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Youngchan Kim

Publications and source records attributed to Youngchan Kim.

8 recordsLinked to original sources

RLDX-1 Technical Report

While Vision-Language-Action models (VLAs) have shown remarkable progress toward human-like generalist robotic policies through the versatile intelligence (i.e. broad scene understanding and language-conditioned generalization) inherited from pre-trained Vision-Language Models, they still struggle with complex real-world tasks requiring broader functional capabilities (e.g. motion awareness, long-term memory, and physical sensing). To address this, we introduce RLDX-1, a general-purpose robotic policy for dexterous manipulation built on the Multi-Stream Action Transformer (MSAT), an architecture that unifies these capabilities by integrating heterogeneous modalities through modality-specific streams with cross-modal joint self-attention. RLDX-1 further combines this architecture with system-level design choices, including data synthesis for rare manipulation scenarios, learning procedures specialized for human-like manipulation, and inference optimizations for real-time deployment. Through empirical evaluation, we show that RLDX-1 consistently outperforms recent frontier VLAs (e.g. $\pi_{0.5}$ and GR00T N1.6) across both simulation benchmarks and real-world tasks that require broad functional capabilities beyond general versatility. In particular, RLDX-1 shows superiority in ALLEX humanoid tasks by achieving success rates of 86.8% while $\pi_{0.5}$ and GR00T N1.6 achieve around 40%, highlighting the ability of RLDX-1 to control a high-DoF humanoid robot under diverse functional demands. Together, these results position RLDX-1 as a promising step toward reliable VLAs for complex, contact-rich, and dynamic real-world dexterous manipulation.

cs.RO

Non-Equilibrium Dynamics of the Time-Dependent Excitonic Coupling in Fluorescent Protein Dimers

We quantify the excitonic coupling in the homodimer of dimeric Venus fluorescent protein using a quantum-classical hybrid workflow. Employing a transition-density coupling formalism, we calculate $J = 74.38~\mathrm{cm^{-1}}$, which is 5.6 times stronger than the far-field point-dipole estimate of $13.31~\mathrm{cm^{-1}}$. This disparity highlights the critical role of near-field multipolar effects at the 27.6~\r{A} chromophore centroid separation. Furthermore, we argue that a separation of timescales resolves the apparent theoretical tension between robust experimental excitonic couplings and the highly decoherent biological environment. While it has been hypothesised that the fluorescent protein $\beta$-barrel scaffold sustains coupling by attenuating thermal fluctuations, we emphasise that the separation of timescales fundamentally applies irrespective of the exact degree of environmental noise suppression. Collective photoexcitation imprints the Davydov splitting under optical-limit dielectric screening upon absorption, preceding bulk solvent relaxation and sub-picosecond environmental dephasing. To characterise the subsequent post-absorption evolution, we employ stochastic simulations for quantum parts to model the transition from a delocalised exciton superposition to incoherent hopping between localised chromophore states.

physics.chem-ph

Hyperspectral Polarimetric BRDFs of Real-world Materials

Acquiring bidirectional reflectance distribution functions (BRDFs) is essential for simulating light transport and analytically modeling material properties. Over the past two decades, numerous intensity-only BRDF datasets in the visible spectrum have been introduced, primarily for RGB image rendering applications. However, in scientific and engineering domains, there remains an unmet need to model light transport with polarization--a fundamental wave property of light--across hyperspectral bands. To address this gap, we present the first hyperspectral-polarimetric BRDF (hpBRDF) dataset of real-world materials, spanning wavelengths from 414 to 950\,nm and densely sampled at 68 spectral bands. This dataset covers both the visible and near-infrared (NIR) spectra, enabling detailed material analysis and light reflection simulations that incorporate polarization at each narrow spectral band. We develop an efficient hpBRDF acquisition system that captures high-dimensional hpBRDFs within a feasible acquisition time. Using this system, we demonstrate hyperspectral-polarimetric rendering using the acquired hpBRDFs. To provide insights on hpBRDF, we analyze the hpBRDFs with respect to their dependencies on wavelength, polarization state, material type, and illumination/viewing geometry. Also, we propose compact representations through principal component analysis and implicit neural hpBRDF modeling.

cs.GR

Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset

Image datasets are essential not only in validating existing methods in computer vision but also in developing new methods. Most existing image datasets focus on trichromatic intensity images to mimic human vision. However, polarization and spectrum, the wave properties of light that animals in harsh environments and with limited brain capacity often rely on, remain underrepresented in existing datasets. Although spectro-polarimetric datasets exist, these datasets have insufficient object diversity, limited illumination conditions, linear-only polarization data, and inadequate image count. Here, we introduce two spectro-polarimetric datasets: trichromatic Stokes images and hyperspectral Stokes images. These novel datasets encompass both linear and circular polarization; they introduce multiple spectral channels; and they feature a broad selection of real-world scenes. With our dataset in hand, we analyze the spectro-polarimetric image statistics, develop efficient representations of such high-dimensional data, and evaluate spectral dependency of shape-from-polarization methods. As such, the proposed dataset promises a foundation for data-driven spectro-polarimetric imaging and vision research. Dataset and code will be publicly available.

cs.CV

Recent developments of selective laser processes for wearable devices

Recently, the growing interest in wearable technology for personal healthcare and smart VR/AR applications newly imposed a need for development of facile fabrication method. Regarding the issue, laser has long been proposing original answers to such challenging technological demands with its remote, sterile, rapid, and site-selective processing characteristics for arbitrary materials. In this review, recent developments in relevant laser processes are summarized in two separate categories. Firstly, transformative approaches represented by laser-induced graphene (LIG) are introduced. Apart from design optimization and alteration of native substrate, latest advancements in the transformative approach now enable not only more complex material compositions but also multilayer device configurations by simultaneous transformation of heterogeneous precursor or sequential addition of functional layers coupled with other electronic elements. Besides, more conventional laser techniques such as ablation, sintering and synthesis are still accessible for enhancing the functionality of the entire system through expansion of applicable materials and adoption of new mechanisms. Various wearable device components developed through the corresponding laser processes are then organized with emphasis on chemical/physical sensors and energy devices. At the same time, special attention is given to the applications utilizing multiple laser sources or multiple laser processes, which pave the way towards all-laser fabrication of wearable devices.

cs.HC

Neural Spectro-polarimetric Fields

Modeling the spatial radiance distribution of light rays in a scene has been extensively explored for applications, including view synthesis. Spectrum and polarization, the wave properties of light, are often neglected due to their integration into three RGB spectral bands and their non-perceptibility to human vision. However, these properties are known to encompass substantial material and geometric information about a scene. Here, we propose to model spectro-polarimetric fields, the spatial Stokes-vector distribution of any light ray at an arbitrary wavelength. We present Neural Spectro-polarimetric Fields (NeSpoF), a neural representation that models the physically-valid Stokes vector at given continuous variables of position, direction, and wavelength. NeSpoF manages inherently noisy raw measurements, showcases memory efficiency, and preserves physically vital signals - factors that are crucial for representing the high-dimensional signal of a spectro-polarimetric field. To validate NeSpoF, we introduce the first multi-view hyperspectral-polarimetric image dataset, comprised of both synthetic and real-world scenes. These were captured using our compact hyperspectral-polarimetric imaging system, which has been calibrated for robustness against system imperfections. We demonstrate the capabilities of NeSpoF on diverse scenes.

cs.CV

On-Stack Two-Dimensional Conversion of MoS2 into MoO3

Chemical transformation of existing two-dimensional (2D) materials can be crucial in further expanding the 2D crystal palette required to realize various functional heterostructures. In this work, we demonstrate a 2D 'on-stack' chemical conversion of single-layer crystalline MoS2 into MoO3 with a precise layer control that enables truly 2D MoO3 and MoO3/MoS2 heterostructures. To minimize perturbation of the 2D morphology, a nonthermal oxidation using O2 plasma was employed. The early stage of the reaction was characterized by a defect-induced Raman peak, drastic quenching of photoluminescence (PL) signals and sub-nm protrusions in atomic force microscopy images. As the reaction proceeded from the uppermost layer to the buried layers, PL and optical second harmonic generation signals showed characteristic modulations revealing a layer-by-layer conversion. The plasma-generated 2D oxides, confirmed as MoO3 by x-ray photoelectron spectroscopy, were found to be amorphous but extremely flat with a surface roughness of 0.18 nm, comparable to that of 1L MoS2. The rate of oxidation quantified by Raman spectroscopy decreased very rapidly for buried sulfide layers due to protection by the surface 2D oxides, exhibiting a pseudo-self-limiting behavior. As exemplified in this work, various on-stack chemical transformations can be applied to other 2D materials in forming otherwise unobtainable materials and complex heterostructures, thus expanding the palette of 2D material building blocks.

cond-mat.mtrl-sci

Characterizations of individual mouse red blood cells parasitized by Babesia microti using 3-D holographic microscopy

Babesia microti causes emergency human babesiosis. However, little is known about the alterations in B. microti invaded red blood cells (Bm-RBCs) at the individual cell level. Through quantitative phase imaging techniques based on laser interferometry, we present the simultaneous measurements of structural, chemical, and mechanical modifications in individual mouse Bm-RBCs. 3-D refractive index maps of individual RBCs and in situ parasite vacuoles are imaged, from which total contents and concentration of dry mass are also precisely quantified. In addition, we examine the dynamic membrane fluctuation of Bm-RBCs, which provide information on cell membrane deformability.

physics.bio-ph