arXiv subjects

Xinyue Ma

Publications and source records attributed to Xinyue Ma.

16 recordsLinked to original sources

arXiv2026

Constraining the presence of exotrojans in hot Jupiter systems using TTV observations from TESS

Co-orbital bodies (Trojans) share a 1:1 mean-motion resonance with a planet. Although Trojans are common in the Solar System, none has yet been confirmed in an exoplanetary system. Hot Jupiters are not expected to retain primordial co-orbitals efficiently, but their deep and frequent transits make them favorable targets for observational constraints using transit timing variations (TTVs). As part of the ExoEcho project, we analyze TESS photometry for 260 confirmed hot Jupiters with published RV-based masses to search for TTV signals compatible with Trojan companions. We derive transit times and compare the observed residuals with co-orbital models computed with REBOUND N-body simulations. Accounting for the degeneracy between Trojan mass and libration amplitude, we place upper mass limits on possible companions over a range of typical libration amplitudes. For a representative libration amplitude of 15 deg, we rule out exotrojans more massive than 1 Earth mass in 130 systems, corresponding to about 50% of the sample. A more conservative chi-square analysis that incorporates observational uncertainties raises this threshold to 3 Earth masses. We further combine these limits with dynamical-stability constraints for the 1:1 resonance to exclude unstable configurations. Our results provide population-level constraints on massive exotrojans in short-period systems and establish a framework for future high-precision searches with missions such as PLATO and ET (Earth 2.0).

astro-ph.EP↗

arXiv2026

Bidirectional Chinese and English Passive Sentences Dataset for Machine Translation

Machine Translation (MT) evaluation has gone beyond metrics, towards more specific linguistic phenomena. Regarding English-Chinese language pairs, passive sentences are constructed and distributed differently due to language variation, thus need special attention in MT. This paper proposes a bidirectional multi-domain dataset of passive sentences, extracted from five Chinese-English parallel corpora and annotated automatically with structure labels according to human translation, and a test set with manually verified annotation. The dataset consists of 73,965 parallel sentence pairs (2,358,731 English words, 3,498,229 Chinese characters). We evaluate two state-of-the-art open-source MT systems with our dataset, and four commercial models with the test set. The results show that, unlike humans, models are more influenced by the voice of the source text rather than the general voice usage of the source language, and therefore tend to maintain the passive voice when translating a passive in either direction. However, models demonstrate some knowledge of the low frequency and predominantly negative context of Chinese passives, leading to higher voice consistency with human translators in English-to-Chinese translation than in Chinese-to-English translation. Commercial NMT models scored higher in metric evaluations, but LLMs showed a better ability to use diverse alternative translations. Datasets and annotation script will be shared upon request.

cs.CL↗

arXiv2026

OrbitFlow: SLO-Aware Long-Context LLM Serving with Fine-Grained KV Cache Reconfiguration

Serving long-context LLMs is challenging because request lengths and batch composition vary during token generation, causing the memory footprint to fluctuate significantly at runtime. Offloading KV caches to host memory limits effective memory usage, but existing static and predetermined offloading strategies cannot adapt to the rapidly shifting memory demands of long-context serving. This often leads to excessive CPU-to-GPU KV transfers that translate into latency spikes and frequent SLO violations. To address these challenges, we introduce OrbitFlow, a fine-grained and adaptive KV cache management system that meets latency SLOs in long-context LLM serving. OrbitFlow employs a lightweight ILP solver to decide which layers' KV caches to retain on the GPU for each request, within memory capacity constraints. It continuously refines KV placements based on runtime feedback when the active plan becomes suboptimal during token generation. Under heavy load, OrbitFlow invokes a fallback mechanism to temporarily defer in-flight requests with large memory footprints, preserving overall SLO attainment. Our experiments demonstrate that OrbitFlow improves SLO attainment for TPOT and TBT by up to 66% and 48%, respectively, while reducing the 95th percentile latency by 38% and achieving up to 3.3x higher throughput compared to existing offloading methods.

cs.AI↗

arXiv2026

Evidence for a Nonzero Eccentricity Superpuff Exoplanet WASP-107 b Using JWST Occultation Observation

WASP-107~b is an extremely low-density super-puff exoplanet whose inflated radius and evidence of strong internal heating make it a key target for understanding planetary structure and evolution. Its orbital eccentricity is a critical parameter for testing mechanisms such as tidal heating and high-eccentricity migration, yet previous measurements have remained inconclusive. Due to the large radial velocity jitter caused by stellar activity, and the presence of at least one additional planet in the system, previous radial velocity measurements could not robustly determine the eccentricity of WASP-107~b. Here we combine the new JWST secondary eclipse data with transit timing data from HST, TESS, and JWST to measure the eccentricity of WASP-107~b. Our joint analysis shows that WASP-107~b has an eccentricity of $0.09\pm0.02$, a mass of $0.096\pm0.005 \, M_J$, and an orbital period of $5.721487\pm0.000001$~days. We find the $99.7\%$ lower limit of the eccentricity is about 0.04. These new measurements are consistent with the scenario in which WASP-107~b is in the final stage of high-eccentricity migration. Preliminary estimate shows that eccentricity-driven tidal dissipation can provide a significant contribution to the energy required to sustain the observed radius inflation of WASP-107~b. Our results establish the dynamical status of one of the most intriguing low-density exoplanets known, and offer new insights into its formation and evolution history.

astro-ph.EP↗

arXiv2025

BeetleFlow: An Integrative Deep Learning Pipeline for Beetle Image Processing

In entomology and ecology research, biologists often need to collect a large number of insects, among which beetles are the most common species. A common practice for biologists to organize beetles is to place them on trays and take a picture of each tray. Given the images of thousands of such trays, it is important to have an automated pipeline to process the large-scale data for further research. Therefore, we develop a 3-stage pipeline to detect all the beetles on each tray, sort and crop the image of each beetle, and do morphological segmentation on the cropped beetles. For detection, we design an iterative process utilizing a transformer-based open-vocabulary object detector and a vision-language model. For segmentation, we manually labeled 670 beetle images and fine-tuned two variants of a transformer-based segmentation model to achieve fine-grained segmentation of beetles with relatively high accuracy. The pipeline integrates multiple deep learning methods and is specialized for beetle image processing, which can greatly improve the efficiency to process large-scale beetle data and accelerate biological research.

cs.CV↗

arXiv2025

BioCAP: Exploiting Synthetic Captions Beyond Labels in Biological Foundation Models

This work investigates descriptive captions as an additional source of supervision for biological multimodal foundation models. Images and captions can be viewed as complementary samples from the latent morphospace of a species, each capturing certain biological traits. Incorporating captions during training encourages alignment with this shared latent structure, emphasizing potentially diagnostic characters while suppressing spurious correlations. The main challenge, however, lies in obtaining faithful, instance-specific captions at scale. This requirement has limited the utilization of natural language supervision in organismal biology compared with many other scientific domains. We complement this gap by generating synthetic captions with multimodal large language models (MLLMs), guided by Wikipedia-derived visual information and taxon-tailored format examples. These domain-specific contexts help reduce hallucination and yield accurate, instance-based descriptive captions. Using these captions, we train BioCAP (i.e., BioCLIP with Captions), a biological foundation model that captures rich semantics and achieves strong performance in species classification and text-image retrieval. These results demonstrate the value of descriptive captions beyond labels in bridging biological images with multimodal foundation models.

cs.CV↗

arXiv2025

Semantic Prosody in Machine Translation: the English-Chinese Case of Passive Structures

Semantic prosody is a collocational meaning formed through the co-occurrence of a linguistic unit and a consistent series of collocates, which should be treated separately from semantic meaning. Since words that are literal translations of each other may have different semantic prosody, more attention should be paid to this linguistic property to generate accurate translations. However, current machine translation models cannot handle this problem. To bridge the gap, we propose an approach to teach machine translation models about semantic prosody of a specific structure. We focus on Chinese BEI passives and create a dataset of English-Chinese sentence pairs with the purpose of demonstrating the negative semantic prosody of BEI passives. Then we fine-tune OPUS-MT, NLLB-600M and mBART50 models with our dataset for the English-Chinese translation task. Our results show that fine-tuned MT models perform better on using BEI passives for translating unfavourable content and avoid using it for neutral and favourable content. Also, in NLLB-600M, which is a multilingual model, this knowledge of semantic prosody can be transferred from English-Chinese translation to other language pairs, such as Spanish-Chinese.

cs.CL↗

arXiv2025

Exoplanet Ephemerides Change Observations (ExoEcho). II. Transit timing variation analysis of Brown Dwarfs around Solar-type Stars

Transit timing variation (TTV) is a useful tool for studying the orbital properties of transiting objects. However, few TTV studies have been done on transiting brown dwarfs (BDs) around solar-type stars. Here we study the long-term TTV of a population of close BD companions around solar-type stars using TESS data. We use the measured orbital period change rate to constrain the tidal interaction strength between the host star and the BD companion and put limits on the destruction timescale of these transiting BDs. However, we find no statistically significant evidence of orbital decay or expansion in our sample based on the current data. This may be due to either poor observational data or inherently weak tidal dissipation. We then perform simulations to investigate future observation strategies for detecting orbital decay of transiting BDs, which show NGTS-7A b, TOI-263~b and LP 261-75 b are the most promising targets in the next few years. Our study demonstrates the potential of TTV technique to probe the formation and evolution of close BD companions around solar-type stars.

astro-ph.EP↗

arXiv2025

HST/WFC3 Constraints on the Abundances of OH and FeH in the Atmosphere of the Ultra-Hot Neptune LTT-9779 b

Planets residing within the hot-Neptune Desert are rare, and studying their atmospheres can provide valuable insights into their formation and evolutionary processes. We present the atmospheric characterization of the first known ultra-hot Neptune, LTT-9779 b, using transmission spectroscopic observations obtained with the HST/WFC3 G141 and G102 grisms. Using the Iraclis pipeline and TauREx3 retrieval code, we find that LTT-9779 b likely possesses a H/He-dominated primary atmosphere with an opaque aerosol layer and the pure cloudy, flat-line model is rejected with approximately 2.7-$\sigma$ confidence. Although we do not find conclusive evidence supporting the presence of any molecular species, we place 95% confidence level upper limits on the volume mixing ratios (VMRs) of hydroxyl radical (OH) and iron hydride (FeH) at $7.18\times10^{-2}$ and $1.52\times10^{-8}$, respectively. Notably, the retrieval results are inconsistent with predictions from equilibrium chemistry models, which favor higher $\rm H_2O$ abundances over OH. This discrepancy suggests that disequilibrium processes, such as photochemistry or vertical mixing, may have altered the atmospheric composition. Comparisons between HST, Spitzer and JWST data reveal no evidence of temporal variations in the atmospheric composition of the terminator region. Our results highlight the need for higher-resolution spectroscopy and secondary eclipse observations to resolve LTT-9779 b's temperature-pressure (T-P) profile and chemical inventory definitively.

astro-ph.EP↗

arXiv2025

Exoplanet Ephemerides Change Observations (ExoEcho). I. Transit Timing Analysis of Thirty-Seven Exoplanets using HST/WFC3 Data

The ExoEcho project is designed to study the photodynamics of exoplanets by leveraging high-precision transit timing data from ground- and space-based telescopes. Some exoplanets are experiencing orbital decay, and transit timing variation (TTV) is a useful technique to study their orbital period variations. In this study, we have obtained transit middle-time data from the Hubble Space Telescope (HST) observations for 37 short-period exoplanets, most of which are hot Jupiters. To search for potential long- and short-term orbital period variations within the sample, we conduct TTV model fitting using both linear and quadratic ephemeris models. Our analysis identifies two hot Jupiters experiencing strong periodic decays. Given the old age of the host stars of the hot Jupiter population, our findings call for a scenario where HJs are continuously being destructed and created. Our study demonstrates the importance of incorporating high-precision transit timing data to TTV study in the future.

astro-ph.EP↗

arXiv2024

Calibration of 3D Single-pixel Imaging Systems with a Calibration Field

3D single-pixel imaging (SPI) is a promising imaging technique that can be ffexibly applied to various wavebands. The main challenge in 3D SPI is that the calibration usually requires a large number of standard points as references, which are tricky to capture using single-pixel detectors. Conventional solutions involve sophisticated device deployment and cumbersome operations, resulting in hundreds of images needed for calibration. In our work, we construct a Calibration Field (CaliF) to efffciently generate the standard points from one single image. A high accuracy of the CaliF is guaranteed by the technique of deep learning and digital twin. We perform experiments with our new method to verify its validity and accuracy. We believe our work holds great potential in 3D SPI systems or even general imaging systems.

eess.IV↗

arXiv2024

Constraining the Presence of Companion Planets in Hot Jupiter Planetary System Using TTV Observation from TESS

The presence of another planetary companion in a transiting exoplanet system can impact its transit light curve, leading to sinusoidal transit timing variations (TTV). By utilizing both $\chi^2$ and RMS analysis, we have combined the TESS observation data with an N-body simulation to investigate the existence of an additional planet in the system and put a limit on its mass. We have developed CMAT, an efficient and user-friendly tool for fitting transit light curves and calculating TTV with a theoretical period, based on which we can give a limit on its hidden companion's mass. We use 260 hot Jupiter systems from the complete TESS data set to demonstrate the use of CMAT. Our findings indicate that, for most systems, the upper mass limit of a companion planet can be restricted to several Jupiter masses. This constraint becomes stronger near resonance orbits, such as the 1:2, 2:1, 3:1, and 4:1 mean motion resonance, where the limit is reduced to several Earth masses. These findings align with previous studies suggesting that a lack of companion planets with resonance in hot Jupiter systems could potentially support the high eccentricity migration theory. Additionally, we observed that the choice between $\chi^2$ or {root mean square (RMS)} method does not significantly affect the upper limit on companion mass; however, $\chi^2$ analysis may result in weaker restrictions but is statistically more robust compared to RMS analysis in most cases.

astro-ph.EP↗

arXiv2024

REP: Resource-Efficient Prompting for Rehearsal-Free Continual Learning

Recent rehearsal-free continual learning (CL) methods guided by prompts achieve strong performance on vision tasks with non-stationary data but remain resource-intensive, hindering real-world edge deployment. We introduce resource-efficient prompting (REP), which improves the computational and memory efficiency of prompt-based rehearsal-free continual learning methods while minimizing accuracy trade-offs. Our approach employs swift prompt selection to refine input data using a carefully provisioned model and introduces adaptive token merging (AToM) and adaptive layer dropping (ALD) for efficient prompt updates. AToM and ALD selectively skip data and model layers while preserving task-specific features during the learning of new tasks. Extensive experiments on multiple image classification datasets demonstrate REP's superior resource efficiency over state-of-the-art rehearsal-free CL methods.

cs.LG↗

arXiv2023

Cost-effective On-device Continual Learning over Memory Hierarchy with Miro

Continual learning (CL) trains NN models incrementally from a continuous stream of tasks. To remember previously learned knowledge, prior studies store old samples over a memory hierarchy and replay them when new tasks arrive. Edge devices that adopt CL to preserve data privacy are typically energy-sensitive and thus require high model accuracy while not compromising energy efficiency, i.e., cost-effectiveness. Our work is the first to explore the design space of hierarchical memory replay-based CL to gain insights into achieving cost-effectiveness on edge devices. We present Miro, a novel system runtime that carefully integrates our insights into the CL framework by enabling it to dynamically configure the CL system based on resource states for the best cost-effectiveness. To reach this goal, Miro also performs online profiling on parameters with clear accuracy-energy trade-offs and adapts to optimal values with low overhead. Extensive evaluations show that Miro significantly outperforms baseline systems we build for comparison, consistently achieving higher cost-effectiveness.

cs.LG↗

arXiv2022

THUEE system description for NIST 2020 SRE CTS challenge

This paper presents the system description of the THUEE team for the NIST 2020 Speaker Recognition Evaluation (SRE) conversational telephone speech (CTS) challenge. The subsystems including ResNet74, ResNet152, and RepVGG-B2 are developed as speaker embedding extractors in this evaluation. We used combined AM-Softmax and AAM-Softmax based loss functions, namely CM-Softmax. We adopted a two-staged training strategy to further improve system performance. We fused all individual systems as our final submission. Our approach leads to excellent performance and ranks 1st in the challenge.

cs.SD↗

arXiv2022

3D Single-pixel imaging with active sampling patterns and learning based reconstruction

Single-pixel imaging (SPI) is significant for applications constrained by transmission bandwidth or lighting band, where 3D SPI can be further realized through capturing signals carrying depth. Sampling strategy and reconstruction algorithm are the key issues of SPI. Traditionally, random patterns are often adopted for sampling, but this blindly passive strategy requires a high sampling rate, and even so, it is difficult to develop a reconstruction algorithm that can maintain higher accuracy and robustness. In this paper, an active strategy is proposed to perform sampling with targeted scanning by designed patterns, from which the spatial information can be easily reordered well. Then, deep learning methods are introduced further to achieve 3D reconstruction, and the ability of deep learning to reconstruct desired information under low sampling rates are analyzed. Abundant experiments verify that our method improves the precision of SPI even if the sampling rate is very low, which has the potential to be extended flexibly in similar systems according to practical needs.

eess.IV↗