPU time while maintaining strong model performance. Our results show that the best configuration of ICL-APT performed better than the state-of-the-art DAPT by 28.7% (7.87 points) and requires almost 4 times less GPU-computing time, providing a cost-effective solution for industries with limited computational capacity. The findings highlight the broader applicability of this framework to other low-resource industries, making NLP-based solutions more accessible and feasible in production environments.

cs.CL↗

arXiv2024

Automated Collection of Evaluation Dataset for Semantic Search in Low-Resource Domain Language

Domain-specific languages that use a lot of specific terminology often fall into the category of low-resource languages. Collecting test datasets in a narrow domain is time-consuming and requires skilled human resources with domain knowledge and training for the annotation task. This study addresses the challenge of automated collecting test datasets to evaluate semantic search in low-resource domain-specific German language of the process industry. Our approach proposes an end-to-end annotation pipeline for automated query generation to the score reassessment of query-document pairs. To overcome the lack of text encoders trained in the German chemistry domain, we explore a principle of an ensemble of "weak" text encoders trained on common knowledge datasets. We combine individual relevance scores from diverse models to retrieve document candidates and relevance scores generated by an LLM, aiming to achieve consensus on query-document alignment. Evaluation results demonstrate that the ensemble method significantly improves alignment with human-assigned relevance scores, outperforming individual models in both inter-coder agreement and accuracy metrics. These findings suggest that ensemble learning can effectively adapt semantic search systems for specialized, low-resource languages, offering a practical solution to resource limitations in domain-specific contexts.

cs.CL↗

arXiv2024

Generative User-Experience Research for Developing Domain-specific Natural Language Processing Applications

User experience (UX) is a part of human-computer interaction (HCI) research and focuses on increasing intuitiveness, transparency, simplicity, and trust for the system users. Most UX research for machine learning (ML) or natural language processing (NLP) focuses on a data-driven methodology. It engages domain users mainly for usability evaluation. Moreover, more typical UX methods tailor the systems towards user usability, unlike learning about the user needs first. This paper proposes a new methodology for integrating generative UX research into developing domain NLP applications. Generative UX research employs domain users at the initial stages of prototype development, i.e., ideation and concept evaluation, and the last stage for evaluating system usefulness and user utility. The methodology emerged from and is evaluated on a case study about the full-cycle prototype development of a domain-specific semantic search for daily operations in the process industry. A key finding of our case study is that involving domain experts increases their interest and trust in the final NLP application. The combined UX+NLP research of the proposed method efficiently considers data- and user-driven opportunities and constraints, which can be crucial for developing NLP applications.

cs.CL↗

arXiv2023

Visualizing the atomic-scale origin of metallic behavior in Kondo insulators

A Kondo lattice is often electrically insulating at low temperatures. However, several recent experiments have detected signatures of bulk metallicity within this Kondo insulating phase. Here we visualize the real-space charge landscape within a Kondo lattice with atomic resolution using a scanning tunneling microscope. We discover nanometer-scale puddles of metallic conduction electrons centered around uranium-site substitutions in the heavy-fermion compound URu$_2$Si$_2$, and around samarium-site defects in the topological Kondo insulator SmB$_6$. These defects disturb the Kondo screening cloud, leaving behind a fingerprint of the metallic parent state. Our results suggest that the mysterious 3D quantum oscillations measured in SmB$_6$ could arise from these Kondo-lattice defects, although we cannot rule out other explanations. Our imaging technique could enable the development of atomic-scale charge sensors using heavy-fermion probes.

cond-mat.str-el↗

arXiv2022

Imaging Se diffusion across the FeSe/SrTiO$_3$ interface

Monolayer FeSe on SrTiO$_3$ superconducts with reported $T_\mathrm{c}$ as high as 100 K, but the dramatic interfacial $T_\mathrm{c}$ enhancement remains poorly understood. Oxygen vacancies in SrTiO$_3$ are known to enhance the interfacial electron doping, electron-phonon coupling, and superconducting gap, but the detailed mechanism is unclear. Here we apply scanning transmission electron microscopy (STEM) and electron energy loss spectroscopy (EELS) to FeSe/SrTiO$_3$ to image the diffusion of selenium into SrTiO$_3$ to an unexpected depth of several unit cells, consistent with the simultaneously observed depth profile of oxygen vacancies. Our density functional theory (DFT) calculations support the crucial role of oxygen vacancies in facilitating the thermally driven Se diffusion. In contrast to excess Se in the FeSe monolayer or FeSe/SrTiO$_3$ interface that is typically removed during post-growth annealing, the diffused Se remains in the top few unit cells of the SrTiO$_3$ bulk after the extended post-growth annealing that is necessary to achieve superconductivity. Thus, the unexpected Se in SrTiO$_3$ may contribute to the interfacial electron doping and electron-phonon coupling that enhance $T_\mathrm{c}$, suggesting another important role for oxygen vacancies as facilitators of Se diffusion.

cond-mat.supr-con↗

arXiv2022

Spin-polarized imaging of strongly interacting fermions in the ferrimagnetic state of Weyl candidate CeBi

CeBi has an intricate magnetic phase diagram whose fully-polarized state has recently been suggested as a Weyl semimetal, though the role of $f$ states in promoting strong interactions has remained elusive. Here we focus on the less-studied, but also time-reversal symmetry-breaking ferrimagnetic phase of CeBi, where our density functional theory (DFT) calculations predict additional Weyl nodes near the Fermi level $E_\mathrm{F}$. We use spin-polarized scanning tunneling microscopy and spectroscopy to image the surface ferrimagnetic order on the itinerant Bi $p$ states, indicating their orbital hybridization with localized Ce $f$ states. We observe suppression of this spin-polarized signature at $E_\mathrm{F}$, coincident with a Fano line shape in the conductance spectra, suggesting the Bi $p$ states partially Kondo screen the $f$ magnetic moments, and this $p-f$ hybridization causes strong Fermi-level band renormalization. The $p$ band flattening is supported by our quasiparticle interference (QPI) measurements, which also show band splitting in agreement with DFT, painting a consistent picture of a strongly interacting magnetic Weyl semimetal.

cond-mat.str-el↗

arXiv2020

Decoupling of Lattice and Orbital Degrees of Freedom in an Iron-Pnictide Superconductor

The interplay of structural and electronic phases in iron-based superconductors is a central theme in the search for the superconducting pairing mechanism. While electronic nematicity, defined as the breaking of four-fold symmetry triggered by electronic degrees of freedom, is competing with superconductivity, the effect of purely structural orthorhombic order is unexplored. Here, using x-ray diffraction (XRD), we reveal a new structural orthorhombic phase with an exceptionally high onset temperature ($T_\mathrm{ort} \sim 250$ K), which coexists with superconductivity ($T_\mathrm{c} = 25$ K), in an electron-doped iron-pnictide superconductor far from the underdoped region. Furthermore, our angle-resolved photoemission spectroscopy (ARPES) measurements demonstrate the absence of electronic nematic order as the driving mechanism, in contrast to other underdoped iron pnictides where nematicity is commonly found. Our results establish a new, high temperature phase in the phase diagram of iron-pnictide superconductors and impose strong constraints for the modeling of their superconducting pairing mechanism.

cond-mat.supr-con↗

arXiv2020

Consistency between ARPES and STM measurements on SmB$_6$

Strongly correlated topological surface states are promising platforms for next-generation quantum applications, but they remain elusive in real materials. The correlated Kondo insulator SmB$_6$ is one of the most promising candidates, with theoretically predicted heavy Dirac surface states supported by transport and scanning tunneling microscopy (STM) experiments. However, a puzzling discrepancy appears between STM and angle-resolved photoemission (ARPES) experiments on SmB$_6$. Although ARPES detects spin-textured surface states, their velocity is an order of magnitude higher than expected, while the Dirac point -- the hallmark of any topological system -- can only be inferred deep within the bulk valence band. A significant challenge is that SmB$_6$ lacks a natural cleavage plane, resulting in ordered surface domains limited to 10s of nanometers. Here we use STM to show that surface band bending can shift energy features by 10s of meV between domains. Starting from our STM spectra, we simulate the full spectral function as an average over multiple domains with different surface potentials. Our simulation shows excellent agreement with ARPES data, and thus resolves the apparent discrepancy between large-area measurements that average over multiple band-shifted domains and atomically-resolved measurements within a single domain.

cond-mat.str-el↗

arXiv2018

Direct Observation of Orbital Hybridisation in a Cuprate Superconductor

The minimal ingredients to explain the essential physics of layered copper-oxide (cuprates= materials remains heavily debated. Effective low energy single-band models of the copper-oxygen orbitals are widely used because there exists no strong experimental evidence supporting multiband structures. Here we report angle-resolved photoelectron spectroscopy experiments on La-based cuprates that provide direct observation of a two-band structure. This electronic structure, qualitatively consistent with density functional theory, is parametrised by a two-orbital ($d_{x^2-y^2}$ and $d_{z^2}$) tight-binding model. We quantify the orbital hybridisation which provides an explanation for the Fermi surface topology and the proximity of the van-Hove singularity to the Fermi level. Our analysis leads to a unification of electronic hopping parameters for single-layer cuprates and we conclude that hybridisation, restraining d-wave pairing, is an important optimisation element for superconductivity.

cond-mat.supr-con↗

arXiv2015

Electron scattering, charge order, and pseudogap physics in La$_{1.6-x}$Nd$_{0.4}$Sr$_x$CuO$_4$: An angle resolved photoemission spectroscopy study

We report an angle-resolved photoemission study of the charge stripe ordered La$_{1.6-x}$Nd$_{0.4}$Sr$_x$CuO$_4$ system. A comparative and quantitative line shape analysis is presented as the system evolves from the overdoped regime into the charge ordered phase. On the overdoped side ($x=0.20$), a normal state anti-nodal spectral gap opens upon cooling below ~ 80 K. In this process spectral weight is preserved but redistributed to larger energies. A correlation between this spectral gap and electron scattering is found. A different lineshape is observed in the antinodal region of charge ordered Nd-LSCO $x=1/8$. Significant low-energy spectral weight appears to be lost. These observations are discussed in terms of spectral weight redistribution and gapping %of spectral weight originating from charge stripe ordering.

cond-mat.supr-con↗