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Dong-Jin Kim

Publications and source records attributed to Dong-Jin Kim.

At least 19 recordsLinked to original sources
arXiv2026

Two Isolated Microlensing Events Near the Upper Shore of Einstein Desert

The Einstein desert is a deficit in the angular Einstein-radius ($θ_{\rm E}$) distribution of isolated objects over the range $9 {\rm μas} < θ_{\rm E}<26 {\rm μas}$. Although this interval contained no events when the desert was first identified, several subsequent detections have fallen within it, raising questions about its detailed structure and requiring a larger detection sample. In this paper, we report the observations and analyses of two microlensing events possibly caused by isolated giant planets or brown dwarfs whose $ θ_{\rm E}$ lie near the upper shore of the desert. MOA-2021-BLG-145 has $ θ_{\rm E} = 23.1\pm2.0 ~{\rm μas}$, placing it just inside the upper boundary, and KMT-2026-BLG-0357 has $ θ_{\rm E} = 36.5\pm 3.7~{\rm μas}$, placing it above the desert. We also compare the $ θ_{\rm E}$ distributions of isolated objects and bound planetary events. The bound population shows no corresponding deficit over the same range, suggesting that the Einstein desert may be associated with the formation or subsequent evolution of the isolated population. Furthermore, some FFPs may lie above the upper shore of the Einstein desert, indicating that a more complete understanding of the FFP population requires direct lens-mass measurements.

astro-ph.EP↗
arXiv2026

Beyond Pairwise Repulsion: Collective Diversity via Determinant Maximization in Diffusion Sampling

Strong guidance in text-to-image (T2I) diffusion models concentrates sampling toward high-density modes of the conditional distribution, collapsing independently sampled noise vectors onto nearly identical visual prototypes. This limits utility for tasks that demand distributional breadth, most critically synthetic data augmentation. Diversity, however, is a collective property of the whole batch: a set can preserve every pairwise distance yet still collapse onto a low-dimensional subspace. Existing sum-of-pairwise noise-optimization and repulsion objectives respond only weakly to this higher-order failure. We propose DetNO (Determinant Noise Optimization), which formulates diverse generation as RKHS volume maximization on the initial noise, maximizing the log-determinant of an RBF Gram matrix over one-step Tweedie predictions. This set-level functional equals the squared batch volume; its repulsion is strongest when the batch is most collapsed and self-attenuates as diversity is achieved. An anchor-based fidelity term keeps the optimized noises near plausible regions, and Lagrangian relaxation gives a two-term objective with a single hyperparameter $λ$ governing the diversity-quality trade-off, without training or sampler modification. Across three backbones (SD1.5, SDXL, SD3), DetNO achieves leading intra-batch diversity in VendiScore and Mean Self-Similarity, and a downstream few-shot classification experiment confirms that broader mode coverage brings statistically significant accuracy gains for synthetic data augmentation in the low-shot regime. Fixing the pipeline and varying only the batch objective, both RBF-based aggregators outperform InfoNCE, and the log-determinant attains the best downstream accuracy on both benchmarks. Its diversity advantage over InfoNCE widens as the batch grows. Code is available at https://github.com/mobled37/DetNO.

cs.CV↗
arXiv2026

Not Just a Subject: Capturing Adaptive Scene-Specific Variance for Visual Storytelling

Recent advancements in diffusion models have significantly improved text-to-image generation, enabling their application to visual storytelling, where coherent image sequences are generated from narrative prompts. However, existing methods primarily focus on identity preservation and often fail to adapt to diverse scene variations, resulting in semantic misalignment and structural inflexibility. We propose EOS-Story, a training-free framework that harmonizes identity consistency with scene-specific adaptation across text and vision spaces. In the text space, we decouple the narrative into identity and scene sub-prompts to prevent information dilution, but this leaves the scene without access to appearance cues. To bridge this gap, we introduce Cross-Contextual Bridging, which softly injects a phrase-level appearance residual into the scene's embedding. In the vision space, we find that scale mismatch between identity and scene subjects causes a few identity tokens to be repeatedly transferred, producing structural artifacts. We address this with Adaptive Identity Preservation, which anchors identity features at the scene-specific scale (Identity Anchoring) and integrates them via Identity-Aware Self-Attention. To evaluate performance under varied spatial compositions, we extend the Consistory+ benchmark with diverse framing scenarios (Consistory+_+). Extensive experiments show that EOS-Story achieves competitive or superior performance on both benchmarks.

cs.CV↗
arXiv2026

Which Tokens to Merge? Diffusion Dynamics for Efficient Image Generation

Token merging has emerged as an effective training-free strategy for accelerating diffusion models by reducing redundant token computation while minimizing generation degradation. A key challenge is determining which tokens can be safely merged and which should be preserved for subsequent computation. Existing method addresses this by preserving prompt-aligned foreground regions, thereby protecting semantically relevant structures. However, this text-relevance criterion overlooks background objects, local details that are not explicitly mentioned in the prompt, leading to degraded structural coherence. In this work, we propose Dynamics-aware Token Merging (DaTMe), a training-free framework that grounds token merging in the underlying diffusion dynamics. Our key insight is that token importance should reflect whether a token remains unresolved during denoising and whether it carries structural information. To this end, DaTMe constructs a dynamics- aware importance map from the Tweedie denoised estimate. The map combines a temporal signal, measuring inter-step changes in the predicted clean image, with a structural signal, capturing local high-frequency content such as boundaries and fine details. Using this map, DaTMe adaptively assigns tokens into merging roles under a given compression ratio: important tokens are preserved as anchors, while tokens that are both temporally stabilized and structurally homogeneous are selected as safe merge candidates. Experiments on PixArt-a and FLUX demonstrate that DaTMe maintains visual fidelity across the entire image, highlighting diffusion dynamics as an effective token-level merging decision in efficient generation. Our code is available at https://github.com/SeungJuCha/DaTMe.

cs.CV↗
arXiv2026

OGLE-2016-BLG-0523: A Low-mass Brown Dwarf or super-Jupiter in a $>100$ au Orbit

To search for very wide-orbit binary-lens events, we cross-match microlensing events detected by OGLE-IV and KMTNet between 2011 and 2024. After removing contaminants from variable stars, we identify OGLE-2016-BLG-0523 as a microlensing event showing two short-lived bumps in its light curve, with the two separated by 8.36 yr. We investigate three scenarios to explain the two bumps, including a binary-lens single-source (2L1S), a single-lens binary-source (1L2S), and two unrelated single-lens single-source events (2$\times$1L1S). The 1L2S interpretation is excluded due to its poorer fit to the data, while the 2$\times$1L1S scenario is disfavored by the low event rate, unphysical total source flux, and unphysical color for one of the two putative sources. For the surviving 2L1S interpretation, the Einstein timescales of the two bumps are $8.343 \pm 0.076$ days and $3.231 \pm 0.047$ days, respectively, implying a binary mass ratio of $q = 0.15$. A Bayesian analysis indicates that the primary lens is most likely a low-mass M dwarf, while the companion is probably a low-mass brown dwarf or super-Jupiter. The inferred projected separation is about 450 au, making the companion the widest low-mass object discovered via microlensing to date. Our discovery highlights both the promise and challenges of identifying very wide, low-mass companions through microlensing. Although upcoming facilities such as Roman and Earth 2.0 space telescopes will improve sensitivity to such events, overcoming degeneracies and distinguishing them from variable phenomena will remain essential for building a robust statistical sample.

astro-ph.EP↗
arXiv2026

Two Low-Mass-Ratio Microlensing Planets from High-Magnification Events: KMT-2021-BLG-0247 and MOA-2023-BLG-169

We present an analysis of two planetary microlensing events, KMT-2021-BLG-0247 and MOA-2023-BLG-169, both of which exhibit high magnifications and low planet--host mass ratios, but with markedly different levels of parameter constraint. For KMT-2021-BLG-0247, the finite-source effect and microlens parallax are both clearly detected, leading to unusually tight constraints on the physical properties of the lens system. The host mass and lens distance are approximately $M_{\rm L}=0.9\pm0.1\,M_\odot$ and $D_{\rm L}=6.7^{+1.0}_{-0.3}\,\mathrm{kpc}$, respectively, and the planet mass is $M_{\rm p}=41\pm5\,M_\oplus$. The projected planet--host separations are $a_\perp=3.4^{+0.7}_{-0.3}\,\mathrm{au}$ and $3.0^{+0.6}_{-0.3}\,\mathrm{au}$ for the wide and close solutions, respectively. In contrast, MOA-2023-BLG-169 involves an extremely faint source, with $I_{S,{\rm OGLE}}=26.73$, such that the light curve permits a broad family of strongly correlated solutions. We therefore construct the physical-parameter likelihood using approximate invariant combinations of the light-curve parameters and supplement it with post-event Euclid/VIS imaging from the Euclid Q2 Galactic Bulge Survey (Beaulieu et al. 2026). The Euclid data reveal a component at the event position with ${\rm VIS}_{\rm AB}=23.05\pm0.09\,{\rm mag}$. Interpreting this component as the combined light from the source and any luminous lens, the resulting posterior gives $M_{\rm L}=0.48^{+0.23}_{-0.17}\,M_\odot$, $D_{\rm L}=3.50^{+2.82}_{-1.20}\,\mathrm{kpc}$, $a_\perp=1.62^{+0.77}_{-0.43}\,\mathrm{au}$, and $M_{\rm p}=143^{+103}_{-63}\,M_\oplus$. MOA-2023-BLG-169 demonstrates that, for an extreme faint-source event, even the event timescale and angular Einstein radius can remain strongly dependent on the Galactic prior and independent flux constraints.

astro-ph.EP↗
arXiv2026

Testing KMTNet--PRIME Optical--Near-Infrared Source-Color Constraints in KMT-2024-BLG-0211 and KMT-2024-BLG-1522

We present analyses of two 2024 microlensing events, KMT-2024-BLG-0211 and KMT-2024-BLG-1522, jointly observed by KMTNet in the optical and PRIME in the near-infrared. For KMT-2024-BLG-0211, the KMTNet--PRIME $I-H$ color provides a useful constraint on the angular source radius for a short-timescale finite-source event with a giant source. The event is consistent with a low-mass stellar lens, although the weak parallax constraint leaves the lens mass and distance uncertain. For KMT-2024-BLG-1522, we compare the results obtained from $V-I$, $I-H$, $V-H$, and $J-H$ color constraints. The microlensing parameters are nearly identical among the four analyses, yielding a robust binary-lens solution with nearly equal masses. However, the inferred source properties and lens physical parameters depend on the adopted source color because the different color estimates imply different angular source radii. Comparing the $(V-I)_{\rm KMT}$ versus $(I-H)_{\rm KMT,PRIME}$ plane shows that the inferred source colors lie off empirical color--color relations but within the scatter of observed stars. The prevalence of such deviations should be tested with a larger sample of KMTNet--PRIME events and this specific case can be further tested with future adaptive-optics follow-up, which can directly measure the lens--source relative proper motion and lens flux.

astro-ph.GA↗
arXiv2026

Phonemizing User-Generated Text: A Benchmark, Taxonomy, and Compositional Approach

Text-to-speech systems increasingly process user-generated text (UGT) such as ppl and imo, whose pronunciation must be inferred from the canonical rather than surface form. We introduce UGTPhon, the first grapheme-to-phoneme (G2P) benchmark for UGT in English, Vietnamese, and Korean, together with an inference-grounded taxonomy for fine-grained diagnosis. Existing G2P models and frontier LLMs exhibit a systematic canonical-to-non-canonical performance gap, reaching up to 66.8 PER points. As a benchmark baseline, we propose a simple compositional G2P approach that incorporates canonical-form evidence through exact-match lookup and staged decoding. Across matched ByT5 and Qwen2.5-0.5B backbones, explicit canonical-form modeling consistently reduces non-canonical G2P errors. The 0.5B variant also performs competitively with much larger few-shot frontier LLMs, highlighting the benefit of explicitly modeling canonical-form inference for UGT phonemization.

cs.CL↗
arXiv2026

Mode Switching in Two Blue Large Amplitude Pulsators observed by OGLE, KMTNet and DREAMS

Blue large-amplitude pulsators (BLAPs) are rare, hot, short-period pulsating stars whose rapid oscillations provide a unique probe of stellar interiors and atmospheres. In this paper, we study two short-period BLAPs in the Galactic bulge, OGLE-BLAP-142 ($P \approx 6.6$ min) and OGLE-BLAP-148 ($P \approx 7.5$ min), by combining light curves from the OGLE, KMTNet, and DREAMS surveys, spanning 17 years with cadences ranging from minutes to hours to days. We perform Generalized Lomb-Scargle periodogram analyses of their light curves and identify, for each BLAP, three closely spaced pulsation modes separated by $\sim 1\%$. The dominant mode can switch within timescales of order a year, accompanied by a likely blueward color shift ($\sim 0.1$--$0.2$ mag). The yearly period excursions of the resolved mode families imply apparent $|\dot{P}/P|$ values of order $10^{-6}$--$10^{-4}\,\mathrm{yr^{-1}}$, large enough to mimic or exceed smooth evolutionary period changes. One mode family in OGLE-BLAP-148 shows a coherent decade-long drift at the $\sim10^{-5}\,\mathrm{yr^{-1}}$ level, but its failure to extrapolate to the earliest and latest epochs suggests a transient mode-family drift rather than secular evolution. Such close-spaced multiple pulsations and mode switching may be common among BLAPs with periods shorter than 10 min, and their physical origin remains unclear.

astro-ph.SR↗
arXiv2026

KMT-2026-BLG-0083L: A Two-Jovian-Planet System Orbiting an M Dwarf Discovered by Microlensing

We present the analysis of the microlensing event KMT-2026-BLG-0083, which was independently detected by the KMTNet, OGLE, and PRIME surveys and also monitored by the DREAMS survey. The combined data provide dense coverage of two distinct short-duration anomalies in the light curve that cannot be reproduced by a standard binary-lens model. Independent analyses of the two anomalies indicate that each is produced by a planetary companion to the lens, motivating a triple-lens interpretation. The modeling yields two pairs of degenerate solutions arising from the well-known inner--outer degeneracy, with each pair exhibiting two local solutions depending on whether the source passes above or below the distant planetary companion. The preferred model indicates two giant planets with mass ratios $q_2=(5.25\pm 0.08)\times 10^{-3}$ and $q_3=(3.04\pm 0.24)\times10^{-3}$ orbiting a common host. Bayesian analysis indicates that the host is an M-dwarf star with a mass of $0.48^{+0.36}_{-0.28}~M_\odot$, hosting two giant planets with masses of $2.65^{+1.96}_{-1.55}~M_{\rm J}$ and $1.54^{+1.14}_{-0.90}~M_{\rm J}$. The projected planet--host separations are $10.6^{+1.7}_{-2.2}$~au and $1.7^{+0.3}_{-0.3}$~au, placing the inner planet near the host's snow line and the outer planet at a substantially larger separation. Thus, KMT-2026-BLG-0083L becomes the seventh confirmed multiple-planet system discovered through gravitational microlensing, providing another example of a cold giant planetary system orbiting a subsolar-mass star.

astro-ph.EP↗
arXiv2026

Seeing Before Synthesizing: VLM-Guided Transition Event Discovery for Weakly-Supervised Dense Video Captioning

Weakly-Supervised Dense Video Captioning aims to localize and describe multiple events in untrimmed videos given only an ordered set of event-level captions per video. Recent work synthesizes auxiliary transition captions via LLM to provide additional vision-language alignment, but these captions lack visual grounding and are rigidly assigned to every inter-event gap at a fixed location and duration. To address these, we propose Seeing Before Synthesizing (SBS), a framework that adaptively provides visually grounded linguistic guidance only where warranted. Leveraging a VLM, we generate frame-level narratives for the inter-event gaps and detect transitions from the semantic variation across them. For identified transitions, we then refine inter-event temporal masks by blending the temporal midpoint with the semantic change point and selecting the width that maximizes vision-language alignment. Experiments on ActivityNet Captions and YouCook2 demonstrate state-of-the-art performance in both captioning and localization.

cs.CV↗
arXiv2026

Systematic KMTNet Planetary Anomaly Search. XIII. Complete Sample of 2021 Prime Field Planets

The Systematic KMTNet Planetary Anomaly Search series was conducted using the KMTNet data archived from $2016$ to $2019$. From this first phase of the series, we reported a total of $50$ planetary systems hidden in the data archive, which represent about $35\%$ of the total microlensing planets discovered from $2016$ to $2019$, demonstrating that this semi-machine-based search is a crucial channel for building a complete microlensing planet sample. We continue this series for $2021$ and beyond to expand the microlensing planet sample. In this work for the $2021$ KMTNet high-cadence fields (Prime fields), we find seven hidden planetary systems and three planet candidates. These new planets represent about $33\%$ of the total microlensing planets discovered within the Prime fields observed during the $2021$ bulge season. While the by-eye search is the primary channel for detecting microlensing planets (i.e., two-thirds of microlensing planet discoveries), this work clearly shows that a systematic search series is still necessary for constructing a complete microlensing planet sample. Such a sample is essential for conducting unbiased statistical studies of planet demographics in our Galaxy. Datasets for all the events used for analyses in this work are publicly available: doi:10.5281/zenodo.21472225.

astro-ph.EP↗
arXiv2026

KMT-2025-BLG-0975Lb and KMT-2025-BLG-1160Lb: Two Uranus-Mass Planets Beyond the Snow Line Discovered by Microlensing

We present the analysis of two planetary microlensing events, KMT-2025-BLG-0975 and KMT-2025-BLG-1160, discovered during the 2025 Galactic bulge microlensing season through high-cadence survey observations. In both events, short-duration anomalies near the peaks of the lensing light curves reveal the presence of planetary companions. Light-curve modeling yields planet-to-host mass ratios of $q = 8.6 \times 10^{-4}$ for KMT-2025-BLG-0975 and $1.3 \times 10^{-4}$ for KMT-2025-BLG-1160. For KMT-2025-BLG-0975, finite-source effects are detected, enabling a measurement of the angular Einstein radius, whereas only a lower limit on this quantity is obtained for KMT-2025-BLG-1160. We estimate the physical parameters of the lens systems through Bayesian analyses constrained by the measured microlensing observables. The results indicate that the planetary companions have masses of $M_{\rm p}=29.8^{+50.5}_{-16.0}~M_\oplus$ for KMT-2025-BLG-0975Lb and $25.4^{+15.5}_{-14.1}~M_\oplus$ for KMT-2025-BLG-1160Lb. Both planets have masses comparable to that of Uranus. The host stars are inferred to be a low-mass M dwarf with a mass of $M_{\rm h}=0.10^{+0.18}_{-0.06}~M_\odot$ for KMT-2025-BLG-0975L and a late K dwarf with a mass of $M_{\rm h}=0.58^{+0.35}_{-0.32}~M_\odot$ for KMT-2025-BLG-1160L. The projected planet--host separations are $a_\perp=0.81^{+0.10}_{-0.11}$~au for KMT-2025-BLG-0975Lb and $a_\perp=2.56^{+0.48}_{-0.71}$~au and $3.29^{+0.61}_{-0.92}$~au for the inner and wide solutions, respectively, of KMT-2025-BLG-1160Lb. In both systems, the planets are located beyond the expected snow-line distances of their hosts, placing them in the cold ice-giant regime.

astro-ph.EP↗
arXiv2026

KMT-2025-BLG-2093: Free-Floating Planet Candidate Near the Shore of the Einstein Desert

We analyze KMT-2025-BLG-2093, with angular Einstein radius $θ_{\rm E}=13.1\pm 2.8\,μ{\rm as}$, which makes it the second isolated microlens that lies in the ``Einstein Desert'' ($9\,μ{\rm as}<θ_{\rm E}<25\,μ{\rm as}$) between free-floating planets (FFPs) on one side and brown dwarfs and stars on the other. We discuss how its characteristics may give clues to future exploration of FFPs, especially in the era of satellite missions that have a major FFP focus, including Earth 2.0 and Roman.

astro-ph.EP↗
arXiv2026

Four Cold Giant Planets Discovered by High-Cadence Microlensing Surveys

We report the discovery of four cold giant planets identified through the analysis of microlensing events detected by high-cadence surveys: OGLE-2016-BLG-0261, KMT-2025-BLG-0026, KMT-2025-BLG-0030, and KMT-2025-BLG-2272. The planetary signals appear as short-duration anomalies in the light curves and are well described by binary-lens single-source models with mass ratios between the lens components of order $q \sim 10^{-3}$. Finite-source effects are securely measured in three out of four events, enabling determinations of the angular Einstein radius. A Bayesian analysis incorporating the measured event timescale and angular Einstein radius yields host masses of $\sim 0.07$--$0.6~M_\odot$ and companion masses of $\sim 0.2$--$2.5~M_{\rm J}$, confirming that all companions lie in the giant-planet regime. The projected separations are ~ 0.7--6 au, placing all planets at or beyond the snow lines of their host stars. The inferred lens distances span $\sim 6.6$--$7.9$ kpc, with all systems consistent with bulge lenses. These detections expand the sample of cold giant planets from homogeneous high-cadence surveys and highlight the sensitivity of microlensing to planetary systems beyond the snow line, providing further constraints on the occurrence and properties of giant planets around low-mass stars.

astro-ph.EP↗
arXiv2026

SIDA: Synthetic Image Driven Zero-shot Domain Adaptation

Zero-shot domain adaptation is a method for adapting a model to a target domain without utilizing target domain image data. To enable adaptation without target images, existing studies utilize CLIP's embedding space and text description to simulate target-like style features. Despite the previous achievements in zero-shot domain adaptation, we observe that these text-driven methods struggle to capture complex real-world variations and significantly increase adaptation time due to their alignment process. Instead of relying on text descriptions, we explore solutions leveraging image data, which provides diverse and more fine-grained style cues. In this work, we propose SIDA, a novel and efficient zero-shot domain adaptation method leveraging synthetic images. To generate synthetic images, we first create detailed, source-like images and apply image translation to reflect the style of the target domain. We then utilize the style features of these synthetic images as a proxy for the target domain. Based on these features, we introduce Domain Mix and Patch Style Transfer modules, which enable effective modeling of real-world variations. In particular, Domain Mix blends multiple styles to expand the intra-domain representations, and Patch Style Transfer assigns different styles to individual patches. We demonstrate the effectiveness of our method by showing state-of-the-art performance in diverse zero-shot adaptation scenarios, particularly in challenging domains. Moreover, our approach achieves high efficiency by significantly reducing the overall adaptation time.

cs.CV↗
arXiv2026

Searching for Extraterrestrial Intelligence with the SKA

The search for technosignatures (also known as the Search for Extraterrestrial Intelligence or SETI) depends critically on our ability to distinguish artificial signals from the rich complexity of natural astrophysical phenomena and radio frequency interference from anthropogenic emissions. As the search for technosignatures increasingly aligns with mainstream astrophysics, complementing the search for biosignatures, it demands not only sophisticated statistical and computational approaches, but also deep domain knowledge across the electromagnetic spectrum. The SKA will play a pivotal role in the next-generation of technosignature searches, providing an unprecedented combination of sensitivity, field of view, and spatial resolution over its wavelength range. Integrating wide-field, high-resolution observations with machine learning and multi-wavelength diagnostics will represent key steps forward. The SKA's singular capabilities will render it an indispensable instrument for the rapid identification and follow-up characterisation of promising technosignature candidates. In this chapter, we discuss the request for high temporal and spectral resolution data products with a main focus on frequency-domain SETI. Nevertheless, multiple SKA observing modes have the potential to substantially advance technosignature research.

astro-ph.IM↗
arXiv2026

Measuring Asteroid Rotation Periods Using the KMTNet Bulge Survey Data

Since 2015, the Korea Microlensing Telescope Network (KMTNet) has conducted high-cadence, near-continuous observations of the Galactic bulge for nearly nine months each year from three sites in Chile, South Africa, and Australia, and its wide field of view provides a unique opportunity to extract asteroid lightcurves from archival survey data. In this work, we performed photometric measurements of bright asteroids ($V< 20$~mag) identified within a one-square-degree field during the 2018 KMTNet bulge season. We derived reliable rotation periods for 96 asteroids, including 84 objects without previously published lightcurves. The reliable spin-rates of the asteroids in our sample are broadly consistent with those reported in the Asteroid Lightcurve Database. This archival mining approach can be readily extended to a much larger KMTNet footprint, and the existing $\sim12$~deg$^2$ high-cadence KMTNet dataset has the potential to yield reliable rotation periods (U $\geq 2+$) for more than 5,500 asteroids, substantially expanding the current database of asteroid rotational properties.

astro-ph.EP↗