Search: “framework”

ActionUNet: Improving Robustness of VLA Models with Efficient Multi-scale Fine-tuning

arXiv:2609.34982v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown great promise for robotic manipulation by mapping multi-modal semantics to physical actions. However, thi

applicationsarxiv-cs-cv

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Active 3D weaves for load-bearing and damage-resilient locomotion

DGX agent

arXiv:2609.32099v1 Announce Type: new Abstract: The craft of weaving, where different materials are interlaced, has tremendous potential for creating active and functional systems for use in soft robo

applicationsarxiv-cs-ro

29 Sept 2026

Active Data Acquisition with Side Information via Discrete Diffusion Priors

arXiv:2609.32252v1 Announce Type: cross Abstract: Acquiring data is costly: higher measurement fidelity costs power and storage and risks collecting irrelevant content, while aggressive cost reduction

Tutorials

Addressing Spatial Indistinguishability in Spatiotemporal Prediction via Optimal Transport-Guided Masking

arXiv:2609.35021v1 Announce Type: new Abstract: Spatiotemporal prediction aims to learn discriminative representations from correlated temporal signals over spatial structures for accurate future infe

tutorialsarxiv-cs-lg

Adjoint-based shape optimization of a ship hull using a Conditional Variational Autoencoder (CVAE) assisted propulsion surrogate model

arXiv:2602.14907v3 Announce Type: replace-cross Abstract: Adjoint-based shape optimization of ship hulls is a powerful tool for addressing high-dimensional design problems in naval architecture, parti

Advancing Video-Text Pretraining with Multi-View Captions

arXiv:2609.35090v1 Announce Type: new Abstract: Video-text pretraining has achieved remarkable progress through the scaling of models and datasets, yet the quality of language supervision remains unde

Adversarial Consistency-Guided Representation Learning for Multi-view Clustering

arXiv:2609.35212v1 Announce Type: new Abstract: Multi-view clustering aims to capture cross-view consistency while exploiting view-specific information. However, shared representations learned to capt

Adversarial Reward Auditing for Active Detection and Mitigation of Reward Hacking

arXiv:2602.01750v2 Announce Type: replace-cross Abstract: Reinforcement Learning from Human Feedback (RLHF) remains vulnerable to reward hacking, where models exploit spurious correlations in learned

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling

arXiv:2605.05586v2 Announce Type: replace Abstract: High-fidelity CFD is essential for aerodynamic design, but repeated simulations are computationally expensive, motivating surrogate models for rapid

AG-CoT: Verified Algorithmic Traces for LLM Program Synthesis on Clifford Circuits

arXiv:2609.33192v1 Announce Type: new Abstract: Scientific code generation can produce executable programs that fail to compute the intended scientific object. We study this problem in language-model

AI-driven ionic liquid discovery with unified chemical intelligence

arXiv:2511.11257v2 Announce Type: replace-cross Abstract: The rational discovery of functional solvents remains challenging because macroscopic solvent behaviors emerge from complex many-body interact

agentsarxiv-cs-lg

Alignment-Guided Flow Transformer for Efficient Vision-Language-Action Policy Learning

arXiv:2609.34467v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models point toward general-purpose robotic intelligence by unifying perception, instruction, and contro

All-Atom GPCR-Ligand Dynamics Simulation via a Residual Latent Flow Mode

arXiv:2602.03902v2 Announce Type: replace-cross Abstract: G-protein-coupled receptors (GPCRs), which are targeted by over one-third of approved drugs, undergo intricate conformational transitions to t

Allspark: Weak to Strong Transfer via Alternating Chain of Thought

arXiv:2609.32913v1 Announce Type: new Abstract: Recent progress in frontier models has renewed interest in large-scale reinforcement learning (RL), but the cost of generating large-model rollouts make

Amnesia by Design, Memory By Necessity: Persistent State for Document Intelligence

arXiv:2609.32041v1 Announce Type: new Abstract: Modern Document AI reads contracts, extracts fields, reasons over tables, and grounds answers to page regions, then forgets everything. Processing an am

An Attention-Driven Heterogeneous GNN Model for Credit Card Fraud Detection

arXiv:2609.32106v1 Announce Type: new Abstract: The global transition to a cashless economy has placed credit cards as the key element of digital transactions, acclaimed for their easy use, speed, and

applicationsarxiv-cs-lg

An RL View of OPD: Least Square Policy Distillation for Sample-Efficient LLM Reasoning

arXiv:2609.35505v1 Announce Type: new Abstract: We study on-policy distillation (OPD) through the lens of reinforcement learning, establishing a connection between the reverse-KL objective in OPD and

Anatomy-Structured Hierarchical MIL for Weakly-Supervised Thoracic Disease Detection in Chest X-rays

arXiv:2609.33520v1 Announce Type: new Abstract: Weakly-supervised thoracic disease detection in chest X-rays (CXR) is challenging due to subtle appearances and complex anatomical overlap, motivating a

Tutorials

AnchorMixGAN: Anchor-Aligned Generative Semi-Supervision for DDoS Detection in Cloud-Integrated IoT Networks

arXiv:2609.32764v1 Announce Type: new Abstract: Detecting distributed denial-of-service (DDoS) attacks in cloud-integrated IoT networks is difficult when labeled traffic is scarce. Generative semi-sup

tutorialsarxiv-cs-lg

Anytime-Valid LLM Leaderboards via Benchmark-weighted and Block-Factorized e-Processes

arXiv:2609.32248v1 Announce Type: new Abstract: Large language model (LLM) leaderboards compare model capabilities by ranking models according to their mean performance on fixed benchmarks. However, v

ARS: Agentic Reward System for Robot Learning

arXiv:2609.34484v1 Announce Type: cross Abstract: Progress reward modeling is the problem of estimating how a robot's behavior changes task progress over time. Reliable estimation requires distinguish

Assisting for Open-Ended Tasks: Goal-Oriented Shared Autonomy as a Particle Filter

arXiv:2609.32576v1 Announce Type: new Abstract: A common approach for shared autonomy blends human inputs with autonomous assistance based on the human's likely goal. However, most existing approaches

agentsarxiv-cs-ro

ASTRA: ADMM-Accelerated Topology Reconfiguration for Dynamic Satellite Constellations

arXiv:2609.33993v1 Announce Type: new Abstract: Dynamic topology reconfiguration is central to the reliability and efficiency of large satellite constellations, yet many existing approaches rely on id

AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs

arXiv:2509.25570v2 Announce Type: replace Abstract: Vision Graph Neural Networks (ViGs) have demonstrated promising performance in image recognition tasks against Convolutional Neural Networks (CNNs)

AutoHGNN: Robust and Efficient Neural Architecture Search for Hypergraph Neural Networks

arXiv:2609.33392v1 Announce Type: new Abstract: Hypergraph neural networks have achieved significant success in recent years. However, manual architecture crafting is labor-intensive and often fails t

Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions

arXiv:2601.08701v2 Announce Type: replace-cross Abstract: Accurate and generalisable segmentation of stroke lesions from magnetic resonance imaging (MRI) is essential for advancing clinical research,

Background Gradients Shape Memorization in Flow Matching

arXiv:2609.33210v1 Announce Type: new Abstract: Repetition is closely associated with memorization in generative models, but how other training images affect the retention and copying of targets remai

Bayesian Active Learning for Intent Disambiguation in Interactive Robot Planning

arXiv:2609.34270v1 Announce Type: new Abstract: Interactive robot planning requires robots to infer and execute human intentions from natural language instructions that are often ambiguous, incomplete

applicationsarxiv-cs-ro

BEHAVE: Functional Behavior Modeling Enables Self-Improving Agents for Hardware Design and Verification

arXiv:2609.34785v1 Announce Type: cross Abstract: Developing agents for hardware design and verification requires reliable correctness feedback. As a hardware specification may permit correct implemen

agentsarxiv-cs-lg

Benchmarking EEG Foundation Models at Scale: Lessons from 20,000 Evaluations

arXiv:2609.32743v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models (FMs) promise transferable neural representations, yet their advantages over strong supervised baselines

Beyond Correctness: Evaluating Semantic Knowledge in Cross-Table Transfer

arXiv:2609.34098v1 Announce Type: new Abstract: Semantic knowledge is increasingly used to bridge heterogeneous schemas in tabular learning, but how much does that knowledge actually improve predictio

Beyond Energy: When Sustainability Dimensions Reshape LLM Serving Decisions

arXiv:2609.35569v1 Announce Type: cross Abstract: Large language model (LLM) serving has environmental impacts across energy consumption, carbon emission, water consumption, and biodiversity loss. Yet

Beyond Gaussian Assumptions: Distribution-Aware Channel Capacity for Effective Connectivity

arXiv:2609.32774v1 Announce Type: new Abstract: Effective-connectivity estimation from brain signals often relies on Gaussian residual modeling, which enables tractable estimation but can discard info

Beyond Isolated Entities: Relation-Aware Multi-Entity Modeling for Unsupervised Video Anomaly Detection

arXiv:2609.31753v1 Announce Type: cross Abstract: Video anomaly detection for patrol robots and surveillance systems must recognize abnormal interactions among familiar entities. Existing pixel-recons

Beyond Reconstruction Loss in Post-Training Quantization: Balanced Fitting for Large Vision-Language Models

arXiv:2609.34765v1 Announce Type: new Abstract: Post-training quantization (PTQ) enables efficient deployment of large vision-language models (LVLMs), but is typically calibrated on a small set while

safetyarxiv-cs-cv

Beyond Saying Less: Fine-Grained Alignment for Informative and Faithful Vision-Language Models

arXiv:2609.35294v1 Announce Type: new Abstract: Object hallucination remains a major challenge for large vision-language models. While off-policy preference optimization proves to be an effective solu

safetyarxiv-cs-cv

Beyond Site Agreement: Re-estimation for Brain Network Generalization

arXiv:2609.34611v1 Announce Type: new Abstract: Cross-site out-of-distribution (OOD) generalization in resting-state functional magnetic resonance imaging (rs-fMRI) often relies on learning task-discr

BiasReducer: Adaptive Bias Mitigation for Reward Models

arXiv:2609.32720v1 Announce Type: new Abstract: Reward models score responses from large language models (LLMs) and guide LLM training toward human preferences. However, reward models can favor superf

Bidirectional Information Flow (BIF) - A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization

arXiv:2505.11294v3 Announce Type: replace Abstract: Hierarchical Gaussian Process (H-GP) models divide problems into different subtasks, allowing different components to address each part, making them

BiMoGen: Bidirectional Motion-Text Generation via Unified Masked Discrete Diffusion

arXiv:2609.35407v1 Announce Type: new Abstract: Text-to-motion generation and motion-to-text captioning are two fundamental tasks in human motion modeling, both grounded in the same underlying motion-

Black-Box Auditing of Epistemic Reliability in Multi-Agent Debate Distillation

arXiv:2609.32361v1 Announce Type: new Abstract: Debate distillation adapts weaker verifiers using multi-agent debate transcripts to improve their judgement in subsequent debates, but gains on monitore

Brain-Conditioned Action Policies for Neural Motor Decoding

arXiv:2609.34561v1 Announce Type: new Abstract: Motor brain-computer interfaces (BCIs) aim to decode motor intention, enabling people with paralysis to control external devices. Neural motor decoding

Bridging Generative and Discriminative Noisy-Label Learning via Direction-Agnostic EM Formulation

arXiv:2308.01184v4 Announce Type: replace Abstract: Although noisy-label learning is often approached with discriminative methods for simplicity and speed, generative modeling offers a principled alte

safetyarxiv-cs-cv

BudgetVerify: Budget-Tiered Verification for Financial QA

arXiv:2609.33052v1 Announce Type: cross Abstract: Financial question answering often requires precise numerical extraction, unit handling, and arithmetic over tables and text, but applying expensive v

Building Intelligent Agents with Neuro-Symbolic Concepts

arXiv:2505.06191v2 Announce Type: replace-cross Abstract: This article presents a concept-centric paradigm for building agents that can learn continually and reason flexibly. The concept-centric agent

agentsarxiv-cs-cv

CAFE: Counterfactual Prediction via Fast Posterior Estimation

arXiv:2609.32167v1 Announce Type: new Abstract: Counterfactual prediction estimates an individual's outcome under an alternative intervention given their factual observations. Such outcomes are genera

applicationsarxiv-cs-lg

Calibration-Free Surface Normals Estimation in Vision-Based Tactile Sensing using Universal Photometric Stereo

arXiv:2609.31754v1 Announce Type: new Abstract: Vision-based tactile sensors are a popular solution for capturing rich contact surface geometry. However, to obtain high-detail contact surface normals

applicationsarxiv-cs-cv

CAME: Company-Aware Evidence-Memory Experts for Interpretable Quarter-Ahead Revenue Forecasting

arXiv:2609.33143v1 Announce Type: cross Abstract: Quarter-ahead revenue forecasting requires company-scale numerical accuracy, strict temporal validity, and company-specific interpretation of narrativ