arXiv preprints from January 1, 2026 through September 19, 2026 — 09:31:17 EST
Exploiting the equality restrictions that nested Markov models encode requires their tangent-space geometry. For strictly positive finite-state models on arbitrary acyclic directed mixed graphs (ADMGs), we differentiate the recursive-head chart and prove that the range of its score map is the full tangent space. Intrinsic-set...
We study anonymous binary social choice functions on the universal weak-preference domain when the society of voters is countably infinite. Voters may strictly support one of the two alternatives or be indifferent, and non-manipulability is required in the form of coalitional strategy-proofness. Full anonymity reduces the relevant...
This paper introduces segregation monotonicity as a criterion for evaluating measures of inequality in social networks. A network inequality measure satisfies segregation monotonicity if, holding the distribution of income fixed, it weakly increases as the network becomes more segregated according to a specified transformation of...
Early-career work both signals a worker's ability and builds long-run skills. We introduce an AI industry into a career signaling model. The industry sells tokens, which workers convert into output indistinguishable from their own. We compare three regimes: no token trade, purchases only, and open trade with side sales. With no token...
Two dominant tokenisation algorithms are used by modern language models: byte-pair encoding (BPE) and UnigramLM. These differ along two orthogonal axes: their optimisation objective (compression vs. log-likelihood) and their search procedure (bottom-up merging vs. top-down pruning). Existing comparisons confound these axes, making it...
Direct preference alignment methods are widely used to align large language models (LLMs) with human preferences because of their computational and memory efficiency. However, likelihood displacement motivates alternative ways to extract information from preference pairs with small likelihood margins. In this paper, we propose and...
Intelligent systems that act in the world require image understanding that is both comprehensive and spatially grounded. Current vision-language models (VLMs) can generate fluent and detailed image captions, but reliably associating them with image pixels remains challenging. Existing methods that combine dense captioning with...
World models endow perceptual systems with the ability to predict how scenes evolve under interaction. They are most beneficial when trained on diverse volumes of data, to instill a rich prior into downstream applications. Existing methods typically require robot action labels to learn action-conditioned 3D dynamics, which excludes...
Cylindrical blast wave theory relates infrasound from hypersonic sources to energy deposition through a characteristic blast radius R_0, yet the normalization constant k in the scaling R_0 = k (E_0/p_0)^(1/2) differs by up to 40% across the formulations examined here. This uncertainty affects period-based source characterization for...
AI agents for security inspect web pages, source code, logs, configuration files, and command outputs. These environments may contain deceptive artifacts that influence the agent's behavior. We call this adversarial task contamination. Whereas prompt injection relies on attacker-supplied instructions, task contamination also includes...
Rapid medical triage following ionizing radiation exposure is critical for emergency management, yet traditional alignment-based bioinformatics are too computationally intensive for mass-casualty scenarios. To address this, we developed STUART (Sequence Triage and qUAntification of Read Transcripts), a mapping-free machine learning...
Enabling robots to adapt to unfamiliar environments as readily as humans remains a moonshot goal of embodied AI. No finite collection of demonstrations can cover every task and situation a robot will encounter, making the ability to learn from context at deployment essential for generalization. Such in-context learning (ICL), however,...
Recent advances in video generation allow robots to learn manipulation trajectories from generated videos. However, these approaches produce purely kinematic trajectories that lack force information, causing failures in contact-rich tasks where appropriate contact forces are essential for success. In this work, we explore augmenting...
The paper presents a one-pass algorithm in the insert-delete graph stream model that returns a $(1+\varepsilon)(α+2)$-approximation for the size of the maximum matching in a graph of arboricity at most $α$. The algorithm uses $O(\varepsilon^{-4/3}α^{4/3}n^{2/3} \text{polylog} n)$ space. For constant $α$ and $\varepsilon$, this...
Can a logged dataset visit every hidden state frequently and still be exponentially uninformative about a target policy's value? We show that it can when the logger depends on history. For every horizon $H \ge 3$, we construct two POMDPs with at most two latent states per stage, three actions, and a common logger with three memory...
Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain conventions, and specialized correctness criteria make this knowledge difficult to convert into reliable learning experience-a challenge we call the scientific experience bottleneck. We...
We report the direct imaging detection of a stellar companion to HD 101452 (HIP 56925; Gaia DR3 5384905720847544192), an A star historically used as an infrared flux calibrator. The companion was identified from an asymmetry in the stellar PSF using short-integration (<1 min), noncoronagraphic JWST MIRI imaging from 15 - 25.5$μ$m that...
The mass profiles of galaxy halos encode how baryons reshape dark matter distribution, yet direct observational constraints across the full radial range remain scarce. Here we combine stellar kinematics from MaNGA, H I dynamical measurements from ALFALFA, and independently calibrated halo masses of SDSS groups to statistically...
Epsilon Eridani b, the nearest known Jupiter analog, has its orbit and mass constrained from radial velocity (RV) and absolute astrometry, and its atmosphere from JWST/NIRCam imaging upper limits in Sanghi et al. 2026. Here we follow up that work with a self-consistent model of Epsilon Eridani b that treats all available data within a...
We present IB-Flows, an open-source, multi-GPU solver for the direct numerical simulation of incompressible fluid-structure interaction (FSI) problems. The code couples a second-order finite-difference fractional-step Navier-Stokes solver on a staggered Cartesian grid with two immersed boundary methods: a Lagrangian method based on...
A \emph{directed feedback vertex set} of a digraph is a set of vertices whose removal destroys all directed cycles. The \textsc{Directed Feedback Vertex Set} (\textsc{DFVS}) problem asks for such a set of minimum cardinality or minimum total weight. Although general \textsc{DFVS} admits no constant-factor approximation under the...
Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery from failed steps. We extend SwiftSage, a dual-process agent that combines a fast action proposer with a slower planner, using two modular cognitive extensions: an Adaptive Memory Module...
We present EarStreAM, a closed-loop earable system for stress-adaptive meditation that integrates in-ear physiological sensing with personalized, real-time intervention. Leveraging OpenEarable 2.0's multimodal sensing, EarStreAM continuously monitors physiological signals and detects elevated stress from heart rate and heart rate...
Very recently, Lech Mazur proved the celebrated Sendov conjecture, and Terence Tao subsequently distilled the main ideas of the proof in a blog post. In this paper, we establish a quantitative strengthening of Sendov's conjecture, namely the quadratic Tang--Zhang inequality. Let $p$ be a polynomial of degree $n\ge2$ whose zeros lie in...
Computer-use agents increasingly operate software designed for people, but interfaces often leave actions or task state unclear to machine readers. We present Affora, a design system that supports both readers while preserving visual freedom and familiar human workflows. Three controlled studies examine component implementations,...