arXiv preprints from January 1, 2026 through September 21, 2026 — 12:45:11 EST
Frontier language models are more aggressively using subquadratic attention to reduce the memory footprint and compute requirements during inference while still delivering frontier accuracy. While existing systems make dense attention-centric disaggregated serving decisions, we show that disaggregating inference around the unique...
Let $2\leq k<n/2$ and let $(M^n,[g_0])$ be a closed, connected, and locally conformally flat Riemannian manifold with a $k$-admissible metric in the conformal class $[g_0]$. We prove a stability result of the $σ_k$-curvature inequality on $M$, in the sense that if equality is almost satisfied for some conformal metric, then this...
We study Boolean Holant problems with complex-valued signature sets closed under conjugation. Such sets arise naturally in tensor-network expressions for classical strong simulation of quantum circuits. We prove a complexity dichotomy for such problems with an explicit tractability criterion. This extends the dichotomy for real-valued...
In 2021, Chern and Tang introduced two families of two-parameter modular functions associated with the Rogers-Ramanujan continued fraction. They established recurrence relations that express the members of these families in terms of eta quotients, and used these expressions to obtain dissection formulas. Motivated by their work, we...
The recent LUX-ZEPLIN (LZ) experiment analysis reported a high energy nuclear recoil candidate at $E_R \simeq 248~{\rm keV}$, motivating interpretations in terms of inelastic dark matter. We study this event in a pseudo-Dirac fermion model with a vector boson mediator $Z'$, assuming a low reheating temperature and dark matter...
We study the dynamical scalar tidal Love numbers of wormholes that provide viable mimickers for black holes, focusing on thin-shell Schwarzschild and Damour-Solodukhin geometries. Using a matched near- and far-zone expansion, we determine their tidal response in the low-frequency regime. The presence of a long throat introduces an...
Deep learning-based semantic communication (DeepSC), a Transformer-based encoder-decoder, achieves semantic fidelity over noisy channels but remains vulnerable to adversarial perturbations injected at multiple stages of the pipeline. We present a layer-wise robustness framework that compares fast gradient sign method (FGSM), projected...
Computational models supporting mechanistic understanding of (complex) biological systems, systems behaviour prediction, and experimental design are becoming more and more embedded in research on complex biological systems. Reuse and refinement of models, rather than continuous reinvention, is becoming increasingly important as...
Let $d,K,N\in \mathbb{N}$ with $K\geq 3$ and $d\geq 4K+4$. Let $Δ\subset \mathbb{Z}^d$ be the vertex set of a nondegenerate $(K-1)$-simplex, and let $A\subseteq[N]^d$ contain no nontrivial similar copy of $Δ$. We prove that \[ |A|\ll_{Δ,d} N^d\exp\!\left(-c_{Δ,d}\sqrt{\log N}\right) \] improving upon a polylogarithmic bound...
Accurate prediction of equity returns remains a major challenge in computational finance due to the non-stationary, nonlinear, and low signal-to-noise ratio nature of financial time series. This paper proposes a hybrid two-stage architecture that combines a long short-term memory (LSTM) network with an XGBoost gradient-boosted...
Excitons in magnetic semiconductors have energies and spin structures that are sensitive to the underlying magnetic order. We study this coupling in a minimal one-dimensional lattice model of a conduction electron and a valence hole moving in a ferromagnetic background of localized quantum spins, treating the electron, the hole, and...
Kinematic perturbations observed with ALMA in CO line emission provide evidence for a population of embedded giant protoplanets shaping the structure of protoplanetary disks. We present JWST/MIRI F1140C ($λ= 11.3~μ$m) coronagraphic observations of five protoplanetary disks, HD163296, RXJ1615.3-3255, RXJ1842.9-3532, SY Cha, and LkCa...
Let $g(n)$ denote the minimum number of peeling sequences among all $n$-point sets in general position in the plane. Dumitrescu and Tóth proved an exponential upper bound with base $12.29$, and Simon subsequently lowered the base to $9.78$. Using the same recursive construction, we prove \begin{equation*} g(n) \le (8+o(1))^n. \end{equation*}
Experimental evidence suggests that ambiguity-sensitive choice can vary systematically with the circumstances of a decision. This paper isolates one channel within a stable preference relation: ambiguity weighting may depend on the act's certainty-equivalent level. After the standard Anscombe-Aumann calibration of consequence utility,...
We study a mechanism of cooperation in the Prisoner's Dilemma (PD). Incorporating social preferences as efficiency concerns into the PD game, we study how altruism translates into cooperation. Under complete information, cooperation requires the opponent's altruism to clear a threshold. We then introduce a subjective extension of...
Graphical causal inference supplies a complete theory of efficient covariate adjustment for the average treatment effect: one adjustment set, computable from the graph, is optimal under every compatible distribution. We show that this is a property of the average treatment effect's inverse-prevalence weights, not of causal estimands...
We show how to optimally design experiments when the resulting data will be used to choose a welfare-maximizing policy subject to constraints. A decision maker seeks to maximize Bayes expected welfare by choosing a policy whose effects depend on an unknown finite-dimensional parameter. The decision maker has access to a first wave of...
This paper studies identification in linear quantile panel models with unrestricted individual heterogeneity when the number of time periods is fixed and small. We impose strict exogeneity, whereby the conditional quantile restriction holds given the individual's complete regressor history and latent individual effect, but otherwise...
Society constantly has to determine the boundaries of what it deems acceptable, from legislative decisions to the guardrails governing autonomous systems. We initiate the axiomatic study of collective consent: given individuals' attitudes toward options, which options should receive societal consent? We organize our analysis around...
Many real-world policies and business interventions require assessing short-term effects to inform timely decisions, even though most causal inference methods focus on long-term average treatment effects. In this paper, we introduce average treatment effect localization (ATEL), which captures localized, short-term policy impacts in...
Speech large language models (SpeechLLMs) offer reduced latency and retain paralinguistic nuances that are typically lost in cascaded automatic speech recognition (ASR) and text-based LM architectures. However, they continue to lag behind text-only LLMs on complex reasoning tasks, while real-time spoken interaction imposes strict...
We consider a game theoretic approach to solve multi-agent coordination problems with submodular maximization objectives. It is known for such problems that the Nash equilibria for the corresponding game are always within 50% of the optimal, but that the equilibria which achieve this worst-case bound are not stable. To exploit this...
Considering sharing or coexistence from the perspective of spectrum alone fails to recognize that any spectrum-enabled service also requires (i) radio and processing infrastructure and (ii) a protocol stack, including waveforms and signal processing pipelines. The efficiency of spectrum coexistence frameworks such as Citizen Broadband...
This paper describes a system to automatically dock an AUV onto a docking station without precise knowledge of the position and orientation of the latter, in the presence of unknown ocean currents, using a fully acoustic sensing architecture. The system relies on a pair of Ultrashort Baseline sensors, one onboard the vehicle and one...
This paper investigates optimal control for nonlinear systems with unknown dynamics, input constraints, disturbances, and adversarial signals. The objective is to develop a learning-based control method that allows the designer to prescribe the desired convergence time in advance. An integral reinforcement-learning framework is...