Search: “context”

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

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Agentic High-Dimensional Bayesian Optimization with Hypothesis- and Evidence-Guided Search

DGX agent

arXiv:2609.34281v1 Announce Type: new Abstract: High-dimensional Bayesian optimization (HDBO) seeks sample-efficient optimization when the number of variables is large relative to the evaluation budge

agentsarxiv-cs-lg

29 Sept 2026

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

AquaBEV-Nav: Learned BEV Occupancy for Underwater Navigation and Exploration

arXiv:2609.32156v1 Announce Type: cross Abstract: Safe underwater exploration requires a robot to understand where surrounding structures are located and which regions are available for motion. Existi

Artificial Intelligence Across the Cardiac Amyloidosis Diagnostic and Management Pathway: From Single-Modality Detection to Multimodal Clinical Integration

arXiv:2607.09948v2 Announce Type: replace-cross Abstract: Cardiac amyloidosis (CA) is increasingly recognized but remains substantially underdiagnosed because its clinical and imaging phenotype overla

Agents

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

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,

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 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

Beyond the Graph: An Adaptive Meta-Learner Fuses Explainability, Weather, and Dynamics for Robust Bus ETA Prediction

arXiv:2609.31667v1 Announce Type: new Abstract: Accurate bus Estimated Time of Arrival (ETA) prediction is vital for urban mobility, passenger satisfaction, and transit efficiency, yet existing models

Bison: Cross-Dataset Learning for Unseen-Compound Perturbation Prediction

arXiv:2609.32467v1 Announce Type: new Abstract: Predicting transcriptional responses to unseen compounds is limited by fragmented chemical coverage and heterogeneous experimental platforms and gene pa

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

safetyarxiv-cs-lg

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

Causally Debiased Latent Action Model for Embodied Action-Conditioned World Models

arXiv:2607.09185v2 Announce Type: replace Abstract: Action-conditioned world models (ACWMs) aim to simulate future observations conditioned on embodied actions. However, learning controllable ACWMs re

CFCH: Coarse-Fine Collaborative Hierarchical Learning for Anterior Segment Disease Analysis

arXiv:2609.32559v1 Announce Type: new Abstract: Accurate classification of anterior segment diseases is crucial for ophthalmic screening and diagnosis. However, slit-lamp image analysis remains challe

CODEBLOCK: Learning to Supervise Code at the Right Granularity

arXiv:2606.18286v2 Announce Type: replace Abstract: Supervised fine-tuning of code LLMs typically applies uniform cross-entropy loss to all response tokens, implicitly assuming that every token provid

Collaborative Principle Evolution via Evidence Transfer for Scientific Discovery

arXiv:2609.35315v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents promise to automate scientific discovery, yet exploring the vast hypothesis space remains costly. Existing princ

Local Ai

Control-Geometry Straightening for Sampling-Based Latent Planning

arXiv:2609.35603v1 Announce Type: new Abstract: Joint-embedding predictive architectures enable planning with latent world models, but accurate transition prediction alone does not ensure that the pla

local-aiarxiv-cs-lg

Correct then Forecast: Observer State-Space Models for Time Series Forecasting

arXiv:2609.33566v1 Announce Type: new Abstract: Time series forecasting requires extrapolating the dynamics of an observed process beyond the last available measurement. Yet recurrent forecasting mode

Counterfactual Attention Policy Distillation for Temporal Video Grounding

arXiv:2609.34581v1 Announce Type: new Abstract: Temporal video grounding is a key capability of advanced Multimodal Large Language Models (MLLMs) for the thorough understanding of video events, which

Counting on Thinking: Tracing Evidence Integration in Language Models

arXiv:2609.32932v1 Announce Type: new Abstract: Finite computational resources force a tradeoff between automatic System 1 processes and costly System 2 thinking. Large language models (LLMs) can spen

d-OPD: Future-Aware On-Policy Distillation for Block Diffusion Language Models

arXiv:2609.35362v1 Announce Type: new Abstract: Large language models (LLMs) typically generate text autoregressively (AR), predicting one token at a time. Block diffusion language models (dLLMs) inst

D^2-VLA: Dual-Memory Dual-Frequency Vision-Language-Action Model For Long Dynamic Manipulation

arXiv:2609.34792v1 Announce Type: new Abstract: Long-horizon manipulation requires robots to remember cues that are no longer in view while responding to moving objects. Yet vision-language-action (VL

Data Processing for Offline Evaluation in Recommender Systems: a Survey

arXiv:2609.31696v1 Announce Type: cross Abstract: Offline evaluation is the dominant experimental paradigm in recommender systems research, enabling reproducible and cost-effective comparisons on hist

DeltaWAM: Change-Centric Visual Foresight via Delta Tokens for an Efficient World-Action Model

arXiv:2609.33177v1 Announce Type: cross Abstract: World-Action Models (WAMs) offer visual foresight for robotic manipulation, but pixel-space models repeatedly reconstruct entire future scenes, incurr

dKFD: Phase-Structured Evidence Allocation for Fixed-Budget Localized Event Understanding

arXiv:2609.33083v1 Announce Type: new Abstract: Sparse video understanding often requires selecting a small set of visual evidence under a fixed frame budget. Most sparse selectors allocate this budge

Local Ai

Do World Models Learn Global Understanding?

arXiv:2609.34058v1 Announce Type: new Abstract: AI systems often feel brittle and fragmented. A large language model (LLM) may correctly explain a concept but fail to apply it, or follow safety instru

local-aiarxiv-cs-lg

Does Transolver really need a Transformer?

arXiv:2609.32525v1 Announce Type: new Abstract: The widely used Transolver family of neural operators is based on physics-attention, which softly assigns the points of an unstructured mesh to a small

DP-Rec: Towards Dynamic Patching for Efficient Long-Sequence Recommendation

arXiv:2609.32215v1 Announce Type: new Abstract: Transformers have redefined sequential recommendation by effectively modeling dynamic user behaviors and long-range dependencies. However, they remain i

Local Ai

DR-net-Mamba: Selective State-Space Modeling for Long-Range ECG Time-Series Denoising

arXiv:2609.35634v1 Announce Type: new Abstract: Electrocardiogram (ECG) recordings are corrupted by non-stationary noise sources that degrade diagnostic reliability, particularly in ambulatory and lon

local-aiarxiv-cs-lg

DreamingGoose: Staged Distillation from Autoregressive Transformers to Bidirectional Recurrent Diffusion Language Models

arXiv:2609.34253v1 Announce Type: new Abstract: Pretrained autoregressive Transformers represent a large sunk investment in compute. Existing conversion methods reuse that investment by changing eithe

DuoOPD: Learning from Joint Teacher-Student Outcomes for Multi-Task On-Policy Distillation

arXiv:2609.33711v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own responses with token-level feedback from a stronger teacher, yet the teacher can fail on questi

DynGraphAgentBench: A Benchmark for Agentic Lifecycle Control in Dynamic Graph Anomaly Detection

arXiv:2609.33980v1 Announce Type: new Abstract: Dynamic graph anomaly detection requires repeated decisions as graph structure and class prevalence drift, yet detector benchmarks usually score a fixed

ECG-Scroll: A Long-Horizon, Streaming Benchmark and Agent Environment for Interpretation of Ambulatory Electrocardiograms

arXiv:2609.33117v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can now interpret a standard ten-second, twelve-lead electrocardiogram (ECG) with clinically grounded, reward-v

EdgeVLN: Runtime-Aware Deployment Ready Quantized Vision Language Navigation Model

arXiv:2609.35570v1 Announce Type: cross Abstract: Vision-language navigation (VLN) models perform well but target compute-rich platforms, limiting deployment on memory- and power-constrained robotic e

Hardware

Efficient World Action Model Inference with Adaptive Intermediate States

arXiv:2609.34608v1 Announce Type: new Abstract: World Action Models (WAMs) enable future-aware control by jointly modeling actions and environment dynamics. However, iterative diffusion or flow infere

hardwarearxiv-cs-ro

Ego-Forge: Text and Geometric-Attention Free Exo-to-Egocentric Video Generation

arXiv:2609.35368v1 Announce Type: new Abstract: Exo-to-egocentric video generation aims to synthesize what a person sees from their own viewpoint given third-person footage and a target head trajector

Elastic Selective Spectral Hybrids for Train-Once, Export-Many Budgeted Inference

arXiv:2609.32486v1 Announce Type: new Abstract: Deploying a language model under different computing and latency budgets calls for compact models with different quality-cost trade-offs. Towards this e

Elicitation and Decision Geometry in Single-Index Bandits

arXiv:2609.35622v1 Announce Type: cross Abstract: We study two-arm contextual bandits with arm-specific single indices and a shared unknown monotone link. Monotonicity makes the optimal action depend

Energy Vision--Language--Action: A Controlled Multimodal Benchmark for Intent-Conditioned Residential Energy Management

arXiv:2609.31648v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are studied mainly in robotics, where visual observations and language instructions are mapped to physical actions.

Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks

arXiv:2609.31981v1 Announce Type: cross Abstract: As Internet of Things (IoT) networks increasingly depend on machine learning for anomaly, malware, intrusion detection, and network monitoring, such s

Hardware

FILIGREE3D: Scaling Sparse Latent Flow Matching for Ultra-High-Resolution Image-to-3D Generation

arXiv:2609.34900v1 Announce Type: new Abstract: Scaling image-to-3D generation to ultra-high resolutions requires controlling rapidly growing computational costs without sacrificing fine geometric det

hardwarearxiv-cs-cv

Forecast-Necessary Causal Discovery for Nonlinear Political Panel Data: Feedback, Functional Form, and the Dynamics of Democratization

arXiv:2609.34115v1 Announce Type: cross Abstract: A non-significant coefficient in a dynamic panel model need not imply the absence of a relationship. It may instead reflect heterogeneous effects aver

ForeFly: A Dual-Horizon World Action Model for Aerial Vision-Language Navigation

arXiv:2609.33581v1 Announce Type: new Abstract: Aerial Vision-Language Navigation (AVLN) requires UAVs to maintain reliable instruction following over long trajectories in complex 3D environments. How

From Feed-Forward to Flow: Unifying Reconstruction and Generation Is Easier Than You Think

arXiv:2609.32761v1 Announce Type: new Abstract: Reconstruct where the images provide evidence, and generate where they do not: recent success of spatial world models such as Atlas (World Labs Team, 20

From Grey-Box to Green-Box: When can Physics-Informed Machine Learning Reduce Carbon Footprints in Structural Health Monitoring?

arXiv:2609.33387v1 Announce Type: new Abstract: Machine learning plays an increasingly vital role in engineering, but the corresponding increase in compute time is not without environmental cost. Phys

Gaussian Splatting-based Volumetric Video Compression with Sparse 4D Anchors

arXiv:2609.33969v1 Announce Type: new Abstract: Immersive video communication requires photorealistic, render-efficient, and compact dynamic scene representations. 3D Gaussian Splatting (3DGS) offers

Geometric Encoding for Spatial Reasoning in Vision-Language Models

arXiv:2609.34148v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are far more reliable at recognizing what appears in a video than at reasoning about its spatial and temporal properties,