Search: “models”

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,

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Exact Functional ANOVA Decomposition for Categorical Inputs Models

DGX agent

arXiv:2603.02673v2 Announce Type: replace-cross Abstract: Functional ANOVA offers a principled framework for interpretability by decomposing a model's prediction into main effects and higher-order int

researcharxiv-cs-lg

10 Jun 2026

Flow Control: Steering Vision-Language-Action Models with Simple Real-Time Inputs

arXiv:2606.10180v1 Announce Type: cross Abstract: We introduce flow control of vision-language-action (VLA) models, a simple and effective way to steer VLA actions in real-time through generic inputs,

Local Ai

Geometric Coastline Localization using Vision-Language Models

arXiv:2606.10468v1 Announce Type: new Abstract: Coastline detection in remote sensing imagery is commonly formulated as a pixel-wise segmentation problem, where the final coastline is extracted from a

local-aiarxiv-cs-cv

HiMem-WAM: Hierarchical Memory-Gated World Action Models for Robotic Manipulation

arXiv:2606.10363v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a new powerful paradigm for embodied intelligence, learning action-relevant visual dynamics that significantl

applicationsarxiv-cs-ro

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

Predicting Future Behaviors in Reasoning Models Enables Better Steering

arXiv:2606.11172v1 Announce Type: new Abstract: Deployed large reasoning models (LRMs) often behave unexpectedly. Test-time steering controls LRM outputs by intervening on their hidden representations

Prefilling-dLLM: Predictive Prefilling for Long-Context Inference in Diffusion Language Models

arXiv:2606.10537v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) re-encode the entire prefix at every denoising step, causing recomputation that scales quadratically with contex

researcharxiv-cs-cl

Speaker Group Encoding in Self-supervised Speech Recognition Models

arXiv:2606.10654v1 Announce Type: new Abstract: We investigate what self-supervised speech recognition models (S3Ms) learn about speaker groups (SGs). We examine several states of S3Ms: pretrained, fi

safetyarxiv-cs-cl

Time Series as Language: A Universal Tokenizer for General-Purpose Time Series Foundation Models

arXiv:2606.09861v1 Announce Type: cross Abstract: While Next-Token Prediction (NTP) has unified LLM pretraining, its adaptation to unbounded, continuous time series (TS) remains open. To bridge the ga

Towards Diverse Scientific Hypothesis Search with Large Language Models

arXiv:2606.10587v1 Announce Type: cross Abstract: Large language models (LLMs) are on the rise for accelerating scientific discovery, most recently in advanced tasks such as generating valid scientifi

VeriSpace: Spatially Grounded Action Verification for Vision-Language-Action Models

arXiv:2606.10568v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong promise for robotic manipulation, but their reliability at test time remains limited by one-shot a

applicationsarxiv-cs-ro

Tutorials

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

CAPruner: Conceptual-Adjacent Scene Graph Pruner for Enhancing 3D Spatial Reasoning of Large Language Models

arXiv:2606.07529v1 Announce Type: cross Abstract: Large language models (LLMs) have recently been applied to 3D vision-language (3D-VL) tasks, which require spatial reasoning to identify target object

Local Ai

Collaborative Edge-to-Server Inference for Vision-Language Models

arXiv:2512.16349v2 Announce Type: replace-cross Abstract: We propose a collaborative edge-to-server inference framework for vision-language models (VLMs) that reduces communication cost while maintain

local-aiarxiv-cs-ai

FAWAM: Force-Aware World Action Models for Closed-Loop Contact-Rich Manipulation

arXiv:2606.08555v1 Announce Type: new Abstract: Force signals provide critical interaction cues for contact-rich robotic manipulation. However, existing methods mostly use force as an additional obser

applicationsarxiv-cs-ro

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

Human-Centered Benchmarking of Driver Monitoring Models

arXiv:2606.08123v1 Announce Type: cross Abstract: Vision-based driver monitoring systems are increasingly deployed in safety-critical intelligent transportation settings, yet they are almost always co

Local Ai

Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction

arXiv:2606.08751v1 Announce Type: new Abstract: Accurate quantification and uptake measurement in PET are critical for assessing disease progression and supporting clinical decision-making. While high

local-aiarxiv-cs-cv

Liberating LLM Capabilities in Full-Duplex Speech Models

arXiv:2606.07547v1 Announce Type: cross Abstract: Speech-based large language models are typically constrained to spoken replies, which limits their user-facing outputs to what can be verbalized and s

mllm-shap: A Shapley Value Explainability Platform for Text-Audio Multimodal Large Language Models

arXiv:2606.07531v1 Announce Type: cross Abstract: We introduce mllm-shap, an open-source Python framework designed to extend Shapley Value (SV) explainability from text-only Large Language Models to M

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

researcharxiv-cs-ro

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

researcharxiv-cs-ro

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,

SAW: Stage-Aware Dynamic Weighting for Multi-Objective Reinforcement Learning in Large Language Models

arXiv:2606.07705v1 Announce Type: cross Abstract: Although multi-objective reinforcement learning (MORL) is central to aligning large language models with complex human preferences, the prevailing pra

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

Sparrow: Sparse Rollout for Stable and Efficient Long-context RL of Large Language Models

arXiv:2606.08446v1 Announce Type: cross Abstract: Despite being powerful, reinforcement learning with verifiable rewards (RLVR) induces extremely long COT, making it computationally expensive. Since R

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

The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models

arXiv:2601.15165v4 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) break the rigid left-to-right constraint of traditional LLMs, enabling token generation in arbitrary o

Zero Touch Predictive Orchestration: Automating Time-Series Models for the Cloud-Edge Continuum

arXiv:2606.09787v1 Announce Type: new Abstract: The Cloud-Edge Continuum (CEC) enables latency-critical applications by distributing resources to the far edge, but its extreme volatility makes proacti

Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models

arXiv:2606.07107v1 Announce Type: new Abstract: Most vision-language-action (VLA) models map observations directly to actions without explicit intermediate planning, which limits performance on long-h

safetyarxiv-cs-ro

DataEvolver: Automatic Data Preparation for Large Language Models through Multi-Level Self-Evolving

arXiv:2606.07001v1 Announce Type: cross Abstract: High-quality training data is essential to large language models (LLMs) and typically requires extensive and costly manual curation. Existing automati

FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models

arXiv:2606.06547v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) refine tokens iteratively but commit them irreversibly, leading to a 'stability lag' where early decisions rem

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

researcharxiv-cs-ro

Tutorials

SS-TPT: Stability and Suitability-Guided Test-Time Prompt Tuning for Adversarially Robust Vision-Language Models

arXiv:2606.06943v1 Announce Type: cross Abstract: Vision-language models (VLMs) such as CLIP achieve strong zero-shot recognition but remain highly fragile under adversarial perturbations. Recent test

tutorialsarxiv-cs-ai

Sycophantic Praise: Evaluating Excessive Praise in Language Models

arXiv:2606.07441v1 Announce Type: new Abstract: Sycophancy in language models is typically studied as excessive agreement or validation, while explicit praise and flattery have received comparatively

safetyarxiv-cs-cl

The Identity Trap in EEG Foundation Models: A Diagnostic Audit

arXiv:2606.06647v1 Announce Type: new Abstract: Objective. EEG foundation models (FMs) report strong accuracy on clinical resting-state EEG. However, high accuracy under subject-disjoint cross-validat

Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission

arXiv:2606.06273v1 Announce Type: cross Abstract: Lossless pixel-level image transmission is a fundamental regime beyond semantic communications, because exact recovery requires both accurate symbol p

Amortizing Federated Adaptation: Hypernetwork Driven LoRA for Personalized Foundation Models

arXiv:2606.06154v1 Announce Type: new Abstract: Federated fine-tuning of foundation models using Low-Rank Adaptation (LoRA) offers a communication efficient solution for distributed learning. However,

Tutorials

GOTabPFN: From Feature Ordering to Compact Tokenization for Tabular Foundation Models on High-Dimensional Data

arXiv:2606.05441v1 Announce Type: cross Abstract: We investigate how to make small tabular foundation models effective for High-Dimensional, Low-Sample Size (HDLSS) tabular prediction without retraini

tutorialsarxiv-cs-ai

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

Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction

arXiv:2606.06303v1 Announce Type: cross Abstract: Controllable generation with discrete diffusion models is often hindered by high computational overhead or the need for retraining. In this paper, we

The Score Hamiltonian: Mapping Diffusion Models to Adiabatic Transport

arXiv:2606.05217v1 Announce Type: cross Abstract: We exhibit an exact correspondence between sampling with score-based diffusion models and adiabatic transport of ground states for a family of Schrodi