arXiv subjects

Yudong Luo

Publications and source records attributed to Yudong Luo.

At least 19 recordsLinked to original sources

arXiv2026

RoboSynChallenge: Mastering Real-World Dexterity via Generalizing Synthesized Manipulation Skills

Achieving generalizable robotic manipulation remains a central challenge in embodied intelligence. Despite rapid advances in model architectures and learning algorithms, progress is often limited by the scarcity and narrow diversity of real-world data. The RoboSynChallenge competition introduces a unified benchmark to evaluate and advance the generalizability of manipulation policies across a spectrum of tasks, environments, and difficulty levels. To alleviate the shortage of realistic data, the challenge integrates large-scale synthetic data generation with standardized real-world robotic evaluation. Participants are encouraged to leverage synthesized state-action trials to improve general-purpose policy learning, while final assessments are conducted exclusively on unseen real-world manipulation environments. Baseline implementations, including Transformer-, Diffusion-, Vision-Language-Action, and World-Action-Model-based policies, are provided to ensure reproducibility and comparability. By coupling scalable simulation-based training with rigorous real-world validation, RoboSynChallenge aims to foster the development of broadly capable, data-efficient, and adaptable manipulation systems, thereby paving the way toward truly general robotic intelligence.

cs.RO↗

arXiv2026

ReflectWorld-MM: An Entity-Oriented Multimodal Memory System for Open-Ended Video Streams

Building assistants that can continually watch the world, remember what they see, and reason over their accumulated experience is a long-standing goal, and recently multimodal agents equipped with long-term memory over video streams have attracted increasing interest. Unfortunately, existing systems either keep their memory inside the model context or in a flat feature store, and organize it around frames rather than around the persistent entities a stream is really about, which confines them to bounded videos and weakens their ability to track who and what reappears over time. In this paper, we propose ReflectWorld-MM, an entity-oriented multimodal memory system for open-ended video streams. It consists of three parts. The first is a perception front-end that turns an audiovisual stream into entity-resolved observations under a bounded short-term memory. The second is a hierarchical long-term memory, grounded in human memory theory, that couples a multi-scale episodic memory, an evolving entity-centric semantic memory, and a procedural memory. The third is a complete realization, built for real-world operation, that ingests arbitrary streams and plugs into off-the-shelf assistants. Across six long-video and lifelong-memory benchmarks, ReflectWorld-MM achieves the best accuracy on all six, outperforming strong memory agents and a frontier model.

cs.CV↗

arXiv2026

Actor-Critic Algorithm for Dynamic Expectile and CVaR

Optimizing dynamic risk with stochastic policies is challenging in both policy updates and value learning. The former typically requires transition perturbation, while the latter may rely on model-based approaches. To address these challenges, we propose a surrogate policy gradient without transition perturbation under softmax policy parameterization. We further develop model-free value learning methods for dynamic expectile and conditional value-at-risk by leveraging elicitability. Finally, inspired by Expected SARSA and Expected Policy Gradient, a model-free off-policy actor-critic algorithm is constructed. Empirical results in domains with verifiable risk-averse behavior show that our algorithm can learn risk-averse policy and consistently outperforms other existing methods.

cs.LG↗

arXiv2026

TacticGen: Grounding Adaptable and Scalable Generation of Football Tactics

Success in association football relies on both individual skill and coordinated tactics. While recent advancements in spatio-temporal data and deep learning have enabled predictive analyses like trajectory forecasting, the development of tactical design remains limited. Bridging this gap is essential, as prediction reveals what is likely to occur, whereas tactic generation determines what should occur to achieve strategic objectives. In this work, we present TacticGen, a generative model for adaptable and scalable tactic generation. TacticGen formulates tactics as sequences of multi-agent movements and interactions conditioned on the game context. It employs a multi-agent diffusion transformer with agent-wise self-attention and context-aware cross-attention to capture cooperative and competitive dynamics among players and the ball. Trained with over 3.3 million events and 100 million tracking frames from top-tier leagues, TacticGen achieves state-of-the-art precision in predicting player trajectories. Building on it, TacticGen enables adaptable tactic generation tailored to diverse inference-time objectives through classifier guidance mechanism, specified via rules, natural language, or neural models. Its modeling performance is also inherently scalable. A case study with football experts confirms that TacticGen generates realistic, strategically valuable tactics, demonstrating its practical utility for tactical planning in professional football. The project page is available at: https://shengxu.net/TacticGen/.

cs.AI↗

arXiv2026

CREST: Constraint-Release Execution for Multi-Robot Warehouse Shelf Rearrangement

Double-Deck Multi-Agent Pickup and Delivery (DD-MAPD) models the multi-robot shelf rearrangement problem in automated warehouses. MAPF-DECOMP is a recent framework that first computes collision-free shelf trajectories with a MAPF solver and then assigns agents to execute them. While efficient, it enforces strict trajectory dependencies, often leading to poor execution quality due to idle agents and unnecessary shelf switching. We introduce CREST, a new execution framework that achieves more continuous shelf carrying by proactively releasing trajectory constraints during execution. Experiments on diverse warehouse layouts show that CREST consistently outperforms MAPF-DECOMP, reducing metrics related to agent travel, makespan, and shelf switching by up to 40.5\%, 33.3\%, and 44.4\%, respectively, with even greater benefits under lift/place overhead. These results underscore the importance of execution-aware constraint release for scalable warehouse rearrangement. Code and data are available at https://github.com/ChristinaTan0704/CREST.

cs.RO↗

arXiv2026

On the survival of strong nuggets in the early Universe

Strong nuggets with a baryon number of $A\sim 10^{10-30}$ could be able to survive from the cosmic separation of the QCD phases, provided the transition from strange quark matter to strangeon matter is accounted for, thereby evading evaporation in the early Universe. Such strangeon nuggets may serve as a dark matter candidate within particle standard model. We formulate the corresponding phase transition of cosmic strange matter, establishing a parameter space which reasonably accommodates observational constraints on the dark-to-luminous matter ratio and the mass-radius relation, as well as tidal deformability of compact objects.

hep-ph↗

arXiv2026

Boosting CVaR Policy Optimization with Quantile Gradients

Optimizing Conditional Value-at-risk (CVaR) using policy gradient (a.k.a CVaR-PG) faces significant challenges of sample inefficiency. This inefficiency stems from the fact that it focuses on tail-end performance and overlooks many sampled trajectories. We address this problem by augmenting CVaR with an expected quantile term. Quantile optimization admits a dynamic programming formulation that leverages all sampled data, thus improves sample efficiency. This does not alter the CVaR objective since CVaR corresponds to the expectation of quantile over the tail. Empirical results in domains with verifiable risk-averse behavior show that our algorithm within the Markovian policy class substantially improves upon CVaR-PG and consistently outperforms other existing methods.

cs.LG↗

arXiv2026

A compact object with a K type star companion in the solar neighborhood: a wide post common envelope binary with a white dwarf candidate

Post-common envelope binaries (PCEBs) consisting of a white dwarf (WD) plus a main-sequence (MS) star can constrain current prescriptions of common envelope evolution (CEE) and calibrate theoretical models of binary formation and evolution. Most PCEBs studied to date have typical orbital periods of hours to a few days and can be well explained by assuming inefficient CEE to expel the envelope. However, there are currently several systems with relatively wide orbital periods ($>$18 days). To explain these wide PCEBs, additional sources of energy have been suggested to be taken into account. Here, we present the discovery and observational characterization of a compact object ($M\,\geq\,0.58\,\rm M_{\odot}$) with a K-type star companion in the solar neighborhood ($d\sim 112$ pc) and an orbital period of $P_{\rm orb}\sim 14$ days. The compact object binary is likely to be a system consisting of a WD and a barium dwarf, making it the shortest-period barium star binary candidate. Such a system with an orbital period within the gap between tight and wide binaries provides a test of whether additional energy sources are required to explain its formation. Using binary evolution models, we investigate the evolutionary history of this wide PCEB system and find that the observed properties of this source can be explained without invoking any extra energy source.

astro-ph.SR↗

arXiv2025

Impact of experimental mass of $^{70}$Kr on the $^{68}$Se waiting-point in $rp$-process

The recent mass measurement of $^{70}$Kr using the $B\rho$-defined isochronous mass spectrometry yields a mass excess of $-41320(140)$ keV, indicating a 220-keV increase in binding energy compared to the AME2020 prediction. We utilize this experimental mass -- the last piece of information needed -- to model the potential waiting point $^{68}$Se in $rp$-process and quantitatively constrain the sequential $p$-capture reaction flow bypassing this waiting point. Our investigation shows that the more tightly bound nature of $^{70}$Kr enhances this reaction flow up to a factor of four. This enhancement reduces the effective half-life of $^{68}$Se. {A} one-zone X-ray burst model calculations reveal that the higher flow of $^{70}$Kr has distinct effects on the tail structure of light curve and the final SnSbTe abundances in the ashes due to a stronger $rp$-process heating.

nucl-th↗

arXiv2025

A Systematic Study of Magnetic Fields Impacts on Neutrino Transport in Core-Collapse Supernovae

We quantify the impact of strong magnetic fields (assuming $B=B_0\cdot r_0^3/r^3$ with $B_0\gtrsim 10^{16}$ G) on the neutrino transport in core-collapse supernovae (CCSNe). Magnetic fields quantize the momenta of electrons and positrons, resulting in an enhanced absorption cross section for low-energy neutrinos and suppressed chemical potentials for $e^\pm$. We include these changes in the M1 scheme for neutrino transport and perform 1-D CCSNe simulations with \texttt{GR1D}. The increased low-energy cross sections reduce the $\bar{\nu}_e$ mean energy $\langle E_{\bar\nu_e}\rangle$ while elevating the neutrino number luminosities $\mathcal{L_\nu}$ for both ${\nu}_e$ and $\bar{\nu}_e$ due to the lower energy weighted spectra. The reduction of chemical potential enhances the $\bar{\nu}_e$ emission while suppressing that of $\nu_e$, thereby driving an increase in the electron fraction behind the stalled shock at $\sim30$--$100$ km. This further amplifies $\langle E_{\nu_e}\rangle$ through an increased electron density. Consequently, magnetic fields amplify $L_{\nu_e}$ by increasing both $\mathcal{L}_{\nu_e}$ and $\langle E_{\nu_e}\rangle$ whereas for $\bar\nu_e$, the rise in $\mathcal{L}_{\bar\nu_e}$ is offset by a decreased $\langle E_{\bar\nu_e}\rangle$, leading to a minimal change in $L_{\bar\nu_e}$. A systematic parameter scan of dipole field configurations suggests that, for $r_0 > 30$ km, $\langle E_{\bar{\nu}_e} \rangle$ is significantly suppressed and $L_{\nu_e}$ is enhanced if $B_0 \geq {2.7} \times 10^{16}$ G. These magnetic effects become negligible for $B_0$ below $\sim {7.4} \times 10^{15}$ G.

astro-ph.HE↗

arXiv2025

High-Precision Measurement of D($\gamma$, $n$)$p$ Photodisintegration Reaction and Implications for Big-Bang Nucleosynthesis

We report on a high-precision measurement of the D($\gamma$,\,$n$)$p$ photodisintegration reaction at the newly commissioned Shanghai Laser Electron Gamma Source (SLEGS), employing a quasi-monochromatic $\gamma$-ray beam from Laser Compton Scattering. The cross sections were determined over $E_\gamma$=2.327--7.089 MeV, achieving up to a factor of 2.2 improvement in precision near the neutron separation threshold. Combined with previous data in a global Markov chain Monte Carlo (MCMC) analysis using dibaryon effective field theory, we obtained the unprecedentedly precise $p$($n$,\,$\gamma$)D cross sections and thermonuclear rate, with a precision up to $\approx$4 times higher than previous evaluations. Implemented in a standard Big-Bang Nucleosynthesis (BBN) framework, this new rate decreases uncertainty of the key cosmological parameter of baryon density $\Omega_b h^2$ by up to $\approx$16\% relative to the LUNA result. A residual $\approx$1.2$\sigma$ tension between $\Omega_b h^2$ constrained from primordial D/H observations and CMB measurements persists, highlighting the need for improved $dd$ reaction rates and offering potential hints of new physics beyond the standard model of cosmology.

nucl-ex↗

arXiv2025

New Determination of the $^{14}$C(n, $\gamma$)$^{15}$C Reaction Rate and Its Astrophysical Implications

We present a novel experiment to investigate the spectroscopic factor of the $^{15}$C ground state for the first time using single-neutron $removal$ transfer reactions on $^{15}$C. Two consistent spectroscopic factors were derived from the (p, d) and (d, t) reactions, which were subsequently used to deduce the $^{14}$C(n, $\gamma$)$^{15}$C reaction cross section and the corresponding stellar reaction rate. A typical cross section of (3.89 $\pm$ 0.76) $\mu$b is determined at $E_\mathrm{_{c.m.}}$ = 23.3 keV. At the temperature range of 0.01-4 GK, our new reaction rate is 2.4-3.7 times higher than that of the first direct measurement and 20\%-25\% lower than that of the most recent direct measurement, respectively. Moreover, it is interesting that we can associate a long-standing nuclear structure issue, i.e., the so-called ``quenching'' effect, with this astrophysically relevant reaction. Finally, motivated by astrophysical interests of this reaction decades ago, implications of our new rate on several astrophysical problems are evaluated using state-of-the-art theoretical models. Our calculations demonstrate that the abundances of $^{14}$N and $^{15}$N can be enhanced in the inner regions of asymptotic giant branch (AGB) stars, though with minimal impact on the chemical compositions of the interstellar medium. In the inhomogeneous Big Bang nucleosynthesis, the updated reaction rate can lead to a $\sim 20\%$ variation in the final yields of $^{15}$N in neutron rich regions. For the $r$-process in the core-collapse supernovae, a slight difference of $\sim 0.2\%$ in the final abundances of heavy elements with $A > 90$ can be found by using our new rate.

nucl-ex↗

arXiv2025

Measures of Variability for Risk-averse Policy Gradient

Risk-averse reinforcement learning (RARL) is critical for decision-making under uncertainty, which is especially valuable in high-stake applications. However, most existing works focus on risk measures, e.g., conditional value-at-risk (CVaR), while measures of variability remain underexplored. In this paper, we comprehensively study nine common measures of variability, namely Variance, Gini Deviation, Mean Deviation, Mean-Median Deviation, Standard Deviation, Inter-Quantile Range, CVaR Deviation, Semi_Variance, and Semi_Standard Deviation. Among them, four metrics have not been previously studied in RARL. We derive policy gradient formulas for these unstudied metrics, improve gradient estimation for Gini Deviation, analyze their gradient properties, and incorporate them with the REINFORCE and PPO frameworks to penalize the dispersion of returns. Our empirical study reveals that variance-based metrics lead to unstable policy updates. In contrast, CVaR Deviation and Gini Deviation show consistent performance across different randomness and evaluation domains, achieving high returns while effectively learning risk-averse policies. Mean Deviation and Semi_Standard Deviation are also competitive across different scenarios. This work provides a comprehensive overview of variability measures in RARL, offering practical insights for risk-aware decision-making and guiding future research on risk metrics and RARL algorithms.

cs.LG↗

arXiv2025

Exploring the Neutrino Mass Hierarchy from Isotopic Ratios of Supernova Nucleosynthesis Products in Presolar Grains

We study the nucleosynthesis in a core-collapse supernova model including newly calculated neutrino-induced reaction rates with both collective and Mikheyev-Smirnov-Wolfenstein (MSW) neutrino-flavor oscillations considered. We show that the measurement of a pair of $^{11}$B/$^{10}$B and $^{138}$La/$^{139}$La or $^6$Li/$^7$Li and $^{138}$La/$^{139}$La in presolar grains that are inferred to have originated from core-collapse supernovae could constrain the neutrino mass hierarchy. The new shell-model and the model of quasi-particle random phase approximation in the estimate of three important neutrino-induced reactions, $\nu+^{16}$O, $\nu+^{20}$Ne, and $\nu+^{138}$Ba are applied in our reaction network. The new rates decrease the calculated $^{7}$Li/$^{6}$Li ratio by a factor of five compared with the previous study. More interestingly, these new rates result in a clear separation of the isotopic ratio of $^{11}$B/$^{10}$B between normal and inverted mass hierarchies in the O/Ne, O/C, and C/He layers where $^{138}$La abundance depends strongly on the mass hierarchy. In these layers, the sensitivity of the calculated abundances of $^{10,11}$B and $^{6,7}$Li to the nuclear reaction uncertainties is also tiny. Therefore, we propose that the $^{11}$B/$^{10}$B vs. $^{138}$La/$^{139}$La and $^6$Li/$^7$Li vs. $^{138}$La/$^{139}$La in type X silicon carbide grains sampled material from C/He layer can be used as a new probe to constrain the neutrino mass hierarchy.

astro-ph.SR↗

arXiv2024

Photo-nuclear reaction rates of $^{157,159}$Ho and $^{163,165}$Tm and their impact in the $\gamma$--process

Reliable photo-nuclear reaction rates at the stellar conditions are essential to understand the origin of the heavy stable neutron-deficient isotopes between $^{74}$Se and $^{196}$Hg-p-nuclei, however, many reaction rates of relevance still have to rely on the Hauser-Feshbach model due to rare experimental progress. One such case is in the mass range of 160 for Dy, Er, Ho and Tm isotopes. In this work we attempt to constrain the Hauser-Feshbach model in the TALYS package by reproducing the available experimental data of $^{160}$Dy($p,\gamma$)$^{161}$Ho and $^{162}$Er($p,\gamma$)$^{163}$Tm in the $A\sim 160$ mass region, and examine the effects of level density, gamma strength function and the optical model potential. The constrained model then allows us to calculate the reaction rates of $^{157, 159}$Ho($\gamma$, $p$) and $^{163,165}$Tm($\gamma$, $p$) for the $\gamma$-process nucleosynthesis in carbon-deflagration SNe Ia model. Our recommended rates differ from the JINA REACLIB by more than 1 order of magnitude in the temperature range of 2-3 GK. This results in the changes of final abundance of $p$-nuclei in the $A\sim 160$ mass range by -5.5-3\% from those with JINA, which means that the ($\gamma$, $p$) reactions uncertainty is not predominant for the synthesis of these nuclei.

astro-ph.SR↗

arXiv2024

Reevaluation of Large Neighborhood Search for MAPF: Findings and Opportunities

Multi-Agent Path Finding (MAPF) aims to arrange collision-free goal-reaching paths for a group of agents. Anytime MAPF solvers based on large neighborhood search (LNS) have gained prominence recently due to their flexibility and scalability, leading to a surge of methods, especially those leveraging machine learning, to enhance neighborhood selection. However, several pitfalls exist and hinder a comprehensive evaluation of these new methods, which mainly include: 1) Lower than actual or incorrect baseline performance; 2) Lack of a unified evaluation setting and criterion; 3) Lack of a codebase or executable model for supervised learning methods. To address these challenges, we introduce a unified evaluation framework, implement prior methods, and conduct an extensive comparison of prominent methods. Our evaluation reveals that rule-based heuristics serve as strong baselines, while current learning-based methods show no clear advantage on time efficiency or improvement capacity. Our extensive analysis also opens up new research opportunities for improving MAPF-LNS, such as targeting high-delayed agents, applying contextual algorithms, optimizing replan order and neighborhood size, where machine learning can potentially be integrated. Code and data are available at https://github.com/ChristinaTan0704/mapf-lns-unified.

cs.RO↗

arXiv2024

Strong magnetic field inside degenerate relativistic plasma and the impacts on the neutrino transport in Core-Collapse Supernovae

We study the impacts of magnetic field on the neutrino transport inside core-collapse supernovae (CCSNe). Magnetic field quantizes the momentum of electrons and positrons, resulting in the modification of weak-interaction cross sections and the chemical potentials of electrons and positrons. We include these changes in the leakage scheme of neutrino transport and perform 1D CCSN simulations with GR1D, assuming the postbounce magnetic field strength of $10^{16-17}$ G. The results show that the neutrino opacities are enhanced due to the amplified interaction rates, resulting in a larger neutrinosphere. This further reduces the peak value of neutrino luminosities and their decay rates since neutrinos stay longer inside the neutrinosphere. Meanwhile, the neutrino mean energies are smaller shortly after bounce and reach their peak values at later times. As these neutrino properties are crucial in subsequent nucleosynthesis processes, including the $\nu$p-process, $\nu$-process, and $r$-process, our findings suggest that the magnetic field may leave discernible marks on the abundance pattern of nucleosynthesis in CCSN.

astro-ph.HE↗

arXiv2024

Radial and Non-Radial Oscillations of Inverted Hybrid Stars

We study the radial and non-radial oscillations of Cross stars (CrSs), i.e., stars with a quark matter crust and a hadronic matter core in an inverted order compared to conventional hybrid stars. We draw comparisons of their oscillation modes with those of neutron stars, quark stars, and conventional hybrid stars. We find that the stellar stability analysis from the fundamental mode of radial oscillations, and the $g$, $f$ modes of non-radial oscillations are quite similar to those of conventional hybrid stars. However, due to the inverted stellar structure, the first non-radial $p$ mode of CrSs behaves in an inverted way and sits in a higher frequency domain compared to that of conventional hybrid stars. These results provide a direct way to discriminate CrSs from other types of compact stars via gravitational-wave probes. Specifically, compact stars emitting $g$-mode gravitational waves within the $0.5$-$1$ kHz range should be CrSs or conventional hybrid stars rather than neutron stars or pure quark stars, and a further GW detection of the first $p$ mode above 8 kHz or an identification of a decreasing trend of frequencies versus star masses associated with it will help identify the compact object to be a CrS rather than a conventional hybrid star.

astro-ph.HE↗