arXiv subjects

Jiho Noh

Publications and source records attributed to Jiho Noh.

At least 19 recordsLinked to original sources

arXiv2026

Using Poly-Encoders for Computationally Efficient Automated Creativity Assessment

Automated creativity assessment has been a long standing challenge, with traditional methods often being resource intensive or lacking practical accuracy. We introduce a novel approach by using Poly-Encoder for computationally efficient and accurate automated creativity assessment. We fine-tuned a Poly-Encoder on a public dataset from the Scientific Creative Thinking Test, comprised of approximately 18,000 human-rated question responses. Our method leverages small pre-trained BERT encoders, achieving performance comparable to fine-tuned Large Language Models while significantly reducing computational demands. Experiments with the BERT-family models and poly-code counts achieved Pearson correlations of up to r = 0.74, 95% CI [0.73, 0.75] with human raters, matching the performance of resource intensive LLMs. This study bridges the gap between high performance and computational efficiency, potentially enabling widespread implementation of automated creativity assessment on accessible consumer-grade hardware. With some limitations, our findings suggest that Poly-Encoders are a promising alternative to LLMs for practical, scalable creativity assessment in various contexts, especially educational.

cs.CL↗

arXiv2026

Enhancing Science Classroom Discourse Analysis through Joint Multi-Task Learning for Reasoning-Component Classification

Analyzing the reasoning patterns of students in science classrooms is critical for understanding knowledge construction mechanism and improving instructional practice to maximize cognitive engagement, yet manual coding of classroom discourse at scale remains prohibitively labor-intensive. We present an automated discourse analysis system (ADAS) that jointly classifies teacher and student utterances along two complementary dimensions: Utterance Type and Reasoning Component derived from our prior CDAT framework. To address severe label imbalance among minority classes, we (1) stratify-resplit the annotated corpus, (2) apply LLM-based synthetic data augmentation targeting minority classes, and (3) train a dual-probe head RoBERTa-base classifier. A zero-shot GPT-5.4 baseline achieves macro-F1 of 0.467 on UT and 0.476 on RC, establishing meaningful upper bounds for prompt-only approaches motivating fine-tuning. Beyond classification, we conduct discourse pattern analyses including UTxRC co-occurrence profiling, Cognitive Complexity Index (CCI) computation per session, lag-sequential analysis, and IRF chain analysis, revealing that teacher Feedback-with-Question (Fq) moves are the most consistent antecedents of student inferential reasoning (SR-I). Our results demonstrate that LLM-based augmentation meaningfully improves UT minority-class recognition, and that the structural simplicity of the RC task makes it tractable even for lexical baselines.

cs.CL↗

arXiv2026

Automated Domain Question Mapping (DQM) with Educational Learning Materials

Concept maps have been widely utilized in education to depict knowledge structures and the interconnections between disciplinary concepts. Nonetheless, devising a computational method for automatically constructing a concept map from unstructured educational materials presents challenges due to the complexity and variability of educational content. We focus primarily on two challenges: (1) the lack of disciplinary concepts that are specifically designed for multi-level pedagogical purposes from low-order to high-order thinking, and (2) the limited availability of labeled data concerning disciplinary concepts and their interrelationships. To tackle these challenges, this research introduces an innovative approach for constructing Domain Question Maps (DQMs), rather than traditional concept maps. By formulating specific questions aligned with learning objectives, DQMs enhance knowledge representation and improve readiness for learner engagement. The findings indicate that the proposed method can effectively generate educational questions and discern hierarchical relationships among them, leading to structured question maps that facilitate personalized and adaptive learning in downstream applications.

cs.AI↗

arXiv2025

Orbital Frontiers: Harnessing Higher Modes in Photonic Simulators

Photonic platforms have emerged as versatile and powerful classical simulators of quantum dynamics, providing clean, controllable optical analogs of extended structured (i.e., crystalline) electronic systems. While most realizations to date have used only the fundamental mode in each site, recent advances in structured light - particularly the use of higher-order spatial modes, including those with orbital angular momentum - are enabling richer dynamics and new functionalities. These additional degrees of freedom facilitate the emulation of phenomena ranging from topological band structures and synthetic gauge fields to orbitronics. In this perspective, we discuss how exploiting the internal structure of higher-order modes is reshaping the scope and capabilities of photonic platforms for simulating quantum phenomena.

physics.optics↗

arXiv2025

Two-photon Interference of Biphotons Emitted by Overlapping Resonances in Metasurfaces

Two-photon interference, a quantum phenomenon arising from the principle of indistinguishability, is a powerful tool for quantum state engineering and plays a fundamental role in various quantum technologies. These technologies demand robust and efficient sources of quantum light, as well as scalable, integrable and multifunctional platforms. In this regard, quantum optical metasurfaces (QOMs) are emerging as promising platforms for quantum light generation, namely biphotons via spontaneous parametric down-conversion (SPDC), and its engineering. Due to the relaxation of phase matching, SPDC in QOMs allows different channels of biphoton generation, such as those supported by overlapping resonances, to occur simultaneously. In previously reported QOMs, however, SPDC was too weak to observe such effects. Here we develop QOMs based on [110]-oriented GaAs that provide more than an order of magnitude enhancement in SPDC rate, after accounting for the spectral bandwidth, compared to any other QOMs studied to date. This boosted efficiency allows the QOMs support the simultaneous generation of SPDC from several spectrally overlapping optical modes. Using polarization components in the interferometer analyzer, we intentionally erase the distinguishability between the biphotons from a high-$Q$ quasi-bound-state-in-the-continuum resonance and a low-$Q$ Mie resonance, which results in the first-time observation of two-photon interference in the spectral domain in these types of devices. This quantum interference can considerably enrich the generation of entangled photons in metasurfaces. Their advanced multifunctionality, improved nonlinear response, ease of fabrication and compact footprint of [110]-GaAs QOMs position them as promising platforms to fulfill the requirements for photonic quantum technologies.

quant-ph↗

arXiv2025

YouLeQD: Decoding the Cognitive Complexity of Questions and Engagement in Online Educational Videos from Learners' Perspectives

Questioning is a fundamental aspect of education, as it helps assess students' understanding, promotes critical thinking, and encourages active engagement. With the rise of artificial intelligence in education, there is a growing interest in developing intelligent systems that can automatically generate and answer questions and facilitate interactions in both virtual and in-person education settings. However, to develop effective AI models for education, it is essential to have a fundamental understanding of questioning. In this study, we created the YouTube Learners' Questions on Bloom's Taxonomy Dataset (YouLeQD), which contains learner-posed questions from YouTube lecture video comments. Along with the dataset, we developed two RoBERTa-based classification models leveraging Large Language Models to detect questions and analyze their cognitive complexity using Bloom's Taxonomy. This dataset and our findings provide valuable insights into the cognitive complexity of learner-posed questions in educational videos and their relationship with interaction metrics. This can aid in the development of more effective AI models for education and improve the overall learning experience for students.

cs.CL↗

arXiv2024

Giant non-reciprocity and gyration through modulation-induced Hatano-Nelson coupling in integrated photonics

Asymmetric energy exchange interactions, also known as Hatano-Nelson type couplings, enable the study of non-Hermitian physics and associated phenomena like the non-Hermitian skin effect and exceptional points (EP). Since these interactions are by definition non-reciprocal, there have been very few options for real-space implementations in integrated photonics. In this work, we show that real-space asymmetric couplings are readily achievable in integrated photonic systems through time-domain dynamic modulation. We experimentally study this concept using a two-resonator photonic molecule produced in a lithium niobate on insulator platform that is electro-optically modulated by rf stimuli. We demonstrate the dynamic tuning of the Hatano-Nelson coupling between the resonators, surpassing the asymmetry that has been achieved in previous work, to reach an EP for the first time. We are additionally able to flip the relative sign of the couplings for opposite directions by going past the EP. Using this capability, we show that the through-chain transport can be configured to exhibit both giant (60 dB) optical contrast as well as photonic gyration or non-reciprocal pi phase contrast.

physics.optics↗

arXiv2024

Quantum Pair Generation in Nonlinear Metasurfaces with Mixed and Pure Photon Polarizations

Metasurfaces are highly effective at manipulating classical light in the linear regime; however, effectively controlling the polarization of non-classical light generated from nonlinear resonant metasurfaces remains a challenge. Here, we present a solution by achieving polarization engineering of frequency-nondegenerate biphotons emitted via spontaneous parametric down-conversion (SPDC) in GaAs metasurfaces, where quasi-bound states in the continuum (qBIC) resonances were utilized for boosting the biphoton generation. By performing a comprehensive polarization tomography, we demonstrate that the polarization of the emitted photons directly reflects the qBIC mode's far-field properties. Furthermore, we show that both the type of qBIC mode and the symmetry of the meta-atoms can be tailored to control each single-photon polarization state, and that the subsequent two-photon polarization states are nearly separable, offering potential applications in the heralded generation of single photons with adjustable polarization. This work provides a significant step towards utilizing metasurfaces to not only generate quantum light but also engineer their polarization, a critical aspect for future quantum technologies.

quant-ph↗

arXiv2023

A mono-atomic orbital-based 1D topological crystalline insulator

Topological crystalline insulators (TCIs) are classified by topological invariants defined with respect to the crystalline symmetries of their gapped bulk. The bulk-boundary correspondence then links the topological properties of the bulk to robust observables on the edges, e.g., the existence of robust edge modes or fractional charge. In one dimension, TCIs protected by reflection symmetry have been realized in a variety of systems where each unit cell has spatially distributed degrees of freedom (SDoF). However, these realizations of TCIs face practical challenges stemming from the sensitivity of the resulting edge modes to variations in edge termination and to the local breaking of the protective spatial symmetries by inhomogeneity. Here we demonstrate topologically protected edge states in a mono-atomic, orbital-based TCI that mitigates both of these issues. By collapsing all SDoF within the unit cell to a singular point in space, we eliminate the ambiguity in unit cell definition and hence remove a prominent source of boundary termination variability. The topological observables are also more tolerant to disorder in the orbital energies. To validate this concept, we experimentally realize a lattice of mechanical resonators where each resonator acts as an "atom" that harbors two key orbital degrees of freedom having opposite reflection parity. Our measurements of this system provide direct visualization of the $sp$-hybridization between orbital modes that leads to a non-trivial band inversion in the bulk. Furthermore, as the spatial width of the resonators is tuned, one can drive a transition between a topological and trivial phase. In the future we expect our approach can be extended to realize orbital-based obstructed atomic insulators and TCIs in higher dimensions.

cond-mat.mes-hall↗

arXiv2023

Electrically-Controlled Suppression of Rayleigh Backscattering in an Integrated Photonic Circuit

Undesirable light scattering is an important fundamental cause for photon loss in nanophotonics. Rayleigh backscattering can be particularly difficult to avoid in wave-guiding systems and arises from both material defects and geometric defects at the subwavelength scale. It has been previously shown that systems with broken time-reversal symmetry (TRS) can naturally suppress detrimental Rayleigh backscattering, but these approaches have never been demonstrated in integrated photonics or through practical TRS-breaking techniques. In this work, we show that it is possible to suppress disorder-induced Rayleigh backscattering in integrated photonics via electrical excitation, even when defects are clearly present. Our experiment is performed in a lithium niobate on insulator (LNOI) integrated ring resonator at telecom wavelength, in which TRS is strongly broken through an acousto-optic interaction that is induced via radiofrequency input. We present evidence that Rayleigh backscattering in the resonator is almost completely suppressed by measuring both the optical density of states and through direct measurements of the back-scattered light. We additionally provide an intuitive argument to show that, in an appropriate frame of reference, the suppression of backscattering can be readily understood as a form of topological protection.

physics.optics↗

arXiv2022

A Survey on Conversational Search and Applications in Biomedicine

This paper aims to provide a radical rundown on Conversation Search (ConvSearch), an approach to enhance the information retrieval method where users engage in a dialogue for the information-seeking tasks. In this survey, we predominantly focused on the human interactive characteristics of the ConvSearch systems, highlighting the operations of the action modules, likely the Retrieval system, Question-Answering, and Recommender system. We labeled various ConvSearch research problems in knowledge bases, natural language processing, and dialogue management systems along with the action modules. We further categorized the framework to ConvSearch and the application is directed toward biomedical and healthcare fields for the utilization of clinical social technology. Finally, we conclude by talking through the challenges and issues of ConvSearch, particularly in Bio-Medicine. Our main aim is to provide an integrated and unified vision of the ConvSearch components from different fields, which benefit the information-seeking process in healthcare systems.

cs.CL↗

arXiv2022

Scattering theory of delicate topological insulators

We study the scattering theory of delicate topological insulators (TIs), which are novel topological phases beyond the paradigm of the tenfold way, topological quantum chemistry, and the symmetry indicator method. We demonstrate that the phase of the reflection amplitude can probe the delicate topology by capturing a characteristic feature of a delicate TI. This feature is the returning Thouless pump, where an integer number of charges are pumped forward and backward in the first and second half of the adiabatic cycle respectively. As a byproduct of our analysis we show that requiring additional symmetries can stable the boundary states of a delicate TI beyond the conventional requirement of a sharply defined surface. Furthermore, we propose a photonic crystal experiment to implement a delicate TI and measure its reflection phase which reveals the delicate topology.

cond-mat.mes-hall↗

arXiv2022

Higher-order topological pumping and its observation in photonic lattices

The discovery of the quantization of particle transport in adiabatic pumping cycles of periodic structures by Thouless [Phys. Rev. B 27, 6083 (1983)] linked the Chern number, a topological invariant characterizing the quantum Hall effect in two-dimensional electron gases, with the topology of dynamical periodic systems in one dimension. Here, we demonstrate its counterpart for higher-order topology. Specifically, we show that adiabatic cycles in two-dimensional crystals with vanishing dipole moments (and therefore zero overall particle transport) can nevertheless be topologically nontrivial. These cycles are associated with higher-order topology and can be diagnosed by their ability to produce corner-to-corner transport in certain metamaterial platforms. We experimentally verify the corner to corner transport associated with this topological pump by using an array of photonic waveguides adiabatically modulated in their separations and refractive indices. By mapping the dynamical phenomenon demonstrated here from two spatial and one temporal dimensions to three spatial dimensions, our observations are equivalent to the observation of chiral hinge states in a three-dimensional second-order topological insulator.

cond-mat.mes-hall↗

arXiv2022

Photonic quadrupole topological insulator using orbital-induced synthetic flux

The rich physical properties of multiatomic molecules and crystalline structures are determined, to a significant extent, by the underlying geometry and connectivity of atomic orbitals. This orbital degree of freedom has also been used effectively to introduce structural diversity in a few synthetic materials including polariton lattices nonlinear photonic lattices and ultracold atoms in optical lattices. In particular, the mixing of orbitals with distinct parity representations, such as $s$ and $p$ orbitals, has been shown to be especially useful for generating systems that require alternating phase patterns, as with the sign of couplings within a lattice. Here we show that by further breaking the symmetries of such mixed-orbital lattices, it is possible to generate synthetic magnetic flux threading the lattice. This capability allows the generation of multipole higher-order topological phases in synthetic bosonic platforms, in which $π$ flux threading each plaquette of the lattice is required, and which to date have only been implemented using tailored connectivity patterns. We use this insight to experimentally demonstrate a quadrupole photonic topological insulator in a two-dimensional lattice of waveguides that leverage modes with both $s$ and $p$ orbital-type representations. We confirm the nontrivial quadrupole topology of the system by observing the presence of protected zero-dimensional states, which are spatially confined to the corners, and by confirming that these states sit at the band gap. Our approach is also applicable to a broader range of time-reversal-invariant synthetic materials that do not allow for tailored connectivity, e.g. with nanoscale geometries, and in which synthetic fluxes are essential.

physics.optics↗

arXiv2022

Spontaneously-Induced Dirac Boundary State and Digitization in a Nonlinear Resonator Chain

The low-energy excitations in many condensed matter and metamaterial systems can be well described by the Dirac equation. The mass term associated with these collective excitations, also known as the Dirac mass, can take any value and is directly responsible for determining whether the resultant band structure exhibits a band gap or a Dirac point with linear dispersion. Manipulation of this Dirac mass has inspired new methods of band structure engineering and electron confinement. Notably, it has been shown that a massless state necessarily localizes at any domain wall that divides regions with Dirac masses of different signs. These localized states are known as Jackiw-Rebbi-type (JR-type) Dirac boundary modes and their tunability and localization features have valuable technological potential. In this study, we experimentally demonstrate that nonlinearity within a 1D Dirac material can result in the spontaneous appearance of a domain boundary for the Dirac mass. Our experiments are performed in a dimerized magneto-mechanical metamaterial that allows complete control of both the magnitude and sign of the local material nonlinearity, as well as the sign of the Dirac mass. We find that the massless bound state that emerges at the spontaneously appearing domain boundary acts similarly to a dopant site within an insulator, causing the material to exhibit a dramatic binary switch in its conductivity when driven above an excitation threshold.

cond-mat.mes-hall↗

arXiv2021

Improved Biomedical Word Embeddings in the Transformer Era

Biomedical word embeddings are usually pre-trained on free text corpora with neural methods that capture local and global distributional properties. They are leveraged in downstream tasks using various neural architectures that are designed to optimize task-specific objectives that might further tune such embeddings. Since 2018, however, there is a marked shift from these static embeddings to contextual embeddings motivated by language models (e.g., ELMo, transformers such as BERT, and ULMFiT). These dynamic embeddings have the added benefit of being able to distinguish homonyms and acronyms given their context. However, static embeddings are still relevant in low resource settings (e.g., smart devices, IoT elements) and to study lexical semantics from a computational linguistics perspective. In this paper, we jointly learn word and concept embeddings by first using the skip-gram method and further fine-tuning them with correlational information manifesting in co-occurring Medical Subject Heading (MeSH) concepts in biomedical citations. This fine-tuning is accomplished with the BERT transformer architecture in the two-sentence input mode with a classification objective that captures MeSH pair co-occurrence. In essence, we repurpose a transformer architecture (typically used to generate dynamic embeddings) to improve static embeddings using concept correlations. We conduct evaluations of these tuned static embeddings using multiple datasets for word relatedness developed by previous efforts. Without selectively culling concepts and terms (as was pursued by previous efforts), we believe we offer the most exhaustive evaluation of static embeddings to date with clear performance improvements across the board. We provide our code and embeddings for public use for downstream applications and research endeavors: https://github.com/bionlproc/BERT-CRel-Embeddings

cs.CL↗

arXiv2021

Observation of Quadratic (Charge-2) Weyl Point Splitting in Near-Infrared Photonic Crystals

Weyl points are point degeneracies that occur in momentum space of periodic materials, and are associated with a quantized topological charge. We experimentally observe in a 3D micro-printed photonic crystal that a charge-2 Weyl point can be split into two charge-1 Weyl points as the protecting symmetry of the original charge-2 Weyl point is broken. Moreover, we use a theoretical analysis to confirm where the charge-1 Weyl points move within the Brillouin zone as the strength of the symmetry breaking increases, and confirm it in experiments using Fourier-transform infrared spectrometry. This micro-scale observation and control of Weyl points is important for realizing robust topological devices in the near-infrared.

physics.optics↗

arXiv2020

Literature Retrieval for Precision Medicine with Neural Matching and Faceted Summarization

Information retrieval (IR) for precision medicine (PM) often involves looking for multiple pieces of evidence that characterize a patient case. This typically includes at least the name of a condition and a genetic variation that applies to the patient. Other factors such as demographic attributes, comorbidities, and social determinants may also be pertinent. As such, the retrieval problem is often formulated as ad hoc search but with multiple facets (e.g., disease, mutation) that may need to be incorporated. In this paper, we present a document reranking approach that combines neural query-document matching and text summarization toward such retrieval scenarios. Our architecture builds on the basic BERT model with three specific components for reranking: (a). document-query matching (b). keyword extraction and (c). facet-conditioned abstractive summarization. The outcomes of (b) and (c) are used to essentially transform a candidate document into a concise summary that can be compared with the query at hand to compute a relevance score. Component (a) directly generates a matching score of a candidate document for a query. The full architecture benefits from the complementary potential of document-query matching and the novel document transformation approach based on summarization along PM facets. Evaluations using NIST's TREC-PM track datasets (2017--2019) show that our model achieves state-of-the-art performance. To foster reproducibility, our code is made available here: https://github.com/bionlproc/text-summ-for-doc-retrieval.

cs.CL↗