Search: “models”

Semi-Supervised Vision-Language-Action Model

arXiv:2606.21493v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models enable robots to predict actions directly from visual observations and language instructions, but adapting them to n

safetyarxiv-cs-cv

23 Jun 2026

VegSim: A Geospatial World Model for Scenario-Conditioned Vegetation Simulation

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DGX agent

arXiv:2606.21961v1 Announce Type: new Abstract: Vegetation monitoring under climate stress requires answering not only how it will evolve given the expected weather, but how it would respond to altern

applicationsarxiv-cs-lg

23 Jun 2026

What Does a Chemical Language Model Know About Molecules?

arXiv:2606.23443v1 Announce Type: new Abstract: Chemical language models (cLMs) are widely assumed to learn surface-level syntactic patterns rather than learning meaningful molecular semantics. Here,

tutorialsarxiv-cs-lg

23 Jun 2026

DAM-VLA: Decoupled Asynchronous Multimodal Vision Language Action model

arXiv:2606.12105v1 Announce Type: cross Abstract: Vision-language-action (VLA) models inherit a shared synchronous clock from vision-language pretraining, processing every input at one rate. This is m

applicationsarxiv-cs-cv

Kalman Linear Attention: Parallel Bayesian Filtering For Efficient Language Modelling and State Tracking

arXiv:2602.10743v2 Announce Type: replace Abstract: State-space language models such as Mamba and gated linear attention (GLA) offer linear-complexity, parallelisable alternatives to transformers, but

Model-Based and Data-Driven Hierarchical Control and Topology Co-Design for Robust Networked Systems

arXiv:2606.11596v1 Announce Type: cross Abstract: In this paper, we consider a class of networked systems comprising an interconnected set of linear subsystems, disturbance inputs, and performance out

local-aiarxiv-cs-ai

Physics-Driven Spatiotemporal Modeling for AI-Generated Video Detection

arXiv:2510.08073v2 Announce Type: replace Abstract: AI-generated videos have achieved near-perfect visual realism (e.g., Sora), urgently necessitating reliable detection mechanisms. However, detecting

researcharxiv-cs-cv

A Navigable Manifold of Hypothesized Consciousness-Spectrum States in Language Model Representations

arXiv:2606.09894v1 Announce Type: cross Abstract: Across contemplative, philosophical, and psychological accounts, human consciousness is often described along a similar spectrum, ranging from reactiv

local-aiarxiv-cs-cl

Democratising Camera Trap AI: An Open-Source Model for Detecting UK Mammals

arXiv:2606.10940v1 Announce Type: cross Abstract: Camera traps have become a cornerstone of biodiversity monitoring, but the artificial intelligence that turns vast quantities of images into usable ec

Dynamics of Adversarial Attacks on Large Language Model-Based Search Engines

arXiv:2501.00745v3 Announce Type: replace-cross Abstract: The increasing integration of Large Language Model (LLM) based search engines has transformed the landscape of information retrieval. However,

Integrating Biological-Informed Recurrent Neural Networks for Glucose-Insulin Dynamics Modeling

arXiv:2503.19158v3 Announce Type: replace Abstract: Type 1 Diabetes (T1D) management is a complex task due to many variability factors. Artificial Pancreas (AP) systems have alleviated patient burden

Interpreting and Steering a Text-to-Speech Language Model with Sparse Autoencoders

arXiv:2606.10029v1 Announce Type: cross Abstract: Language models increasingly serve as the backbone of text-to-speech (TTS) systems, yet we understand little about the representations they build when

Model-Based Reinforcement Learning in Discrete-Action Non-Markovian Reward Decision Processes

arXiv:2512.14617v2 Announce Type: replace-cross Abstract: Many practical decision-making problems involve tasks whose success depends on the entire system history, rather than on achieving a state wit

MODIP: Efficient Model-Based Optimization for Diffusion Policies

arXiv:2606.10825v1 Announce Type: new Abstract: Diffusion policies (DPs) have emerged as expressive policy representations for robot learning, often used with imitation learning methods such as behavi

safetyarxiv-cs-lg

Vision-Assisted Foundation Model for Solving Multi-Task Vehicle Routing Problems

arXiv:2606.10431v1 Announce Type: cross Abstract: Multi-task vehicle routing problems play a critical role in enhancing efficiency across various industries and service sectors. These problems consist

tutorialsarxiv-cs-ai

Brain2Text Decoding Model Reveals the Neural Mechanisms of Visual Semantic Processing

arXiv:2503.22697v3 Announce Type: replace-cross Abstract: Decoding sensory experiences from neural activity to reconstruct human-perceived visual stimuli and semantic content remains a challenge in ne

GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series

arXiv:2606.07725v1 Announce Type: cross Abstract: Displacement time series from Global Navigation Satellite Systems (GNSS) are essential for a wide range of applications, including monitoring tectonic

Modeling Components and Connections in Cyber-Physical Systems

arXiv:2606.09645v1 Announce Type: new Abstract: Text based configuration files for cyber-physical systems show the hierarchy of component modules well but often hide the details of connections and int

MotionVLA: Injecting Geometric Motion into Vision-Language-Action Model

arXiv:2606.08288v1 Announce Type: new Abstract: Vision-language-action (VLA) models increasingly condition robot policies on history, depth, or 4D features to resolve ambiguity in long-horizon manipul

NoRD: A Data-Efficient Vision-Language-Action Model that Drives without Reasoning

arXiv:2602.21172v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are advancing autonomous driving by replacing modular pipelines with unified end-to-end architectures. However,

SEF-CLGC at SemEval-2026 Task 11: Logical Notation Impact on Language Model Performance

arXiv:2606.09157v1 Announce Type: cross Abstract: This paper revisits our pipeline called Syllogistic Evaluation Framework-Common Logic Grammar Construction (SEF-CLGC). We combine formal logical notat

STELLAR: Spatio-Temporal Environmental Learning with Latent Alignment and Refinement for Long-Tailed Species Distribution Modeling

arXiv:2606.08484v1 Announce Type: cross Abstract: Joint Species Distribution Modeling (JSDM) is a key enabler for biodiversity monitoring and conservation planning. However, accurate JSDM faces two co

Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Records

arXiv:2606.08903v1 Announce Type: new Abstract: Synthetic healthcare data are widely proposed as privacy-preserving substitutes for real patient data, yet their evaluation remains dominated by statist

applicationsarxiv-cs-lg

On orbital stabilization of a circular motion primitive for a dynamic extension of the Dubins car model

arXiv:2606.07449v1 Announce Type: cross Abstract: This paper addresses orbital stabilization of a circular motion primitive for a dynamic extension of the Dubins car model within a transverse-lineariz

8 Jun 2026

Gradient descent at the Edge of Stability: free energy model and kinetic description of the two-layer network

arXiv:2606.05326v1 Announce Type: cross Abstract: We study the dynamics of gradient descent in the Edge of Stability regime, where the learning rate is large enough to induce persistent oscillations i

6 Jun 2026

A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing

arXiv:2606.05330v1 Announce Type: new Abstract: Large language models can shift human beliefs across high-stakes domains, but most persuasion studies rely on pre/post belief change. These endpoint mea

researcharxiv-cs-cl

5 Jun 2026

Amortized Nonlinear Model Predictive Control

arXiv:2606.05840v1 Announce Type: cross Abstract: Nonlinear Model Predictive Control requires solving a constrained nonlinear program (NLP) in real-time at every sampling instant, a computational bott

5 Jun 2026

Temporal Preference Concepts and their Functions in a Large Language Model

arXiv:2606.05194v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly being deployed to make decisions that require trading off near-term gains against long-term consequences

local-aiarxiv-cs-cl

5 Jun 2026

GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling

arXiv:2606.04516v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) significantly advances LLM reasoning, yet it faces a dilemma: standard supervised scaling is thr

tutorialsarxiv-cs-ai

4 Jun 2026

How Users Understand Robot Foundation Model Performance through Task Success Rates and Beyond

arXiv:2602.03920v2 Announce Type: replace Abstract: Robot Foundation Models (RFMs) represent a promising approach to developing general-purpose home robots. Given the broad capabilities of RFMs, users

4 Jun 2026

ReSGA: A Large Tail Risk Model for Learning Value-at-Risk and Expected Shortfall

arXiv:2606.04576v1 Announce Type: cross Abstract: Learning Value-at-Risk (VaR) and Expected Shortfall (ES) is important for managing financial risks effectively. Existing approaches with limited param

4 Jun 2026

An Attention-Based Denoising Model for Diffusion Weighted Imaging

arXiv:2606.03903v1 Announce Type: new Abstract: Diffusion-weighted imaging (DWI) is used for whole-body cancer screening, but it typically requires a long acquisition time. When the scan time is reduc

researcharxiv-cs-cv

Are Common Substructures Transferable? Riemannian Graph Foundation Model with Neural Vector Bundles

arXiv:2606.03270v1 Announce Type: cross Abstract: Foundation models have sparked a revolution via a pretraining-adaptation paradigm, with recent efforts extending this success to graphs. Unlike other

Causal Evidence of Stack Representations in Modeling Counter Languages Using Transformers

arXiv:2606.03398v1 Announce Type: cross Abstract: Formal languages have proven to be effective conduits to understand the inner mechanisms of transformers. Past work has shown that transformers traine

tutorialsarxiv-cs-ai

Distill-then-Replace: Efficient Task-Specific Hybrid Attention Model Construction

arXiv:2601.11667v2 Announce Type: replace-cross Abstract: Transformer architectures deliver state-of-the-art accuracy via dense full-attention, but their quadratic time and memory complexity with resp

local-aiarxiv-cs-ai

Hardware

GRZO: Group-Relative Zeroth-Order Optimization for Large Language Model Fine-Tuning

arXiv:2606.02857v1 Announce Type: cross Abstract: Zeroth-order (ZO) optimization is a memory-efficient alternative to backpropagation for fine-tuning large language models, but its deployment is limit

hardwarearxiv-cs-ai

Physical Plausibility Reasoning via HCM-GRPO: Empowering Compact Model for Superior Performance

arXiv:2511.10055v2 Announce Type: replace Abstract: The performance of image generation has been significantly improved in recent years. However, the study of image screening is rare, and its performa

safetyarxiv-cs-cv

ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction

arXiv:2502.02748v4 Announce Type: replace Abstract: Predicting properties of crystals from their structures is a fundamental yet challenging task in materials science. Unlike molecules, crystal struct

local-aiarxiv-cs-lg

Agents

Reinforcement Learning from Cross-domain Videos with Video Prediction Model

arXiv:2606.03201v1 Announce Type: cross Abstract: Reinforcement learning from expert videos across visually distinct domains is challenging due to the absence of reward signals and the presence of dom

agentsarxiv-cs-ai

Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling

arXiv:2606.03102v1 Announce Type: new Abstract: Test-time scaling improves the reasoning performance of large language models but incurs substantial cost in both total computation and latency. Existin

researcharxiv-cs-cl

Hardware

Speedrunning Tabular Foundation Model Pretraining

arXiv:2606.03681v1 Announce Type: new Abstract: Pretraining cost is a major bottleneck for research on tabular foundation models, slowing the iteration cycle for new architectures, priors, and optimiz

hardwarearxiv-cs-lg

Agents

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection

arXiv:2606.02812v1 Announce Type: new Abstract: Modeling patient trajectories from longitudinal electronic health records (EHRs) requires reasoning over sparse, noisy, and long-context multimodal sequ

agentsarxiv-cs-ai

ART: Attention Run-time Termination for Efficient Large Language Model Decoding

arXiv:2606.00024v1 Announce Type: new Abstract: Long-context decoding in Large Language Models (LLMs) is severely constrained by the memory bandwidth required to fetch the extensive Key-Value (KV) cac

researcharxiv-cs-cl

Cellular Sheaf Neural Operators for Structure-Preserving Surrogate Modeling of Constrained PDEs

arXiv:2606.00937v1 Announce Type: new Abstract: Neural operators provide fast surrogate models for PDE simulations, but standard architectures often treat geometry and discretization as secondary to f

safetyarxiv-cs-lg

EnergyMamba: An Uncertainty-Aware Graph-Enhanced Selective State Space Model for Energy Consumption Prediction

arXiv:2606.00506v1 Announce Type: new Abstract: Energy consumption prediction is essential for efficient grid management, demand-side optimization, and sustainable energy planning. Although advanced m

applicationsarxiv-cs-ai

Hot-Start Chinese Language Modeling:Visual Glyphs Accelerate Sample-Efficient Learning

arXiv:2601.09566v4 Announce Type: replace-cross Abstract: In this work, we study whether rendering Chinese characters as visual glyph images, rather than discrete token IDs as mainstream LLMs do, prov

ImagineUAV: Aerial Vision-Language Navigation via World-Action Modeling and Kinodynamic Planning

arXiv:2606.01205v1 Announce Type: new Abstract: Vision-language navigation (VLN) for UAVs demands grounding free-form instructions into 6-DoF flight under partial observability. While Vision-Language-

applicationsarxiv-cs-ro

Mitigating Perceptual Judgment Bias in Multimodal LLM-as-a-Judge via Perceptual Perturbation and Reward Modeling

arXiv:2606.02578v1 Announce Type: cross Abstract: Recent multimodal large language models have demonstrated strong reasoning ability, yet their reliability as automated evaluators remains limited by a