Search arXiv⌕ Search

arXiv subjects

Search papers

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

At least 1,207 records · Page 67Linked to original sources
arXiv2026

RGraph-Eval: Task-Grounded Scene Graphs for Evaluating Robot Video Generation

Generated robot videos can look convincing while depicting the wrong interac- tion: a different object is moved, a grasp disappears, or a placement ends out- side its destination. We introduce RGraph-Eval, a reference-based framework that makes these discrepancies explicit through task-grounded temporal scene graphs. Unlike approaches that construct separate evidence representations for different evaluation dimensions, we organize task entities, interactions, and motion within a unified, interpretable scene graph representation. A foundation-model pipeline identifies manipulation roles, grounds persistent object masks, infers and verifies state transitions and action intervals, and reconstructs manipulated- object motion in three dimensions. Applying this representation to a generated video and a reference demonstration supports an interpretable RGraph-Eval score with visible-object, relation-change, and 3D path-shape components. We also introduce ShareRobot-SG, a collection of 1,000 manipulation scenes from ten ShareRobot sources annotated with the multimodal representation. Our eval- uation separates graph-generation quality from agreement with human video judgments, and includes comparisons with adapted SVG2 and SG-Ego, a bench- mark of three video generators. The framework connects robot-video assessment to the observable entities and interactions underlying a task, while making the graph annotations reusable beyond evaluation. Code will be publicly available at https://github.com/SashaDance/rgraph-eval.

cs.RO↗
arXiv2026

Parton distribution functions of the proton in a hot isospin-asymmetric nuclear medium and finite nuclei

When a nucleon is bound in a nucleus, its quark distributions are modified, and the change in the spin-dependent distributions can differ in size from that in the spin-independent ones. We compute the unpolarized $f_1(x)$, helicity $g_1(x)$, and transversity $h_1(x)$ distributions of the $u$ and $d$ quarks in a proton immersed in hot and isospin-asymmetric nuclear matter. The proton is described in the diquark spectator model, with the medium effects entering through the effective quark, diquark, and proton masses computed using the chiral SU(3) quark mean field (CQMF) model. The axial and tensor charges are obtained for baryon densities up to saturation density and temperatures $T = 0$ and $0.1$ GeV, in both symmetric nuclear matter and pure neutron matter. The distributions are then carried to $^{40}$Ca, $^{56}$Fe, $^{197}$Au, and $^{208}$Pb at zero temperature through the local density approximation. In symmetric matter at saturation density and zero temperature, the peaks of the three $u$ quark distributions move toward larger $x$ and fall least for the unpolarized distribution and most for the transversity distribution, so the spin-dependent $u$ quark distributions are modified more strongly. Between vacuum and saturation density, the axial charge of the proton drops from $1.28$ to $0.844$, and the tensor charge of the $u$ quark decreases while that of the $d$ quark grows in magnitude. At the center of each nucleus, the axial charge of the proton rises from $0.699$ in $^{40}$Ca to $0.817$ in $^{208}$Pb as the central baryon density decreases, which suggests that the modification at the center follows the central density rather than the mass number.

hep-ph↗
arXiv2026

WildDepth-v2: A Synchronized RGB--LiDAR--Radar Dataset and Benchmark for Metric Depth, Motion, and Tracking of Wildlife

Measuring animal distance and motion in metric units underpins abundance estimation, morphometrics, and movement ecology, yet monocular video lacks metric scale and wildlife datasets lack metric ground truth. We present WildDepth 2, extending the synchronized RGB-LiDAR WildDepth dataset in three directions. (i) Imaging radar: 37 RGB-LiDAR-4D-radar sequences (19,716 frames) with per-point Doppler velocity and a measured error budget, to our knowledge the first imaging-radar wildlife recordings. (ii) Benchmarking: a frozen, checksummed hidden test set for RGB-only distance estimation and RGB+sparse-LiDAR depth completion, evaluated separately on animal and background pixels. (iii) Motion and tracking: metric 3D trajectories obtained by lifting 2D tracks using LiDAR, radar, or monocular depth. Across 48,723 animal frames, object-level radar calibration improves monocular depth over scene-level LiDAR calibration without requiring LiDAR at inference (AbsRel 0.120 vs. 0.198), although animal-level LiDAR remains more accurate (0.052). Across 431 tracks, once-per-track radar scaling reduces 3D position error four-fold (2.20 to 0.58 m) and distance-sampling detection-function bias from -13% to -2%, matching once-per-track LiDAR calibration. Transferring radar Doppler onto LiDAR produces motion masks 3.7 times denser than radar alone at 72% precision, reduces moving-animal LiDAR accumulation error by 37%, and estimates radial speed (r = 0.60), albeit with approximately 50% underestimation.

cs.CV↗
arXiv2026

Quantitative positivity properties of the temperature in multi-dimensional thermoviscoelastic systems

We consider the classical model for small-strain thermoviscoelastic evolution in isotropic Kelvin-Voigt materials with inertia, as given by $$\begin{cases} u_{tt} = μΔu_t + (λ+μ)\nabla\nabla\cdot u_t + \hatμΔu + (\hatλ+\hatμ)\nabla\nabla\cdot u - B\nablaΘ, \\ κΘ_t = DΔΘ+ μ|\nabla u_t|^2 + (λ+μ)|\mathrm{div}\,u_t|^2 - BΘ\,\mathrm{div}\,u_t. \end{cases}$$ Recently, Winkler (arXiv:2602.05964) established global-in-time solvability for an initial value problem in smoothly bounded multi-dimensional domains $Ω$ under homogeneous Dirichlet boundary conditions for the displacement variable $u$, and homogeneous Neumann boundary conditions for the temperature $Θ$, allowing the heat capacity $κ$ to depend on $Θ$. Moreover, it was shown there that the corresponding temperature is positive a.e. in $Ω\times(0,\infty)$. In the present work, we strengthen this positivity result by deriving a quantitative lower bound for $Θ$. Our analysis applies to heat capacities $κ$ with power-law scaling for small arguments, precisely: either $κ(ξ)\simξ^α$ for some $α\ge 0$, or $κ(ξ)\geξ$, in a suitable neighborhood of $ξ=0$. Under these structural assumptions on $κ$, we show that for every $τ>0$ and $T>τ$ there exists $c(τ,T)>0$ such that $Θ(x,t)\ge c(τ,T)$ for a.e. $(x,t)\inΩ\times(τ,T)$.

math.AP↗
arXiv2026

Delta N-gram: Forward-Only Continual Writing into a Language Model's Native N-gram Memory

Our previous analysis found that a model's native hashed N-gram table is where continual updates disturb the base least, but its writes needed backpropagation and changed the pretrained table. We present Delta N-gram, a forward-only write path into that table. The pretrained table T^0 is never modified. Evidence is written into a sparse patch Δon the rows it addresses: a 4.1M-parameter writer emits a target and a gate per (position, hash head) event, and a block-averaged delta rule keeps each row a convex combination of its old value and the gated targets. The writer is trained offline on raw text with the pretraining objective; at use time writing takes forward passes only, and clearing Δrestores the original model. A 0.6B prototype trained to answer questions keeps 16/16 facts after a second write; online gradient writes keep 2--4/16. We study two writers: a plain writer that encodes evidence with the T^0-only model, and a delta writer that reads its current memory while encoding. On Qwen3.8-Flash-Next, the plain writer's memory is document-specific: on 64 held-out news events it lowers continuation NLL by 0.068 nats/token against empty memory and by 0.024 against another document's memory, and 0.063 and 0.013 after 16 intervening articles. The delta writer's memory is more document-specific and keeps more of it under distraction (70% vs 54%). Over 35,000 writes on our previous seven-task chain both writers stay stable and the delta writer drifts less (layer-2 math drift 176% vs 188%); later accuracy changes by -0.26/-0.52pp (-7.29pp for gradient updates) and small-k_i drift is 17.9/17.5% (39.2%). Acquisition is negative, and general-input drift reaches 32.8% (20.75%): format rows read by every example grow to 4--12 times their pretrained norm. Zeroing eight such rows removes over 98% of layer-2 drift on math inputs, together with their NLL gain.

cs.CL↗
arXiv2026

Entropy-production cost limits hierarchical decision-making in homing pigeon flocks

Collective decision-making requires individuals to reconcile diverse, often conflicting opinions to reach a common course of action. However, within a group, they rarely exert equal influence, leading to non-reciprocal communication patterns manifested as leader-follower relationships and social hierarchies. Here, using homing pigeon flocks as a model system, we develop a trajectory-based framework to infer and quantify hierarchy within navigating living collectives. We find that while small flocks exhibit pronounced hierarchy, increasing flock size progressively weakens it, driving the collection toward more egalitarian decision-making. We provide a physical basis of this observation using a thermodynamic framework in which non-reciprocal communication between birds carries an information-entropy cost. Our calculations reveal that hierarchy weakening observed in larger flocks is a direct consequence of maintaining a constant per-individual entropy production rate across flock sizes. Together, these results suggest that constraints on information-processing capacity may play an important role in the collective dynamics of living organisms.

cond-mat.soft↗
arXiv2026

The often overlooked role of sound in liquid thermal transport

Formulated a hundred years ago, the Bridgman formula for thermal conductivity of liquids postulates a proportionality between sound velocity and thermal conductivity. This designates phonons as heat carriers in a liquid. Its empirical success has been under-appreciated and its conceptual implications overlooked. It is not mentioned in well-known condensed-matter textbook. Here, we review its origin, its links to hydrodynamic Euler equations and to the fundamental paradox surrounding the parabolic heat equation and its fate across the quantum-classical crossover.

cond-mat.mtrl-sci↗
arXiv2026

Open dynamics with a moving hole: inhomogeneous IFS and exponential separation condition

Let $\mathcal F=\{f_i(x)=r_i x+t_i\}_{i=0}^{b-1}$ be a self-similar iterated function system (IFS) on $\mathbb R$ with $b\ge 3$, and let $K_{\mathcal F}$ be the associated self-similar set. Given $m\in\mathbb N$, for any sequence $ω=ω^0ω^1\ldots$ with each $ω^i\in \{0,1,\ldots,b-1\}^m$ a block of length $m$, let \[ K_{\mathcal F}^ω:=π_{\mathcal F}\left(\{(d_i)\in \{0,1,\ldots,b-1\}^{\mathbb N}: d_{k+1}d_{k+2}\ldots d_{k+m}\neω^k\quad\forall k\ge 0\}\right), \] where $π_{\mathcal F}$ is the natural coding map from $\{0,1,\ldots,b-1\}^{\mathbb N}$ to $K_{\mathcal F}$. The set $K_{\mathcal F}^ω$ is called the survivor set of an open dynamical system with a moving hole related to $ω$. When $\mathcal F$ is a homogeneous IFS satisfying the open set condition (OSC), the dimensions of $K_{\mathcal F}^ω$ were determined by the first author, Sun and Wang (Adv. Math., 2026). In this paper we generalize these results to inhomogeneous IFSs. When $\mathcal F$ satisfies the OSC, we give explicit formulae for the dimensions of $K_{\mathcal F}^ω$. In particular, we show that the packing dimension and upper box-counting dimension of $K_{\mathcal F}^ω$ always coincide, while the Hausdorff dimension and lower box-counting dimension of $K_{\mathcal F}^ω$ are not necessarily equal, which is different from the homogeneous case. Furthermore, when $\mathcal F$ satisfies the exponential separation condition and the similarity dimension $s_{\mathcal F}\le 1$, we are able to determine the Hausdorff dimension of $K_{\mathcal F}^ω$. Finally, we apply our results to badly approximable numbers and non-recurrence points in the setting of inhomogeneous IFS satisfying the OSC.

math.DS↗
arXiv2026

Quasinormal modes of Type I perturbations of dilaton-Euler-Heisenberg black holes

We study the type I quasinormal modes (QNMs) of magnetically charged dilaton--Euler--Heisenberg (dEH) black holes, where axial gravitational and polar electromagnetic perturbations are coupled. Direct integration and Chebyshev pseudospectral methods give consistent QNM frequencies for the fundamental branches continued from Schwarzschild at $\ell=1,2,3$. Varying $α$ at fixed $ζ=α-β$ changes the spectrum on the same background. The damping response depends on charge and multipole and can have opposite signs for the two coupled branches. For $ζ<0$, dipole damping decreases with charge toward horizon merger. For $ζ>0$, the Type I charge range extends beyond the complementary polarization's local angular-gradient bound. All tracked modes remain damped in the nonextremal ranges, supporting the stability of these branches.

gr-qc↗
arXiv2026

Post-Audit Mirage: Identifiability Limits of Offline Agent Verification

Offline tests can fail to reveal whether an agent update will remain safe after deployment. We operationalize this post-audit mirage using matched safe and harmful lifecycles that expose identical verifier-visible evidence while an isolated scorer records opposite deployment truth. Our theorem applies standard observational-equivalence and indistinguishability ideas to this executable audit boundary and states the resulting error-abstention tradeoff. The Post-Audit Mirage benchmark makes that boundary executable across authorization, scheduling, and shared-capacity environments. IdentifiedRangeMonitor uses fresh group-labelled harm outcomes to return deploy, hold, cannot determine, or unsupported. Experiments show that monitoring can recover the missing distinction in favorable settings but may remain undecided for rare groups, small effects, or missing observations. Verifier-agent evaluation must therefore test both calculation validity and whether the available evidence supports the deployment decision.

cs.AI↗
arXiv2026

Music Between Two Minds: Individual Signatures, Shared States, and the Emergence of Creative Interaction

Some of the most valued forms of human creativity arise between people-in conversation, collaboration, and improvised music-yet how two minds jointly regulate the flow of novelty in real time remains unknown. Here we examined the information dynamics of interpersonal improvisation using 986 professional jazz improvisations. Pitch-based fluctuations of uncertainty and surprise behaved as signatures of individual identity: the two partners differed within 90% of takes, performers were identifiable from single solos and the separation between partners persisted undiminished across turns and takes. Rhythm-based fluctuations showed the reverse organization: partners were statistically indistinguishable within a take yet shifted together from take to take, and this shared state drifted gradually as each performance progressed, with each performer moving away from their own past at the same rate as from their partner's. Beyond joint drift, solo hand-offs revealed turn-by-turn complementarity: when one performer exceeded their own average surprise in the predictive dynamics of improvisation, the partner's next solo fell below their own, in both pitch and rhythm and in all duos. Improvising pairs thus neither fuse into one system nor remain two independent ones: they preserve individual melodic voices while sharing a rhythmic state, within which moment-to-moment push-pull continually rebalances their interaction. Individuality and togetherness thus coexist, carried by different musical dimensions, a measurable organization of creativity that emerges between minds.

q-bio.NC↗
arXiv2026

The Hardy-Littlewood-type equivalence problem and its applications

The main purpose of this paper is to resolve the Hardy-Littlewood-type equivalence problem. In particular, we show that a Hardy-Littlewood-type theorem holds for arbitrary majorants in the case \(p\in(1,\infty)\), and that the equivalence holds in the case \(p=1\). For the proof, we employ new functional analytic approaches based on Fourier series, the Hilbert transform, and the uniform boundedness principle. Those proof methods are completely different from those of Dyakonov [Acta Math., 178 (1997), 143-167] and Pavlović [Acta Math., 183 (1999), 141-143]. In addition, we present several representative applications that improve a series of known results.

math.CV↗
arXiv2026

Is High Local Accuracy Enough? Geometric Consensus with Support-Adaptive Statistical Personalization for Federated Learning

Real-world deployment of personalized federated learning (PFL) requires adapting to heterogeneous clients while preserving recognition performance beyond local distributions. However, high local accuracy can conceal failures on locally rare or absent classes. Effective personalization should therefore strengthen global recognition while raising the personalization floor. We propose an evaluation protocol that complements local accuracy with global, rare-class, and unseen-class evaluations to reveal generalization obscured by local scores, and assesses personalization floors among the worst-performing clients to expose weaknesses hidden by aggregate performance. To meet these deployment challenges, we propose FedGRC, a unified PFL framework integrating generalization and personalization through (i) Consensus-Guided Representation Learning (CGRL), which learns discriminative representations through shared directional and magnitude guidance; (ii) Multilayer Metric Synthesis (MMS), which constructs a shared covariance metric from these multilayer representations for statistical classification; and (iii) Support-Adaptive Shrinkage Personalization (SASP), which adapts class means within this metric by shrinking local estimates toward shared means according to local sample support, enabling adaptation while retaining shared knowledge. Extensive experiments, including benchmarking against 21 methods across 5 heterogeneity settings on 3 datasets and comprehensive ablation studies, validate the effectiveness of FedGRC. On CIFAR-10 and CIFAR-100, FedGRC surpasses state-of-the-art (SOTA) baselines in global recognition and personalization floors by at least 2.17% and 2.13%, respectively. On the real-world heterogeneous FedRS dataset, it outperforms the respective best baselines by 2.15%, 3.30%, and 4.61% in local adaptation, global recognition, and the personalization floor.

cs.LG↗
arXiv2026

Well-posedness of a stress-augmented Moore-Gibson-Thompson-type model for thermoviscoelastic evolution in a standard linear solid

This manuscript studies a coupled system of nonlinear parabolic and hyperbolic equations that models thermoviscoelastic materials with explicit internal stress relaxation, $$\begin{cases} τu_{ttt} + u_{tt} = (D(Θ)u_{xt})_x + (C(Θ)u_x)_x, \\ Θ_t = Θ_{xx} + |E(Θ)u_{xt} + F(Θ)g_t|^2, \\ τg_t + g = D(Θ)u_{xt} + C(Θ)u_x. \end{cases}$$ The system arises from a stress-strain constitutive relation of Zener type, where the internal variable $g$ encodes mechanical memory effects. A key feature is the explicit coupling of stress relaxation to the heat equation through the dissipation term, which differs from standard approaches that eliminate $g$ via algebraic substitution. Under the assumptions that $τ>0$ and that $D,C\in C^2([0,\infty))$ are positive and $E,F\in C^1([0,\infty))$, and for suitably regular initial data, we establish local existence and uniqueness of strong solutions. Under additionally strengthened regularity requirements on the initial data and on $D,C$, this solution is moreover shown to be classical. These results extend a corresponding local strong and classical solvability theory developed for the underlying system without the stress variable $g$ to the present, stress-augmented setting.

math.AP↗
arXiv2026

Mixing Matters: Evidence Position Bias Across Sequence Mixers in Long-Context Question Answering

Long-context models often use answer-bearing evidence less effectively when it appears away from a prompt boundary. We compare this position bias across Transformer, state-space, and hybrid Mamba architectures by moving one gold document through a fixed set of nine distractors. The evaluated Transformers show a beginning advantage that the evaluated state-space models lack, while both families favor evidence near the end. A matched pure-versus-hybrid Mamba comparison points in the same direction but remains statistically uncertain. The family difference appears among models that can answer the task. Transformer primacy reappears on synthetic retrieval, where state-space ceiling prevents a family comparison. A corpus swap within one state-space architecture changes overall accuracy without a detectable change in curve shape. Prompt changes can create or nearly remove a beginning advantage. Position remains decodable across architectures even when response curves differ, and attention concentration near initial tokens covaries with beginning sensitivity in the tested Transformer family. These exploratory results show that effective context use depends on the evaluated architecture family, capability, task, and prompt, without isolating the sequence mixer as the sole cause.

cs.CL↗
arXiv2026

Array Rotation in Near-Field ISAC: Communication, Detection, and Estimation Under Low-Complexity Transmit Architectures

This paper studies near-field integrated sensing and communication (ISAC) with a rotatable base-station array under an exact spherical-wave propagation model. For a general transmit covariance, we derive a Cramér--Rao bound (CRB) decomposition that separates target-side geometry from transmit-covariance-dependent terms. We then specialize the framework to two representative low-complexity architectures: a single-stream superposition architecture, and a dual-waveform split architecture design. We characterize the communication-, detection-, and estimation-optimal rotations for each architecture using the exact finite-array model. In addition, we show how a second-order approximation yields compact approximate expressions for the optimal rotation angles. We also study uncertainty in the target state used for beamforming design through a correlated Gaussian perturbation model, and derive approximations of the optimal robust rotation angles for target sensing and detection. The analysis shows that the two architectures behave differently under rotation: the single-stream design can align communication and detection tasks, whereas the dual-waveform design exhibits a direct communication--detection tradeoff and can incur a larger communication loss when sensing is prioritized. Numerical results show clear gains over a fixed array orientation, especially for range estimation, and close agreement between the approximate and exact rotation choices. Detection is less affected by target-state errors than estimation in the considered cases.

eess.SP↗
arXiv2026

Grushin spherical harmonics in non-degenerate dimension one

The Grushin Laplacian $Δ_α= Δ_x +|x|^{2α}Δ_y $ is a degenerate elliptic operator in $\mathbb{R}^{h+k}$ that degenerates on $\{0\} \times \mathbb{R}^k$. We explicitly compute the Grushin spherical harmonics on the gauge sphere $\{(x,y) \in \mathbb{R}^{h+k} : |x|^{2(α+1)}+(α+1)^2|y|^2=1\}$ and the corresponding spectrum when the non-degenerate dimension $h=1$, a case not covered by the existing literature. The eigenfunctions consist of homogeneous Grushin-harmonic polynomials of degrees $n \equiv 0,1 \pmod{α+1}$, even and odd in the $x$-variable respectively, which can be described in terms of Jacobi polynomials.

math.AP↗
arXiv2026

Zero Forcing on Maximal Outerplanar Graphs: Capacities and Phase Repair

We determine the zero-forcing number of maximal biconnected outerplanar graphs. When the weak dual is a path, the zero-forcing number and the induced path-covering number are both two. Otherwise, the branching faces determine a canonical core and a family of terminal strips. We prove that an optimal forcing process can be chosen in a normal form governed by explicit vertex and face capacities on the core. After fixing forests on the terminal strips, the zero-forcing number is expressed through an optimization over core-edge selections and the minimum number of root connections that must be removed to obtain an executable orientation. The path-covering number is obtained from the same capacity optimization without the repair cost. We characterize executable orientations by blocking-circuit equations and identify the two-path obstruction with a first cohomology class of a signed contact multigraph. Local replacements and a finite comparison of boundary recurrences establish the normal form for graphs of arbitrary size. A fifty-six-state recurrence constructs a minimum zero-forcing set and a complete forcing chronology in linear time from indexed triangle adjacency. We also obtain exact replacement results for rooted blocks and construct infinite families in which the zero-forcing number exceeds the path-covering number.

math.CO↗