arXiv subjects

Xinyi Hong

Publications and source records attributed to Xinyi Hong.

9 recordsLinked to original sources

arXiv2026

Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Prediction

Large language model (LLM) agents increasingly rely on invoking external tools to complete real-world tasks. Tool retrieval, which selects a small task-relevant subset from a library of thousands of tools before the agent acts, has therefore become a critical component of LLM agent pipelines. However, existing retrievers either score each tool in isolation or assemble the tool set sequentially, so the joint utility of a candidate set is never evaluated as a whole. In this paper, we propose HYSET, short for HYperedge-based SEt-level Tool retrieval. Our contributions are threefold: (i) we formulate tool retrieval as query-conditioned hyperedge prediction on a tool co-invocation hypergraph, under which the tool set itself becomes the unit of scoring and most existing retrieval paradigms reduce to restricted instances; (ii) we capture size-dependent tool compatibility through cardinality-specific interactions; and (iii) we design HYSET as a pre-selection module requiring no modification to the downstream agent. Experiments on ToolBench demonstrate that HYSET consistently outperforms state-of-the-art baselines in both tool retrieval performance and end-to-end task success. Beyond the in-domain setting, HYSET further supports zero-shot/few-shot transfer, generalizing to held-out tools/categories and unseen domains with minimal supervision.

cs.LG↗

arXiv2026

HYVINT: Intensity-Driven Hypergraph Generation with Variational Embeddings

Hypergraphs provide a principled framework for modeling polyadic interactions, with applications in recommendation systems, social networks, and molecular modeling. Hypergraph generation remains challenging because incidence structures are discrete, sparse, and governed by heterogeneous higher-order interactions. Existing generators often rely on implicit latent spaces or continuous incidence decoders, which provide limited mechanistic interpretation of how node-hyperedge incidences arise. To address these limitations, we propose HYVINT, an intensity-driven hypergraph generative framework. Our key innovations are twofold: (i) we develop an intensity-driven incidence formation mechanism for hypergraphs that links latent interaction strength to binary incidence, and (ii) we derive a tractable lower-bound variational estimator for learning latent representations. We provide generation error bounds with asymptotic convergence rates and empirically show that HYVINT achieves strong fidelity while maintaining substantial novelty and diversity on synthetic and real-world hypergraphs.

stat.ML↗

arXiv2026

SN 2023fyq: direct detection of a Type Ibn supernova progenitor and its multi-wavelength environmental constraints

Context. Type Ibn supernovae (SNe) are characterized by narrow helium emission lines arising from ejecta-circumstellar medium interaction, yet their progenitors remain debated, with both massive Wolf-Rayet stars and low-mass helium stars in binaries proposed. Aims. We aim to directly identify the progenitor of the Type Ibn SN 2023fyq and to characterize its environment in order to constrain the progenitor's nature and evolutionary channel. Methods. We search for the SN progenitor based on pre-explosion and late-time HST and JWST images and derive its properties by fitting the spectral energy distribution. We investigate the SN environment by probing the stars, dust, ionized gas and molecular gas with a multi-wavelength dataset including HST and JWST imaging, VLT/MUSE integral-field-unit spectroscopy and ALMA CO (2--1) radio interferometry. Results. We discover a pre-explosion source at the SN position, which is consistent with a hot ($T>$15000 K) and luminous (log($L$/$L_\odot$) $\gtrsim$ 5.5) SN progenitor and a possible host star cluster. The progenitor is confirmed to have disappeared after explosion. Analysis of the SN environment implies that the progenitor likely has an age of log($t$/yr) = 7.1--7.2. These phenomena disfavor a very massive single-star progenitor and instead support a binary scenario involving a low-mass helium star and a compact object; the observed progenitor emission likely arises from binary interaction that began at least $\sim$12 yr before the explosion. Conclusions. SN 2023fyq is the first Type Ibn SN with a directly detected progenitor and a possible host star cluster. It adds to the diversity of Type Ibn SNe in terms of their progenitor channels and mass-loss mechanisms.

astro-ph.SR↗

arXiv2026

SN 2024abfl: A Low-Luminosity Type IIP Supernova in NGC 2146 from a Low-Mass Red Supergiant Progenitor

Type IIP supernovae (SNe IIP) exhibit a significant diversity in their explosion properties, yet the physical mechanisms driving this diversity remain unknown. In this work, we present photometric and spectroscopic observations of SN 2024abfl, a SN IIP in NGC 2146 with a directly detected red supergiant (RSG) progenitor. We find it has a low plateau luminosity ($M_V \sim -15$ mag) and a relatively long plateau length ($\sim 126.5$ days). By fitting a semi-analytical model, we estimated a $^{56}$Ni mass of $\sim 0.009 M_\odot$, an initial kinetic energy of $\sim 0.42$ foe, an initial thermal energy of $\sim 0.03$ foe and an ejecta mass of $\sim 8.3 M_\odot$. The spectral evolution of SN 2024abfl is similar to those of other SNe IIP, except for much lower ejecta velocities at similar epochs. At later epochs, we find a relatively high-velocity H$\alpha$ absorption feature at $\sim -4000$ km s$^{-1}$, possibly due to a fast-moving plume of matter in the inner ejecta, and two emission features at $\pm 2000$ km s$^{-1}$, possibly caused by CSM interaction. We estimate the progenitor mass to be $\le 15 M_\odot$ based on nebular spectra. We conclude that SN 2024abfl is a low-luminosity SN IIP originating from a low-mass RSG progenitor.

astro-ph.HE↗

arXiv2026

Direct Detection of Type II-P Supernova Progenitors with the $\textit{Euclid}$ and CSST Surveys

Identifying and characterizing supernova (SN) progenitor stars remains a central yet difficult goal in SN research, limited by archival images lacking sufficient depth or spatial resolution and circumstellar dust biasing intrinsic parameter estimates. This field will be revolutionized by $\textit{Euclid}$ and the upcoming Chinese Space-station Survey Telescope (CSST), which conduct deep, wide-field, high-resolution and multi-band imaging surveys. We evaluate their detection capability by comparing model magnitudes of RSG progenitors with detection limits, finding their optical and near-infrared filters highly effective. Monte-Carlo simulations predict that completed $\textit{Euclid}$ and CSST surveys will enable $\lesssim$13 (or 24) progenitor detections per year within the mass range of 8--16 (or 8--25)\,$M_\odot$, an order of magnitude higher than the current detection rate of $\sim$1 per year (primarily based on HST). With the circumstellar dust, the emerging spectral energy distribution (SED) of the SN progenitor is mainly affected by the optical depth and is almost independent of dust temperature in their survey filters. Mock tests demonstrate that the progenitor mass and dust optical depth can be derived simultaneously by fitting the observed SED over 11 survey filters while fixing dust temperature to a typical value. $\textit{Euclid}$ and CSST will significantly enlarge the sample of direct progenitor detections with accurate mass measurements, crucial for resolving the long-standing RSG problem.

astro-ph.SR↗

arXiv2025

A late-time view of the progenitor candidates of the Type II-P SN 2009ib and SN 2012ec

The progenitors of Type II-P supernovae (SNe) are generally considered to be red supergiants; however, the so-called "red supergiant problem" indicates that a deeper investigation into the progenitors of this class of SNe is necessary. SN 2009ib and SN 2012ec are two Type II-P SNe for which progenitor candidates have been identified in pre-explosion images. In this work, we use new, late-time Hubble Space Telescope observations to search for the disappearance of these two candidates and confirm their nature. In the case of SN 2009ib, the late-time high-resolution imaging reveals that the progenitor candidate is in fact a blend of multiple unresolved stars. Subsequent difference imaging shows no significant change in brightness at the SN's position even years after the explosion. These findings indicate that the flux from the previously identified source is dominated by unresolved field stars, with little to no contribution from the genuine progenitor. In the case of SN 2012ec, a comparison of pre-explosion and late-time images reveals that the progenitor candidate faded by about 0.6 mag in the F814W band seven years after the explosion, confirming the disappearance of the progenitor.

astro-ph.SR↗

arXiv2024

Exclusion of a direct progenitor detection for the Type Ic SN 2017ein based on late-time observations

To date, SN 2017ein is the only Type Ic supernova with a directly identified progenitor candidate. This candidate points to a very massive ($>$45 $M_\odot$) Wolf-Rayet progenitor, but its disappearance after the explosion of SN 2017ein remains unconfirmed. In this work, we revisit SN 2017ein in late-time images acquired by the Hubble Space Telescope (HST) at 2.4--3.8 yrs after peak brightness. We find this source has not disappeared and its brightness and color remain almost the same as in the pre-explosion images. Thus, we conclude that the pre-explosion source is not the genuine progenitor of SN 2017ein. We exclude the possibility that it is a companion star of the progenitor, since it has a much lower extinction than SN 2017ein; its color is also inconsistent with a star cluster, indicated by the newly added magnitude limit in F336W, apart from F555W and F814W. We suggest, therefore, this source is an unrelated star in chance alignment with SN 2017ein. Based on the low ejecta mass, we propose that SN 2017ein is most likely originated from a moderately massive star with $M_{\rm ini}$ $\sim$ 8--20 $M_\odot$, stripped by binary interaction, rather than a very massive Wolf-Rayet progenitor.

astro-ph.HE↗

arXiv2024

A Multi-Agent Dual Dialogue System to Support Mental Health Care Providers

We introduce a general-purpose, human-in-the-loop dual dialogue system to support mental health care professionals. The system, co-designed with care providers, is conceptualized to assist them in interacting with care seekers rather than functioning as a fully automated dialogue system solution. The AI assistant within the system reduces the cognitive load of mental health care providers by proposing responses, analyzing conversations to extract pertinent themes, summarizing dialogues, and recommending localized relevant content and internet-based cognitive behavioral therapy exercises. These functionalities are achieved through a multi-agent system design, where each specialized, supportive agent is characterized by a large language model. In evaluating the multi-agent system, we focused specifically on the proposal of responses to emotionally distressed care seekers. We found that the proposed responses matched a reasonable human quality in demonstrating empathy, showing its appropriateness for augmenting the work of mental health care providers.

cs.HC↗

arXiv2024

Constraining the progenitor of the nearby Type II-P SN 2024ggi with environmental analysis

The progenitors of Type II-P supernovae (SN) have been confirmed to be red supergiants. However, the upper mass limit of the directly probed progenitors is much lower than that predicted by current theories, and the accurate determination of the progenitor masses is key to understand the final fate of massive stars. Located at a distance of only 6.72 Mpc, the Type II-P SN 2024ggi is one of the closest SN in the last decade. Previous studies have analyzed its progenitor by direct detection, but the derived progenitor mass may be influenced by the very uncertain circumstellar extinction and pulsational brightness variability. In this work, we try to constrain the progenitor mass with an environmental analysis based on images from the Hubble Space Telescope. We found that stars in the progenitor environment have a uniform spatial distribution without significant clumpiness, and we derived the star formation history of the environment with a hierarchical Bayesian method. The progenitor is associated with the youngest population in the SN environment with an age of log($t$/yr) = 7.41 (i.e. 25.7 Myr), which corresponds to an initial mass of $10.2^{+0.06}_{-0.09}$ $M_\odot$. Our work provides an independent measurement of the progenitor mass, which is not affected by circumstellar extinction and pulsational brightness variability.

astro-ph.SR↗