arXiv subjects

Xing Gao

Publications and source records attributed to Xing Gao.

At least 37 records · Page 2Linked to original sources

arXiv2026

InternVLA-A1.5: Unifying Understanding, Latent Foresight, and Action for Compositional Generalization

Unified models for robot manipulation aim to equip one policy with both the semantic priors of pretrained VLMs and the physical dynamics learned through future prediction. In practice, existing designs tend to erode the semantics of the pretrained backbone, suffer interference among heterogeneous objectives, and learn future prediction from scratch in pixel space, leaving the dynamics priors of pretrained video generators unexploited. We present InternVLA-A1.5, which builds the policy on a native VLM backbone that keeps training on VQA and subtask prediction, and attaches a lightweight unified expert for continuous action generation. Future prediction is recast as a latent-querying problem, where a small set of learnable foresight tokens condenses the task-relevant future into a compact latent code under the supervision of a frozen pretrained video generation model, so the policy inherits world-model dynamics priors without ever learning pixel-level generation. The video branch is discarded at inference, keeping real-time control. Pretrained on 1.2M robot episodes and 3M multimodal samples, InternVLA-A1.5 achieves the best overall results on all six simulation benchmarks. In the real world, the preserved semantics deliver the strongest compositional generalization on held-out instruction bindings, and the two designs together sustain long-horizon execution.

cs.RO↗

arXiv2026

Exact Signature Tail Asymptotics for Pure Rough Paths

We prove~\cite[Conjecture 2.12]{BGS20} on the signature tail asymptotics of pure rough paths and extend it to arbitrary reasonable tensor norms. In more details, let \[ \mathbf X_t=\exp(tl) \,\text{ with }\, l=l_1+\cdots+l_m\,\text{ and }\, l_r\in\mathcal L_r(V), \] be a pure $m$-rough path over a finite dimensional real or complex Banach space, and equip the tensor powers of $V$ with arbitrary reasonable tensor algebra norms. We prove that \[ \limsup_{n\to\infty}\left(\left(\frac{n}{m}\right)!\left\|π_n(\exp l)\right\|_n\right)^{m/n}=\|l_m\|_m . \] In particular, this identifies the signature tail with the local $m$-variation of the pure rough path. The upper bound was obtained in~\cite{BGS20}; the main contribution of the paper is the matching lower bound. Its proof is based on finite dimensional developments and a norming cyclic construction. For every top-level tensor $l_m$, we also build a contractive development in which $\|l_m\|_m$ appears as an eigenvalue at degree $m$.

math.PR↗

arXiv2026

A Low-Regularity Semigroup Sewing Lemma via Quotient Structures

We develop a low-regularity Sewing theory for the semigroup coboundary $\hatδ=δ-a$ associated with a strongly continuous semigroup $S$. Unlike the ordinary low-regularity Sewing problem, the semigroup setting has an intrinsic algebraic non-uniqueness below the threshold $1$, in the sense that solutions are canonical only modulo semigroup cocycles. Accordingly, the natural target is a quotient space rather than an increment space. We identify this quotient structure and construct the corresponding semigroup Sewing map. The construction uses a frozen terminal-time transform, which rewrites semigroup defects, for each terminal time, as ordinary low-regularity Sewing problems on a frozen simplex. This reduction, however, does not by itself produce a genuine semigroup increment; the main additional step is to prove that the frozen solution classes are compatible as the terminal time varies and hence assemble into a canonical quotient class for $\hatδ$. This yields canonical classes for $0<γ<1$, and at $γ=1$ under logarithmic control. We further provide a scale-dependent criterion for selecting genuine representatives, verified for heat semigroups on Sobolev scales through a parabolic Littlewood--Paley tail condition.

math.PR↗

arXiv2026

Infinitesimal Bialgebra on Planar Binary Trees

We construct a weight-zero infinitesimal bialgebra structure on the $\bk$-module spanned by planar binary trees, using the under product $\backslash$ of Aguiar--Sottileand a root-recursive coproduct $\DeltaLR$. We prove that $\DeltaLR$ is coassociative and satisfies the infinitesimal derivation rule with respect to $\backslash$, hence gives a unitary infinitesimal bialgebra distinct from the usual Loday--Ronco Hopf structure. We also obtain an elementary vertex-cut formula, establish freeness properties for unitary $(\backslash,\vee)$-algebras and unitary infinitesimal $(\backslash,\vee)$-bialgebras, and identify the construction with the infinitesimal coproduct transported from planar rooted forests.

math.CO↗

arXiv2026

Stability of nontrivial graph pairs

A graph pair $(Γ, Σ)$ is called stable if every automorphism of the direct product $Γ\timesΣ$ is induced componentwise by automorphisms of $Γ$ and $Σ$. A graph is twin-free if no two distinct vertices share the same neighbourhood in the graph. Two graphs $Γ$ and $Σ$ are coprime with respect to the direct product if there is no graph $Δ$ of order greater than $1$ such that $Γ\congΓ'\timesΔ$ and $Σ\congΣ'\timesΔ$ for some graphs $Γ'$ and $Σ'$. A graph pair $(Γ,Σ)$ is nontrivial if $Γ$ and $Σ$ are coprime connected twin-free graphs and exactly one of them is bipartite. In this paper, we prove that if $Γ$ is non-bipartite, stable, and factor-loopless, then each nontrivial graph pair $(Γ,Σ)$ is stable. This gives a partial answer to [Question~19, Qin, Xia and Zhou, Discrete Math., 113856, (2024)] and proves the factor-loopless case of [Conjecture~1.3, Wang, Qin and Xia, arXiv:2509.26170]. We also give affirmative answers to [Questions~3.5, 3.6, Gan, Liu and Xia, J. Combin. Theory Ser. B, 140--164, (2025)] and a negative answer to [Question~3.7, Gan, Liu and Xia, J. Combin. Theory Ser. B, 140--164, (2025)].

math.CO↗

arXiv2026

Ni-O hybridization-driven electronic reconstruction across the superconducting dome in an infinite-layer nickelate

Superconductivity in infinite-layer nickelates has drawn wide interest as a cuprate analogue, yet how the electronic structure evolves with hole doping remains unsettled. Here we map the doping- and temperature-dependent unoccupied states of the La-based infinite-layer nickelate La1-xCaxNiO2 using O K-edge and Ni L-edge x-ray absorption spectroscopy. Superconductivity occurs for 0.18<=x<=0.27. Near x~0.20-0.23, low-energy spectral weight redistributes: Ni3d-dominated states decrease while O2p-hybridized states increase, indicating an orbital-selective crossover in Ni-O covalency. This crossover coincides with a sign reversal of the Hall coefficient and precedes the reduction of the superconducting critical temperature at higher doping. By directly linking transport anomalies and the superconducting dome to a measurable Ni-O orbital reorganization, our results provide a key step toward a unified, orbital-resolved phase diagram for infinite-layer nickelates and a practical route to engineer superconductivity via hybridization control.

cond-mat.supr-con↗

arXiv2026

High-field-stabilized reentrant superconductivity in infinite-layer nickelate thin films

Magnetic fields typically suppress superconductivity through Pauli and orbital limiting effects. However, there are rare instances of magnetic-field-induced superconductivity, as seen in Chevrel phase compounds [1], organic conductors [2], uranium-based heavy-fermion systems [3, 4], and moire graphene [5], though these materials possess inherently low superconducting transition temperatures (Tc). Here, we demonstrate high field-stabilized superconductivity in a class of materials with a significantly higher Tc (up to 40 K): the infinite-layer nickelates [6]. Both low-field and high-field superconducting states can be plausibly explained by a compensation mechanism akin to the Jaccarino-Peter effect. These findings demonstrate the possibility of achieving substantially enhanced upper critical fields in high-temperature superconductors.

cond-mat.supr-con↗

arXiv2026

Hole-doped superconductivity above 100 K in infinite-layer cuprate thin films

Since the discovery of superconductivity in (La,Ba)2CuO2 (Ref.~\cite{bednorz1986possible}), a broad family of structurally distinct cuprate superconductors has been proposed or engineered to elucidate the physics of high-temperature superconductivity~\cite{chu2015hole,plakida2010high}. Among them, the infinite-layer cuprate has the simplest structure, consisting only of the essential ingredients for superconductivity: CuO$_2$ square planes separated by spacer ions~\cite{siegrist1988parent}. Despite being proposed nearly 40 years ago, the hole-doped superconductivity via chemical substitution in this compound has not yet been achieved, a fundamental open question in the field. Here, we report the observation of superconductivity in the hole-doped infinite-layer cuprate thin film. Measurements of resistivity and magnetic-field response in Sr1-xRbxCuO2 single-crystal thin films show superconducting transitions with a high onset temperature of 100 K. Hole doping is achieved via the synergistic effect of rubidium substitution and apical oxygen incorporation, as evidenced by structural analysis and transport measurements. As the parent structure of the cuprate family~\cite{chu2015hole}, hole-doped infinite-layer cuprate provides a unique platform for revisiting key puzzles in cuprate superconductors~\cite{keimer2015quantum,tsuei2000pairing,armitage2010progress,dagotto1994correlated}, including strange metal~\cite{proust2019remarkable,taillefer2010scattering} and electron-hole symmetry~\cite{tohyama2004asymmetry,segawa2010zero,lee2014asymmetry}, while bridging to cuprate-nickelate symmetry~\cite{li2019superconductivity,zeng2022superconductivity,chow2025bulk,lechermann2020late}.

cond-mat.supr-con↗

arXiv2026

Universal limit theorem for rough differential equations driven by controlled rough paths

We study rough differential equations driven by controlled rough paths in the level-$2$ regime $1/3<α\le 1/2$. Given a reference rough path $\mathbf X=(1,X,\mathbb X)$ and an $\mathbf X$-controlled driver $\mathbf Z=(Z,Z')$, we first give a point-removal construction of the controlled rough integral $ \int_s^t Y_r\,d\mathbf Z_r $ and prove the corresponding remainder estimates. We then establish local and global well-posedness for the controlled-driven rough differential equation $ dY_t=F(Y_t)\,d\mathbf Z_t. $ A key structural result is the canonical lift of the controlled driver: from the controlled data $(\mathbf X,\mathbf Z)$ we construct a level-$2$ rough path \[ \widehat{\mathbf Z}=(1,Z,\mathbb Z), \qquad \mathbb Z_{s,t}:=\int_s^t Z_{s,u}\otimes dZ_u, \] and show that the controlled-driven equation is equivalent to the classical rough differential equation driven by $\widehat{\mathbf Z}$. This equivalence shows compatibility with classical rough path theory, while the controlled formulation keeps track of the dependence of the effective driver $Z$ on the reference rough path $\X$. Finally, we prove a universal limit theorem for the solution map $ (\mathbf X,\mathbf Z,Y_0)\longmapsto Y, $ which gives stability with respect to perturbations of the initial condition, the reference rough path, and the controlled driver. These results provide a natural framework for layered rough systems and equations driven by transformed or previously evolved rough signals.

math.PR↗

arXiv2026

Fertility fibres and coproduct coefficients in the LOT Hopf algebra

We study fibres of the fertility map $Φ$ from decorated rooted trees to decorated multi-index monomials. For a multi-index $\mathbf{k}$ of weight $-1$, the fibre $\mathcal F_{\mathbf{k}}=\{\,t:Φ(t)=\xx^{\mathbf{k}}\,\}$ consists of all rooted trees with decoration--fertility profile $\mathbf{k}$. We consider its ordinary cardinality $F_{\mathbf{k}}$, its symmetry-weighted cardinality $W_{\mathbf{k}}$, and the coefficient mass $J_{\mathbf{k}}$ appearing in the tree expansion of the transposed embedding $\jmath$. We obtain an explicit formula and a functional equation for the weighted counts, and an exact multiset recursion together with a cycle-index functional equation for the ordinary counts. We also introduce coefficient generating functions for the lowering derivation $\bar\partial$, derive recursive and transport-array formulas for the corresponding coefficients, and use them to refine the admissible-cut formula for the coproduct in the LOT Hopf algebra.

math.CO↗

arXiv2026

Jump Itô-type formula with arbitrary regularity

We establish an Itô-type formula for finite $p$-variation paths with jumps for arbitrary $p\geq 1$. The formula is stated in a fully pathwise form and separates the reduced rough integral from explicit left- and right-jump correction terms. In the càdlàg case, only the left-jump correction remains, while in the continuous case, both jump correction terms vanish and the formula recovers the corresponding continuous arbitrary-regularity change-of-variable formula. The proof is based on the reduced rough path framework and a refinement Riemann-Stieltjes convergence criterion adapted to discontinuous paths. This approach allows us to handle the higher-order Taylor expansions required for large values of $p$ and to control the interaction between rough increments and discrete jumps. As applications, we derive Itô-type formulas for stochastic processes whose sample paths have finite $p$-variation, including pure-jump models and mixed fractional Brownian-jump signals. The latter class includes cases with Hurst parameter $H\leq 1/3$, which fall outside the regime $2\leq p<3$. We also obtain chain-rule identities for nonlinear observables of càdlàg finite-$p$-variation solutions of random differential equations with jumps, together with a pathwise log-wealth decomposition.

math.PR↗

arXiv2026

LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token Speculation

Speculative decoding (SD), where a small draft model is employed to propose draft tokens in advance and then the target model validates them in parallel, has emerged as a promising technique for LLM inference acceleration. Many endeavors to improve SD are to eliminate the need for a draft model and generate draft tokens in a retrieval-based manner in order to further alleviate the drafting overhead and significantly reduce the difficulty in deployment and applications. However, retrieval-based SD relies on a matching paradigm to retrieval the most relevant reference as the draft tokens, where these methods often fail to find matched and accurate draft tokens. To address this challenge, we propose LogitSpec to effectively expand the retrieval range and find the most relevant reference as drafts. Our LogitSpec is motivated by the observation that the logit of the last token can not only predict the next token, but also speculate the next next token. Specifically, LogitSpec generates draft tokens in two steps: (1) utilizing the last logit to speculate the next next token; (2) retrieving relevant reference for both the next token and the next next token. LogitSpec is training-free and plug-and-play, which can be easily integrated into existing LLM inference frameworks. Extensive experiments on a wide range of text generation benchmarks demonstrate that LogitSpec can achieve up to 2.61 $\times$ speedup and 3.28 mean accepted tokens per decoding step. Our code is available at https://github.com/smart-lty/LogitSpec.

cs.CL↗

arXiv2026

A First Look at the Security Issues in the Model Context Protocol Ecosystem

The Model Context Protocol (MCP) has emerged as a standard for connecting large language models (LLMs) with external tools. However, this MCP ecosystem introduces new security risks across hosts, servers, and registries. In this paper, we present the first cross-entity security study of MCP under a two-stage attack surface. At the registry-level, weak vetting and ownership checks allow adversarial or hijacked servers to enter hosts. After integration, attacker-controlled tool metadata can shape LLM reasoning and induce attacker-intended operations, which hosts execute without independent verification. Code-level vulnerabilities (e.g., code injection) are not required but can amplify attacker-controlled parameters into exploitation. We analyze 67,057 servers across six public registries and identify widespread conditions enabling server hijacking and invocation manipulation. We further implement MCPInspect, a pre-integration analysis tool that detects misleading tool metadata and exploitable code vulnerabilities, identifying 833 vulnerable servers and 18 with suspicious descriptions.

cs.CR↗

arXiv2026

InfBaGel: Human-Object-Scene Interaction Generation with Dynamic Perception and Iterative Refinement

Human-object-scene interactions (HOSI) generation has broad applications in embodied AI, simulation, and animation. Unlike human-object interaction (HOI) and human-scene interaction (HSI), HOSI generation requires reasoning over dynamic object-scene changes, yet suffers from limited annotated data. To address these issues, we propose a coarse-to-fine instruction-conditioned interaction generation framework that is explicitly aligned with the iterative denoising process of a consistency model. In particular, we adopt a dynamic perception strategy that leverages trajectories from the preceding refinement to update scene context and condition subsequent refinement at each denoising step of consistency model, yielding consistent interactions. To further reduce physical artifacts, we introduce a bump-aware guidance that mitigates collisions and penetrations during sampling without requiring fine-grained scene geometry, enabling real-time generation. To overcome data scarcity, we design a hybrid training startegy that synthesizes pseudo-HOSI samples by injecting voxelized scene occupancy into HOI datasets and jointly trains with high-fidelity HSI data, allowing interaction learning while preserving realistic scene awareness. Extensive experiments demonstrate that our method achieves state-of-the-art performance in both HOSI and HOI generation, and strong generalization to unseen scenes. Project page: https://yudezou.github.io/InfBaGel-page/

cs.CV↗

arXiv2026

Rough Burger-like SPDEs

We study a class of nonlinear Burgers-type stochastic partial differential equations driven by additive space-time white noise in one spatial dimension. Building on the rough path framework initiated by Hairer, which provides a pathwise solution theory under spatial regularity $α\in(\frac{1}{3}, \frac{1}{2})$, we extend this approach to the full subcritical regime $α\in(0, \frac{1}{2})$. Our main contribution is the establishment of pathwise existence and uniqueness of mild (equivalently, weak) solutions when the spatial regularity of the solution lies strictly below the classical rough path threshold. This is achieved through refined estimates for controlled rough paths, including a new upper bound for compositions with smooth functions and a scaling analysis for rough integrals against heat kernels. In particular, we extend and sharpen key analytic estimates originating from Hairer's work, incorporating refined scaling arguments that are effective in the low-regularity regime. As a result, our framework significantly enlarges the class of Burgers-type SPDEs that can be treated pathwise using rough path techniques.

math.PR↗

arXiv2025

Net Magnetization and Inhomogeneous Magnetic Order in a High-Tc Nickelate Superconductor

High-temperature and high-magnetic-field-induced re-entrant superconductivity has been discovered in the infinite-layer nickelate $\mathrm{Sm_{1-x-y} Eu_x Ca_y Ni O_2}$ (SECNO). Infinite-layer nickelates are the closest known analogues of high-$\mathrm{T}_c$ cuprate superconductors, yet they host distinct magnetic ground states. Using low-energy muon spin relaxation and polarized neutron reflectometry, we reveal the magnetic order in SECNO. We find that magnetic freezing occurs at a higher-temperature than in other nickelate compounds, and that a substantial net magnetization of 55 $\,\mathrm{kA}\,\mathrm{m}^{-1}$ $\pm10 \,\mathrm{kA}\,\mathrm{m}^{-1}$ emerges and remains largely unchanged across the superconducting transition. The magnetism in SECNO is disordered and nonuniform.

cond-mat.supr-con↗

arXiv2025

Spectroscopic and Decade-long Photometric Observations of the Contact Binary V2790 Ori: Evidence for a Brown Dwarf Companion and a Solar-like Magnetic Activity Cycle

We present 22 sets of light curves and one radial velocity curve for the W UMa-type total eclipse contact binary system V2790 Ori, derived by combining all available public photometric data, the photometric data in previous studies, and our own spectroscopic and decade-long photometric observations. Our simultaneous analysis of the light curves and radial velocity curve shows that V2790 Ori is a W-subtype contact binary with a mass ratio of $q = 0.322(\pm0.001)$ and a shallow contact degree of $14.8(\pm0.6)\%$. The orbital period analysis based on 445 eclipsing minima reveals a secular decrease at a rate of $\dot P = -3.18 (\pm 0.75) \times 10^{-8}\mathrm{d~yr^{-1}}$, superimposed with a cyclic variation with an amplitude of $A = 8.98 (\pm 2.19) \times 10^{-4}~\mathrm{d}$ and a period of $ P_3 = 7.44 (\pm 0.52)~\mathrm{yr}$. The secular decrease is caused by AML via magnetic braking, while the cyclic period variation is explained by the light-travel time effect due to a third body, which is likely to be a brown dwarf. Furthermore, our analysis indicates a mass transfer from the more massive component to the less massive one at a rate of $1.22(\pm0.29) \times 10^{-8}~\mathrm{M_{\odot}~yr^{-1}}$. A model with a cool spot on each component was adopted to fit the O'Connell effect observed in the light curves. Since the O'Connell effect varies over time, we identified a solar-like magnetic activity cycle with a period of approximately 5.4 yr by analyzing the magnitude difference ($Δm$) at the two light maxima and the O'Connell effect ratio. In addition, evolutionary analysis suggests that V2790 Ori is a newly formed contact binary that evolved from a detached phase into the present contact configuration.

astro-ph.SR↗

arXiv2025

Cross-Modal Alignment between Visual Stimuli and Neural Responses in the Visual Cortex

Investigating the mapping between visual stimuli and neural responses in the visual cortex contributes to a deeper understanding of biological visual processing mechanisms. Most existing studies characterize this mapping by training models to directly encode visual stimuli into neural responses or decode neural responses into visual stimuli. However, due to neural response variability and limited neural recording techniques, these studies suffer from overfitting and lack generalizability. Motivated by this challenge, in this paper we shift the tasks from conventional direct encoding and decoding to discriminative encoding and decoding, which are more reasonable. And on top of this we propose a cross-modal alignment approach, named Visual-Neural Alignment (VNA). To thoroughly test the performance of the three methods (direct encoding, direct decoding, and our proposed VNA) on discriminative encoding and decoding tasks, we conduct extensive experiments on three invasive visual cortex datasets, involving two types of subject mammals (mice and macaques). The results demonstrate that our VNA generally outperforms direct encoding and direct decoding, indicating our VNA can most precisely characterize the above visual-neural mapping among the three methods.

cs.CE↗