Lateral connection is a fundamental feature of biological neural circuits, facilitating local information processing and adaptive learning. In this work, we integrate lateral connections with a substructure selection network to develop a novel diffusion model based on spiking neural networks (SNNs). Unlike conventional artificial neural networks, SNNs employ an intrinsic spiking inner loop to process sequential binary spikes. We leverage this spiking inner loop alongside a lateral connection mechanism to iteratively refine the substructure selection network, enhancing model adaptability and expressivity. Specifically, we design a lateral connection framework comprising a learnable lateral matrix and a lateral mapping function, both implemented using spiking neurons, to dynamically update lateral connections. Through mathematical modeling, we establish that the proposed lateral update mechanism, under a well-defined local objective, aligns with biologically plausible synaptic plasticity principles. Extensive experiments validate the effectiveness of our approach, analyzing the role of substructure selection and lateral connection during training. Furthermore, quantitative comparison
Chain-of-thought (CoT) reasoning improves large language models (LLMs) on difficult tasks, but it also makes inference expensive because every intermediate step must be generated as a discrete token. Latent reasoning reduces visible token generation by propagating continuous states, yet replacing explicit derivations with latent computation can hurt tasks that require symbolic checking. We propose Latent-Then-Explicit Reasoning (LaTER), a two-stage paradigm that first performs bounded exploration in a continuous latent space and then switches to explicit CoT for verification and answer generation. In a training-free instantiation, LaTER projects final-layer hidden states back to the input embedding space, preserves the latent KV cache, and uses entropy and model-native stop-token probes to decide when to switch. We find that strong reasoning models already exhibit structured latent trajectories under this interface. On Qwen3-14B, training-free LaTER reduces total token usage by 16%-32% on several benchmarks while matching or improving accuracy on most of them; for example, it improves AIME 2025 from 70.0% to 73.3% while reducing tokens from 15,730 to 10,661. We further construct La
A mathematical model for wire rolling is developed, focusing on predicting the lateral spread. This provides, for the first time, an analytic model of lateral spread without any fitting parameters. The model is derived directly from the governing equations, assuming a rigid, perfectly plastic material and exploiting the thinness of the wire (in thickness and width) relative to the roller size. Results are compared against experiments performed on stainless steel wire using 100mm diameter rolls, demonstrating accurate predictions of lateral spread across a wide range of wire diameters (2.96mm-7.96mm) and reduction ratios (20%-60%), all without the need for fitting parameters. Since the model requires only seconds to compute, the model's valid range is explored for varying roll diameter, wire diameter, and reduction ratio, and their effects on the resulting lateral spread characterized. The model can serve as a robust tool for validating FE results, guiding process design, and laying the foundation for future improved models. Matlab code to evaluate the model is provided in the supplementary material.
Semiconducting transition metal dichalcogenides (TMDs), such as MoSe$_2$ and WSe$_2$, exhibit unique optical and electronic properties. Vertical stacking of layers of one or more TMDs, to create heterostructures, has expanded the fields of moiré physics and twistronics. Bottom-up fabrication techniques, such as chemical vapor deposition, have advanced the creation of heterostructures beyond what was possible with mechanical exfoliation and stacking. These techniques now enable the fabrication of lateral heterostructures, where two or more monolayers are covalently bonded in the plane of their atoms. At their atomically sharp interfaces, lateral heterostructures exhibit additional phenomena, such as the formation of charge-transfer excitons, in which the electron and hole reside on opposite sides of the interface. Due to the energy landscape created by differences in the band structures of the constituent materials, unique effects such as unidirectional exciton transport and excitonic lensing can be observed in lateral heterostructures. This review outlines recent progress in exciton dynamics and spectroscopy of TMD-based lateral heterostructures and offers an outlook on future deve
Recent observations have revealed numerous protocluster candidates at $z\,{\gtrsim}\,5$, yet whether these systems will eventually evolve into today's galaxy clusters remains an open question. Using the FLAMINGO simulations -- resolving protocluster cores up to $z\,{\simeq}\,10$ -- we track the later evolution of observationally selected protocluster candidates, comparing three selection methods against observational samples. The observed number density falls between our mass-selected and abundance-matched samples, implying that current searches pick up both genuine cluster progenitors and significant interlopers that will not reach cluster masses by $z\,{=}\,0$. We find that candidates at $z\gtrsim5$ are heavily clustered, hosting 2$-$10 neighbors within 10\,cMpc. Consequently, a candidate with a neighbor at 5\,cMpc (10\,cMpc) faces a $\gtrsim50\%$ ($\gtrsim30\%$) probability of later merging into a larger system, mostly at $z\,{\lesssim}\,2$. The merger count converges beyond ${\sim}10$\,cMpc, pointing to a fundamental scale in structure formation. Observations show markedly weaker clustering than our simulations predict, suggesting clustering offers a currently overlooked diagno
Automated parking requires accurate localization for quick and precise maneuvering in tight spaces. While the longitudinal velocity can be measured using wheel encoders, the estimation of the lateral velocity remains a key challenge due to the absence of dedicated sensors in consumer-grade vehicles. Existing approaches often rely on simplified vehicle models, such as the zero-slip model, which assumes no lateral velocity at the rear axle. It is well established that this assumption does not hold during low-speed driving and researchers thus introduce additional heuristics to account for differences. In this work, we analyze real-world data from parking scenarios and identify a systematic deviation from the zero-slip assumption. We provide explanations for the observed effects and then propose a lateral velocity model that better captures the lateral dynamics of the vehicle during parking. The model improves estimation accuracy, while relying on only two parameters, making it well-suited for integration into consumer-grade applications.
Final outputs hide when a checkpoint commits to its next-token prediction. We introduce the convergence gap, a model-diffing diagnostic that decodes each layer's next-token distribution and measures its distance to the model's own final distribution. Across six paired pretrained and instruction-tuned checkpoints in native prompting regimes, instruction-tuned checkpoints remain farther from their final predictions later into the stack. The effect persists under endpoint-matched raw and tuned readouts, endpoint-free same-history checks, and fixed-history template replay. Matched-prefix interventions identify late MLP windows as the largest tested leverage point: late IT grafts into PT hosts increase late KL by +0.34 nats, while PT-late swaps into IT hosts reduce it by -0.51 nats; matched random late perturbations give only +0.003 versus +0.327 for the true late graft. A preselected Gemma case study provides behavior-facing plausibility for the same late swap, without serving as a benchmark claim. These results identify a robust predictiondynamics signature of post-training: released instruction-following checkpoints tend to settle later, and late MLP computation is the strongest test
Helping seems to make a lock wait-free: wrap the critical section in an idempotent thunk that any process can finish once the holder stalls. Yet helping protects the system, not the call. An overwritable candidate lets later requests bump one another in sequence, so a call can be forced to help newcomer after newcomer and never return, while point contention never exceeds two. We ask whether a call can instead be charged only for the requests active when it takes its ticket, never for what arrives afterward. We show that the answer is yes. SeniorLock is a deterministic helpable thunk lock in which a call with ticket-time seniority $β$ finishes in $O((β+1)(T+1))$ local shared-memory steps, where $T$ bounds one thunk's cost, independently of later invocations. We call this guarantee \emph{retrospective wait-freedom}. The same lock doubles as a universal construction we call SeniorObj: it turns any deterministic sequential object whose operations are bounded, concurrently idempotent thunks into a retrospective wait-free one, with no copying of its representation and, when no senior is active, at essentially the native cost of the operation.
This paper addresses the lateral control of Autonomous and Connected Vehicles (ACVs) in a platoon executing an Emergency Lane Change (ELC) maneuver. These maneuvers are typically triggered by emergency signals from the front or rear of the platoon in response to the need to avoid obstacles or allow other vehicles to pass. The study assumes that ACVs maintain reliable connectivity, enabling each following vehicle to access GPS position traces of both the lead and immediately preceding vehicles in the platoon. We demonstrate that lateral string stability in the ACV platoon can be achieved using communicated information solely from the lead and preceding vehicles. Additionally, we present a lateral control framework for ACVs, which helps track a discretized preview of the trajectory constructed from the communicated data. This framework involves constructing two distinct trajectories based on the preview data from the lead and preceding vehicles, calculating the associated errors and lateral control actions for each, and then integrating these to generate a steering command. Numerical results validate the effectiveness of the proposed lateral control scheme.
VeriFast is one of the leading tools for semi-automated modular formal program verification. A central feature of VeriFast is its support for higher-order ghost code, which enables its support for expressively specifying fine-grained concurrent modules, without the need for the later modality. We present the first formalization and soundness proof for this aspect of VeriFast's logic, and we compare it both to Iris, a state-of-the-art logic for fine-grained concurrency which features the later modality, as well as to some recent proposals for Iris-like reasoning without the later modality.
Sequential lateration is a class of methods for multidimensional scaling where a suitable subset of nodes is first embedded by some method, e.g., a clique embedded by classical scaling, and then the remaining nodes are recursively embedded by lateration. A graph is a lateration graph when it can be embedded by such a procedure. We provide a stability result for a particular variant of sequential lateration. We do so in a setting where the dissimilarities represent noisy Euclidean distances between nodes in a geometric lateration graph. We then deduce, as a corollary, a perturbation bound for stress minimization. To argue that our setting applies broadly, we show that a (large) random geometric graph is a lateration graph with high probability under mild conditions, extending a previous result of Aspnes et al (2006).
The lateral diffusion of lipids within membrane is of paramount importance, serving as a central mechanism in numerous physiological processes including cell signaling, membrane trafficking, protein activity regulation, and energy transduction pathways. This review offers a comprehensive overview of lateral lipid diffusion in model biomembrane systems explored through the lens of neutron scattering techniques. We examine diverse models of lateral diffusion and explore the various factors influencing this fundamental process in membrane dynamics. Additionally, we offer a thorough summary of how different membrane-active compounds, including drugs, antioxidants, stimulants, and membrane proteins, affect lipid lateral diffusion. Our analysis unveils the intricate interplay between these additives and membranes, shedding light on their dynamic interactions. We elucidate that this interaction is governed by a complex combination of multiple factors including the physical state and charge of the membrane, the concentration of additives, the molecular architecture of the compounds, and their spatial distribution within the membrane. In conclusion, we briefly discuss the future directions
This chapter demonstrates how computational social science (CSS) tools are extending and expanding research on aging. The depth and context from traditionally qualitative methods such as participant observation, in-depth interviews, and historical documents are increasingly employed alongside scalable data management, computational text analysis, and open-science practices. Machine learning (ML) and natural language processing (NLP), provide resources to aggregate and systematically index large volumes of qualitative data, identify patterns, and maintain clear links to in-depth accounts. Drawing on case studies of projects that examine later life--including examples with original data from the DISCERN study (a team-based ethnography of life with dementia) and secondary analyses of the American Voices Project (nationally representative interview)--the chapter highlights both uses and challenges of bringing CSS tools into more meaningful dialogue with qualitative aging research. The chapter argues such work has potential for (1) streamlining and augmenting existing workflows, (2) scaling up samples and projects, and (3) generating multi-method approaches to address important question
The success of language models has inspired the NLP community to attend to tasks that require implicit and complex reasoning, relying on human-like commonsense mechanisms. While such vertical thinking tasks have been relatively popular, lateral thinking puzzles have received little attention. To bridge this gap, we devise BRAINTEASER: a multiple-choice Question Answering task designed to test the model's ability to exhibit lateral thinking and defy default commonsense associations. We design a three-step procedure for creating the first lateral thinking benchmark, consisting of data collection, distractor generation, and generation of adversarial examples, leading to 1,100 puzzles with high-quality annotations. To assess the consistency of lateral reasoning by models, we enrich BRAINTEASER based on a semantic and contextual reconstruction of its questions. Our experiments with state-of-the-art instruction- and commonsense language models reveal a significant gap between human and model performance, which is further widened when consistency across adversarial formats is considered. We make all of our code and data available to stimulate work on developing and evaluating lateral thin
This paper studies the design of a Model Predictive Controller (MPC) for integrated lateral stability, traction/braking control, and rollover prevention of electric vehicles intended for very high speed (VHS) racing applications. We first identify the advantages of a state-of-the-art dynamic model in that it includes rollover prevention into the MPC (a total of 8 states) and also linearizes the tire model prior to solving the MPC problem to save computation time. Then the design of a novel model predictive controller for lateral stability control is proposed aimed for achieving stable control at top speed significantly greater than typical highway speed limits. We have tested the new solution in simulation environments associated with the Indy Autonomous Challenge, where its real-world racing conditions include significant road banking angles, lateral position tracking, and a different suspension model of its Dallara Indy Lights chassis. The results are very promising with a low solver time in Python, as low as 50 Hz, and a lateral error of 30 cm at speeds of 45 m/s. Our open source code is available at: https: //github.com/jadyahya/Roll-Yaw-and-Lateral-Velocity-MPC/.
This article is dedicated to three fundamental papers on Markov Decision Processes and on control with incomplete observations published by Albert Shiryaev approximately sixty years ago. One of these papers was coauthored with O.V. Viskov. We discuss some of the results and some of many rich ideas presented in these papers and survey some later developments. At the end we mention some recent studies of Albert Shiryaev on Kolmogorov's equations for jump Markov processes and on control of continuous-time jump Markov processes.
Large language models are capable of leveraging both contextual and parametric knowledge but how they prioritize and integrate these sources remains underexplored. We introduce CoPE, a novel evaluation framework that systematically measures contextual knowledge (CK) and parametric knowledge (PK) across models and languages. Using our MultiWikiAtomic dataset in English, Spanish, and Danish, we analyze how large language models (LLMs) integrate context, prioritize information, and incorporate PK in open-ended question answering. Our analysis uncovers a phenomenon we call lost-in-the-later, where LLMs tend to overlook or deprioritize information that appears later in a given context, revealing a strong positional bias that affects contextual grounding. We further find that reasoning models, as well as non-reasoning models prompted with chain-of-thought (CoT), use context even less than non-reasoning models without CoT and fail to mitigate the lost-in-the-later effect. CoT prompting, in particular, results in lower recall and shorter responses, leading to degraded contextual grounding. Based on these insights, we design prompt-based methods to effectively leverage input context. A case
This paper aims to present a stability control strategy for quadruped robot under lateral impact with the help of lateral trot. We firstly propose five necessary conditions for keeping balance. The classical four-neuron Central Pattern Generator (CPG) network with Hopf oscillators is then extended to eight-neuron network with four more trigger-enabled neurons, which controls the lateral trot. With proper adjustment of network's parameters, such network can coordinate the lateral and longitudinal trot gait. Based on Zero Movement Point (ZMP) theory, the robot is modeled as an inverted pendulum to plan the Center of Gravity (CoG) position and calculate the needed lateral step length. The simulation shows that the lateral acceleration of the quadruped robot after lateral impact regains to the normal range in a short time. Comparison shows that the maximal lateral impact that robot can resist increases about 125% from 0.72g to 1.55g.
Atmospheric refraction modifies the apparent position of objects in the sky. We computed the lateral translation that is to be considered for short-range applications, such as wavefront sensing and meteor trajectories. We aim to calculate the lateral shift at each altitude and study its variation according to meteorological conditions and the location of the observation site. We also pay special attention to the chromatism of this lateral shift. We extracted the variation equations of refraction from the geometric tracing of a light ray path. A numerical method and a dry atmosphere model allowed us to numerically integrate the system of coupled equations. In addition to this, based on Taylor expansions, we established three analytic approximations of the lateral shift, one of which is the one already known in the literature. We compared the three approximations to the numerical solution. All these estimators are included in a Python 3.2 package, which is available online. Using the numerical integration estimator, we calculated the lateral shift values for any zenith angle including low elevations. The shift is typically around 3 m at a zenith angle of 45°, 10 m at 65°, and even 30
As a celebration of the \emph{Tractatus} 100th anniversary it might be worth revisiting its relation to the later writings. From the former to the latter, David Pears recalls that ``everyone is aware of the holistic character of Wittgenstein's later philosophy, but it is not so well known that it was already beginning to establish itself in the \emph{Tractatus}" (\emph{The False Prison}, 1987). From the latter to the former, Stephen Hilmy's (\emph{The Later Wittgenstein}, 1987) extensive study of the \emph{Nachlass} has helped removing classical misconceptions such as Hintikka's claim that ``Wittgenstein in the \emph{Philosophical Investigations} almost completely gave up the calculus analogy." Hilmy points out that even in the \emph{Investigations} one finds the use of the calculus/game paradigm to the understanding of language, such as ``in operating with the word" (Part I, §559) and ``it plays a different part in the calculus". Hilmy also quotes from a late (1946) unpublished manuscript (MS 130) ``this sentence has use in the calculus of language"), which seems to be compatible with ``asking whether and how a proposition can be verified is only a particular way of asking `How do