Search: “framework”

arXiv:2609.29906v1 Announce Type: new Abstract: The estimation of Annual Average Daily Traffic (AADT) is vital for transportation planning and infrastructure maintenance, yet obtaining accurate values

applicationsarxiv-cs-lg

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Research

Spooftral: Can Voxtral Audio-Language Model Detect Speech Spoofing?

DGX agent

arXiv:2609.28713v1 Announce Type: cross Abstract: Self-supervised learning (SSL) countermeasures (CMs) have shown strong performance in recent years. However, they often show degraded performance whil

researcharxiv-cs-cl

25 Sept 2026

STRAND: Benchmarking and Improving Object-Centric Spatio-Temporal Monitoring in Video Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.29607v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) have advanced video understanding, they remain highly prone to hallucinations in dynamic scenes. We arg

Tag-Aware Structured Text Translation: Towards a Systematic Understanding

arXiv:2609.29131v1 Announce Type: cross Abstract: Internet texts are replete with format tags that carry structural, semantic, and functional meaning. Current large language model (LLM)-based translat

Tutorials

ToCo-Mesh: Topology-Consistent Dynamic Mesh Reconstruction via Adaptive Tessellation and Surface-Aligned 2DGS

arXiv:2609.29529v1 Announce Type: cross Abstract: Reconstructing dynamic meshes with consistent topology from multi-view temporal images remains a challenge. Existing approaches typically face a dilem

tutorialsarxiv-cs-cv

Unraveling the cognitive patterns of Large Language Models through module communities

arXiv:2508.18192v2 Announce Type: replace Abstract: Large Language Models (LLMs) have reshaped our world with significant advancements in science, engineering, and society through applications ranging

researcharxiv-cs-ai

UNWIND: Any-Length Facial Video for Stress Detection without Temporal Windowing

arXiv:2609.29553v1 Announce Type: cross Abstract: Automatic stress recognition from facial video provides a non-contact approach for affective monitoring. However, most existing video-based methods di

researcharxiv-cs-ai

When Honesty is Not Enough in AI Debate

arXiv:2609.29189v1 Announce Type: new Abstract: Scalable oversight aims to verify the behaviour of agents whose capabilities exceed those of their overseers. AI debate has been proposed as an oversigh

A Discrepancy-Based Perspective on Dataset Condensation

arXiv:2509.10367v2 Announce Type: replace Abstract: Given a dataset of finitely many elements T = {mathbf{x}_i}_{i = 1}^N, the goal of dataset condensation (DC) is to construct a synthetic dataset S =

AI-Driven Neural Surrogates for In Silico Design of Cognitive-Affective Neuromodulation Targets

arXiv:2609.27729v1 Announce Type: cross Abstract: In neuropsychiatry, the primary goal is often not only to decode brain activity but to change it, for example to lessen a negative affective bias or a

Backdoors in Learning-Based Industrial Robotic Arm Manipulation: An Empirical Security Study

arXiv:2609.26868v1 Announce Type: new Abstract: Learning-based models (e.g., visuomotor and Vision-Language-Action (VLA)) are increasingly explored for industrial robotic manipulation, where model pre

researcharxiv-cs-ro

BronchoTop: Bronchoscopy Navigation via RGB-Only Topological Localization

arXiv:2609.28328v1 Announce Type: new Abstract: Accurate localization of the bronchoscope within the bronchial tree is essential for clinicians to be able to reach target lesions, perform biopsies and

local-aiarxiv-cs-cv

Controlled Attribute-Specific Summarization of Interrogative Dialogues

arXiv:2609.28004v1 Announce Type: cross Abstract: Effective summarization of interrogative dialogues is a critical task in forensic and investigative settings, requiring high factual accuracy, coheren

COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation

arXiv:2609.26853v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved remarkable results across various benchmarks, their alignment with normative values often results in

Cross-Modal Contrastive Learning from Histopathology and CT for Automated Renal Cell Carcinoma Grading

arXiv:2609.26920v1 Announce Type: cross Abstract: Background: Clear cell renal cell carcinoma (ccRCC) exhibits substantial clinical heterogeneity, and accurate grade assessment is essential for risk s

Diff-RF: Mutually Reinforced Image Registration and Fusion via Degradation-Aware Learning

arXiv:2609.28235v1 Announce Type: new Abstract: Image registration and fusion aim to establish spatial correspondences from misaligned multi-modal source images, and integrate complementary informatio

safetyarxiv-cs-cv

DUGM-R: Uncertainty-Aware Dynamic Grid Mapping and Risk-Triggered Recovery for Learned Local Navigation

model-releasesarxiv-cs-ro

arXiv:2609.27338v1 Announce Type: new Abstract: Learned local navigation in crowded indoor environments is sensitive to how dynamic obstacle motion is represented, while collision-prone behaviour may

FFM-CP: Cross-Backbone Fusion of Vision-Language Foundation Models for Few-Shot Computational Pathology

arXiv:2609.27710v1 Announce Type: new Abstract: Pathology vision-language foundation models vary in performance across diseases and tasks, with no single model consistently performing best. The high c

safetyarxiv-cs-cv

Fine-Tune, Then Rectify

arXiv:2511.19486v3 Announce Type: replace-cross Abstract: Driven by recent advances in artificial intelligence, a growing literature has demonstrated the potential of using large language models (LLMs

researcharxiv-cs-ai

Finite-Sample Probabilistic Safety Certification for AI-Based Grid-Edge Coordination

arXiv:2609.28182v1 Announce Type: new Abstract: Coordinating large population of flexible grid-edge devices can alleviate the need for time-consuming and capital-intensive network upgrades, and AI-bas

From greenhouse climate to individual leaves: an organ-resolved model of lettuce growth

arXiv:2609.27118v1 Announce Type: new Abstract: Greenhouse climate management aims to improve crop production while limiting energy use. This requires knowing how a crop will respond before conditions

local-aiarxiv-cs-cv

GaussianDS: Depth-supervised Semantic Gaussian Splatting for Scene Understanding

arXiv:2609.27850v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an efficient representation for 3D reconstruction, and recent extensions attach semantic attributes to Gaussians for open

safetyarxiv-cs-cv

Gray-Box Model Predictive Control for Articulated Dump Trucks via Gaussian Process Learning of Sideslip

arXiv:2609.27597v1 Announce Type: new Abstract: The growing demand for automation in the mining industry, particularly for the autonomous operation of articulated dump trucks (ADTs), has drawn increas

Invisible in Space, Visible in Time: Motion Vision CAPTCHA against GUI Agents

model-releasesarxiv-cs-cv

arXiv:2609.27461v1 Announce Type: new Abstract: Most existing visual CAPTCHAs remain spatially solvable: the required information is exposed by static appearance, local structure, and interface state.

Learning a Speed-adaptive Hip Exoskeleton Control Policy Via Sim-to-real Reinforcement Learning

arXiv:2609.28027v1 Announce Type: new Abstract: Providing personalized exoskeleton assistance across varying walking speeds remains challenging. Existing online optimization methods are sample-ineffic

safetyarxiv-cs-ro

Learning to Remember: Attentive Reinforcement Learning for Edge Serverless Autoscaling

arXiv:2603.28790v2 Announce Type: replace-cross Abstract: In edge computing, the stochastic and bursty nature of serverless workloads challenges autonomous resource orchestration. Traditional reactive

safetyarxiv-cs-lg

Live Assistant: Learning Whether, When, and Whom to Assist in Real-World Live Social Streams

model-releasesarxiv-cs-lg

arXiv:2609.27303v1 Announce Type: new Abstract: Livestreams are long-lasting interactive environments where audiovisual content, viewer activity, host behavior, and platform signals evolve together, c

Look Where It Matters: High-Resolution Crops Retrieval for Efficient VLMs

arXiv:2603.16932v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) typically process images at a native high-resolution, forcing a trade-off between accuracy and computational eff

agentsarxiv-cs-ai

Math Reasoning in LLMs is Organized by Approach, Not Topic

model-releasesarxiv-cs-ai

arXiv:2609.27041v1 Announce Type: new Abstract: Mathematical reasoning benchmarks are typically organized by topic, but language models may organize their internal computation by reusable reasoning ap

Memory That Changes Action Is Not Memory That Guides It: Counterfactual Auditing of History-Conditioned Robot Policies

arXiv:2609.27247v1 Announce Type: new Abstract: A robot returning a block to its origin tray may encounter two task-consistent pasts that reconverge to the same current input but warrant different act

safetyarxiv-cs-ro

Policy-as-Skill: Governed LLM Decision Support with Evidence, Deterministic Control, and Audit

arXiv:2609.27087v1 Announce Type: new Abstract: Organizations increasingly use LLMs for policy, compliance, risk, and operational decision support, requiring evidence validation, review routing, versi

Quantum score matching with applications to learning thermal states

model-releasesarxiv-cs-lg

arXiv:2609.28391v1 Announce Type: cross Abstract: Score matching has driven major advances in classical generative learning by enabling models to learn from data without evaluating intractable normali

Reliable Fusion of Conflicting Experts

arXiv:2609.27913v1 Announce Type: new Abstract: We study the problem of aggregating opinions from multiple black-box experts in noisy, conflict-prone settings where expert reliability varies across in

RoboCafe in the Open: Interaction Continuity in Long-Term Public Human-Robot Interaction

arXiv:2609.27475v1 Announce Type: new Abstract: As robots remain in public spaces over extended periods, they must maintain interaction continuity by preserving and correctly applying context as peopl

Safety-Filtered Distributed Koopman-MPC

arXiv:2609.27463v1 Announce Type: new Abstract: Distributed model predictive control (DMPC) often constructs both predictions and collision constraints from neighbor trajectories, so packet loss can r

local-aiarxiv-cs-ro

Tractable Reinforcement Learning for Full Class of Signal Temporal Logic Specifications Using Spatiotemporal Tube Reward

arXiv:2609.28396v1 Announce Type: new Abstract: This paper addresses the control problem for robotic systems, including non-holonomic and underactuated platforms operating under unknown dynamics and s

Transfer Learning with Conformalized Quantile Regression for Solar PV Forecasting Under Load-Shedding-Driven Data Scarcity

arXiv:2609.26959v1 Announce Type: new Abstract: Solar photovoltaic (PV) forecasting in regions affected by load shedding is challenging because reliable historical observations are scarce. This study

Applications

Untangling the Geometry and Speed for RF Sensing Spectrograms

arXiv:2609.26960v1 Announce Type: cross Abstract: A fundamental challenge in RF sensing is that Doppler signatures observed by a link entangle the target's motion with the sensing geometry, resulting

applicationsarxiv-cs-lg

VLMs Can Describe, But Not Measure: Object-Centric Scene Understanding for Robotic Manipulation

arXiv:2609.28184v1 Announce Type: cross Abstract: Robotic operation in previously unseen environments requires both semantic understanding and reliable metric information. While vision--language model

local-aiarxiv-cs-cv

Adaptive Helpfulness-Harmlessness Alignment with Preference Vectors

arXiv:2504.20106v4 Announce Type: replace Abstract: Ensuring that large language models (LLMs) are both helpful and harmless is a critical challenge, as overly strict constraints can lead to excessive

safetyarxiv-cs-lg

Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning

arXiv:2511.16043v2 Announce Type: replace Abstract: Large Language Model (LLM) Agents, often trained with Reinforcement Learning (RL), are constrained by a dependency on human-curated data, limiting s

agentsarxiv-cs-lg

An Accurate and Interpretable Hyper Graph Neural Network for GBM Survival Prediction

arXiv:2609.25088v1 Announce Type: cross Abstract: Survival prediction for glioblastoma multiforme (GBM) demands models that are both accurate and interpretable, yet existing approaches treat these obj

APEXA: Execution-Integrity Enforcement for Multi-Agent LLM Automation of Synchrotron Data Reduction

model-releasesarxiv-cs-ai

arXiv:2609.24165v1 Announce Type: new Abstract: Synchrotron data reduction, detector calibration followed by azimuthal integration of terabyte-scale diffraction series, is a multi-step, expert-bound b

ARAFA: An LLM-Generated Arabic Fact-Checking Dataset

arXiv:2609.25833v1 Announce Type: new Abstract: Automatic fact-checking poses a significant challenge in Arabic natural language processing due to the scarcity of datasets and resources. In this manus

researcharxiv-cs-cl

Behavior is Not Enough: A Mechanism-Based Evaluation of Social Norm Emergence in LLM Societies

arXiv:2609.26481v1 Announce Type: cross Abstract: Social norms cannot be identified from behavior alone: the same cooperative equilibrium may reflect shared expectations, strategic incentives, or simp

agentsarxiv-cs-cl

Applications

BridgeShield: Risk-Aware Graph Modeling for Cross-Chain Bridge Attack Detection

arXiv:2508.20517v2 Announce Type: replace-cross Abstract: Cross-chain bridges enable asset and state transfers across heterogeneous blockchains, but their complex cross-domain interactions introduce n

applicationsarxiv-cs-ai

CacheDyG: Decoupling Temporal Propagation for Efficient Dynamic Graph Learning

model-releasesarxiv-cs-lg

arXiv:2609.25814v1 Announce Type: new Abstract: Dynamic graphs are widely used to model time-evolving relational systems in real-world applications. Dynamic graph neural networks provide an effective

CDKF-Track: Cluster-aware Data-Driven Kalman Filtering for Cooperative 3D Multi-Object Tracking

arXiv:2609.25668v1 Announce Type: new Abstract: Multi-Object Tracking (MOT) is essential for EdgeAI perception systems, where accurate object localization and reliable identification enable safe decis