Search: “framework”

Metaplasticity as adaptive gradient preconditioning for incremental learning

model-releasesarxiv-cs-lg

arXiv:2608.14634v1 Announce Type: new Abstract: Biological intelligence naturally prevents catastrophic forgetting through Complementary Learning Systems (CLS) theory, a macroscopic consolidation proc

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Agents

MistyPilot: Enabling Social-Robot Control through Multi-Agent LLM Skill Orchestration

DGX agent

arXiv:2608.15549v1 Announce Type: cross Abstract: Programming small social robots from natural-language instructions requires more than invoking isolated APIs. Interactive tasks combine reactive physi

agentsarxiv-cs-ai

18 Aug 2026

MITE-Net: SWaP-Optimized 4K Video Tiny Target Perception for Embodied Edge SAR

model-releasesarxiv-cs-cv

arXiv:2608.15830v1 Announce Type: new Abstract: Real-time tiny target perception in high-resolution imagery is critical for embodied Search-and-Rescue (SAR) missions. However, strict Size, Weight, and

Mitigating Error Accumulation in Co-Speech Motion Generation via Global Rotation Diffusion and Multi-Level Constraints

arXiv:2511.10076v3 Announce Type: replace Abstract: Reliable long-horizon co-speech gesture generation requires precise motion representation and consistent structural priors across all joints. Existi

Mitigating Rubric Interference in LLM Judges via On-Policy Self-Distillation

arXiv:2608.14684v1 Announce Type: cross Abstract: LLM judges increasingly evaluate responses against fine-grained rubric checklists. When a sample requires multiple rubrics, current methods typically

Mixture of experts architectures for machine learning interatomic potentials

arXiv:2603.07977v3 Announce Type: replace-cross Abstract: Machine Learning Interatomic Potentials (MLIPs) enable accurate large-scale atomistic simulations, yet improving their expressive capacity eff

MODAL: Multi-Modal Object Re-ID via Model-Driven Sparse Decoupling and Text-Image Differential Filtering

arXiv:2608.15096v1 Announce Type: new Abstract: Multi-modal object re-identification (Re-ID) aims to facilitate cross-camera object retrieval in complex environments by leveraging complementary inform

Modality-Invariant Coarse-to-Fine Retinal Image Registration

arXiv:2608.14829v1 Announce Type: cross Abstract: Retinal image registration is essential for ophthalmic diagnosis, longitudinal disease monitoring, and multimodal retinal image analysis. Existing ret

safetyarxiv-cs-cv

MoE Router-Guided Clustering for Heterogeneous Federated Instruction Tuning

arXiv:2608.15311v1 Announce Type: new Abstract: Federated instruction fine-tuning enables Large Language Models (LLMs) to adapt to decentralized, privacy-sensitive data without requiring data sharing.

mR^2AG: Multimodal Retrieval-Reflection-Augmented Generation for Knowledge-Based VQA

arXiv:2411.15041v2 Announce Type: replace Abstract: Advanced Multimodal Large Language Models (MLLMs) struggle with recent Knowledge-based Visual Question Answering (VQA) tasks, such as INFOSEEK and E

local-aiarxiv-cs-ai

Multi-Feature Riemannian Hypergraph for Online Test-Time Adaptation of Motor Imagery Brain-Computer Interface

arXiv:2608.16134v1 Announce Type: new Abstract: In clinical motor imagery brain-computer interface (MI-BCI) decoding, cross-day transferability and online operation remain two critical challenges. Hyp

safetyarxiv-cs-lg

Multi-Granularity Sentiment Integration for LLM-Based Multimodal Sentiment Analysis

arXiv:2608.16201v1 Announce Type: new Abstract: Multimodal sentiment analysis (MSA) aims to predict sentiment polarity and intensity from heterogeneous inputs such as text, audio, and vision. While la

local-aiarxiv-cs-lg

Multilook Coherent Imaging: Theoretical Guarantees and Algorithms

arXiv:2505.23594v2 Announce Type: replace-cross Abstract: Multilook coherent imaging is a widely used technique in applications such as digital holography, ultrasound imaging, and synthetic aperture r

NeuRoute: Logit-Guided Neural Routing for Billion-Scale Vector Search with Sub-Hour Index Construction

arXiv:2608.15438v1 Announce Type: cross Abstract: Building approximate nearest neighbor (ANN) indexes at billion scale is often dominated by expensive global clustering or graph construction, making t

NICE: Scale-Stable Perturbations for Graph Neural Network Explanations via Noise Corruption

arXiv:2608.16038v1 Announce Type: cross Abstract: Post-hoc Graph Neural Network (GNN) explainers commonly follow a Perturb-Query paradigm, inferring the importance of graph elements based on queried p

Not All Attention Is Equal: A Quantitative Survey of the EEI Trade-off

arXiv:2608.15459v1 Announce Type: cross Abstract: Attention mechanisms have driven machine learning for a decade, from neural machine translation to language models that do general-purpose reasoning.

Not All Neighbors Matter: Understanding the Impact of Graph Sparsification on GNN Pipelines

arXiv:2603.06952v2 Announce Type: replace Abstract: As graphs scale to billions of nodes and edges, graph Machine Learning workloads are constrained by the cost of multi-hop traversals over exponentia

Tutorials

NRCD: An Open Database of Collegiate Running with Unified Performance Standardization

arXiv:2608.14776v1 Announce Type: new Abstract: Collegiate running in the United States generates thousands of race results annually in cross country and track and field, yet no large-scale dataset ha

tutorialsarxiv-cs-lg

Tutorials

OccamView: Object-Conditioned View Selection for Frame-Budgeted Active 3D Gaussian Reconstruction

arXiv:2608.16499v1 Announce Type: cross Abstract: Active 3D Gaussian reconstruction fundamentally relies on selecting informative next-best views under limited sensing budgets. Existing active 3DGS me

tutorialsarxiv-cs-cv

OceanLight: Efficient Global Ocean Forecasting via Geometry-Adaptive Unstructured Mesh Representation

arXiv:2608.16070v1 Announce Type: cross Abstract: Reliable global ocean forecasting is critical for climate monitoring, marine navigation, and extreme event early warning. Physics-based ocean forecast

local-aiarxiv-cs-ai

Tutorials

ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription

arXiv:2307.15691v4 Announce Type: replace-cross Abstract: ODTlearn is an open source Python package that provides methods for learning optimal decision trees for high-stakes predictive and prescriptiv

tutorialsarxiv-cs-lg

Offline Reinforcement Learning for Hemodynamic Management of Sepsis in the ICU: a MIMIC-IV Study with Dual Off-Policy Evaluation

arXiv:2608.16482v1 Announce Type: new Abstract: The dosing of intravenous fluids and vasopressors in sepsis is a sequential decision made under uncertainty and guided largely by clinical judgment, whi

safetyarxiv-cs-ai

Hardware

On Fibonacci Ensembles: An Alternative Approach to Ensemble Learning Inspired by the Timeless Architecture of the Golden Ratio

arXiv:2512.22284v2 Announce Type: replace-cross Abstract: Nature rarely reveals her secrets bluntly, yet in the Fibonacci sequence she grants us a glimpse of her quiet architecture of growth, harmony,

hardwarearxiv-cs-lg

On the Adversarial Robustness of Remote Sensing Semantic Change Detection

arXiv:2608.15267v1 Announce Type: new Abstract: Semantic change detection (SCD) is a bitemporal dense-prediction task that jointly identifies changed regions and their semantic states before and after

local-aiarxiv-cs-cv

Optimizing Multi-Market Participation of Battery and Electrolyser Systems Based on Field Performance

arXiv:2608.16238v1 Announce Type: new Abstract: The increasing share of renewable energy in power systems creates a need for fast-response and flexible resources to maintain system stability. With the

Orbital AI Computing: Carbon Tradeoffs Across Satellite Scale

arXiv:2608.14557v1 Announce Type: cross Abstract: Low Earth Orbit (LEO) computing is emerging for low-latency, globally distributed AI services, enabled by advances in satellite constellations and reu

local-aiarxiv-cs-ai

OvDSGG: End-to-End Open-Vocabulary Dynamic Scene Graph Generation

model-releasesarxiv-cs-cv

arXiv:2608.14835v1 Announce Type: new Abstract: Dynamic scene graphs (DSGs) capture spatio-temporal interactions across videos as langlesubject, predicate, objectrangle triplets, and underpin downstre

P2E-VQ: ECG-linked representation augmentation for PPG via discrete patch retrieval

arXiv:2608.14656v1 Announce Type: cross Abstract: Photoplethysmography (PPG) is widely used in consumer wearables because of its low cost and ease of acquisition. However, unlike electrocardiography (

PACE: Phase-Progress-Aware Credit for Long-Horizon Embodied Manipulation

arXiv:2608.15026v1 Announce Type: new Abstract: Post-training of vision-language-action (VLA) models typically relies on expert demonstrations and policy interaction trajectories. However, in long-hor

local-aiarxiv-cs-ro

ParaTempo: Efficient Parallel Reasoning via Temporal Confidence

arXiv:2608.16425v1 Announce Type: new Abstract: Parallel reasoning improves the accuracy and robustness of large reasoning models by exploring multiple solution paths, but its computational cost grows

PAS-QFL: Personalized Ansatz Selection for Quantum Federated Learning under Client Data Heterogeneity

arXiv:2608.14995v1 Announce Type: cross Abstract: Quantum federated learning (QFL) lets multiple quantum clients collaboratively train quantum neural networks (QNNs) without sharing private local data

PaSTel: Anchoring Histology in Spatial Transcriptomics via Multi-Scale Hierarchical Bio-Prior Contrastive Pretraining

arXiv:2608.14924v1 Announce Type: cross Abstract: Spatial transcriptomics (ST) links tissue morphology with molecular programs, motivating multimodal pretraining methods that align histology images wi

safetyarxiv-cs-ai

Path2ST: Hierarchical Cell-Tissue Grounded Cross-Modal Translation for Spatial Transcriptomics

arXiv:2608.14710v1 Announce Type: cross Abstract: Predicting spatial gene expression from hematoxylin and eosin (H&E)-stained images offers a cost-effective alternative to spatial transcriptomics (ST)

PCA-guided Activation Scaling for Monotonic Bidirectional Control over LLM Sycophancy

arXiv:2608.16650v1 Announce Type: new Abstract: Large language models (LLMs) exhibit sycophancy, a tendency to agree with user beliefs regardless of factual accuracy. This can reinforce misconceptions

researcharxiv-cs-cl

PDDLCoder: Agentic PDDL Generation for LLM-Assisted Symbolic Planning

arXiv:2608.16637v1 Announce Type: new Abstract: LLMs remain unreliable for long-horizon planning, often generating logically inconsistent or non-applicable plans. Recent hybrid methods instead transla

Applications

PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification

arXiv:2608.15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as

applicationsarxiv-cs-lg

Agents

PersonaDrive: Controllable Trajectory Prediction with Multi-Dimensional Driving Personas

arXiv:2608.15230v1 Announce Type: new Abstract: Although recent trajectory prediction and end-to-end autonomous driving methods improve robustness in urban environments, they still lack meaningful con

agentsarxiv-cs-cv

Physics-informed VAE-EVT for Tail Aware Radio Map Prediction

arXiv:2608.15314v1 Announce Type: new Abstract: Ultra-reliable low-latency communication (URLLC) requires precise identification of spatial regions where the signal-to-noise ratio (SNR) falls below an

Applications

PhyxMamba: Chaotic System Reconstruction from Short Context Observations with Generative State-Space Models

arXiv:2505.23863v3 Announce Type: replace-cross Abstract: Understanding chaotic dynamics is a fundamental problem across scientific disciplines, including climate science, neuroscience, and fluid dyna

applicationsarxiv-cs-ai

PickStyle: Video-to-Video Style Transfer with Context-Style Adapters

arXiv:2510.07546v2 Announce Type: replace Abstract: We address the task of video style transfer with diffusion models, where the goal is to preserve the context of an input video while rendering it in

safetyarxiv-cs-cv

PixelControl: Fine-Grained Condition Fidelity in Text-to-Image Diffusion

arXiv:2608.15705v1 Announce Type: new Abstract: Controllable text-to-image diffusion models can often follow the global layout of spatial conditions, yet still violate fine-grained structures such as

Platform Adaptation Under Governance Interventions: Actor Best-Response Modeling and an External Public-Case Benchmark

arXiv:2608.15131v1 Announce Type: new Abstract: Digital platforms govern by changing rules: rankings, monetization thresholds, moderation standards, verification systems, disclosure requirements, appe

PoseAdapter: Dual-Stream 2.5D Controllable Image Generation for Complex Multi-Object Scenes

arXiv:2608.15583v1 Announce Type: new Abstract: While Text-to-Image (T2I) diffusion models have achieved remarkable success, precise spatial and orientational control in multi-object scenes remains a

Agents

Position: AI Agents in Scientific Teams Should Be Studied as Human-Agent Systems

arXiv:2608.14667v1 Announce Type: new Abstract: Large language model-based agents are increasingly deployed as collaborators in scientific discovery yet most current work focuses on the autonomous cap

agentsarxiv-cs-ai

Agents

Position: Certified Correctness in Neural Constraint Reasoning Requires Symbolic Integration

arXiv:2608.14569v1 Announce Type: new Abstract: Neural solvers for constraint satisfaction problems have achieved remarkable in-distribution accuracy, yet they suffer from a fundamental limitation per

agentsarxiv-cs-ai

Position: Evaluations of AI Moral Reasoning Still Miss Half of the Picture

arXiv:2608.14566v1 Announce Type: new Abstract: Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.e., whet

PosterText: Towards Unified Visual Text Generation and Editing for E-commerce Poster

model-releasesarxiv-cs-cv

arXiv:2608.16289v1 Announce Type: new Abstract: Automated e-commerce poster design requires both high-quality poster generation and flexible editing of existing designs. However, most existing methods

Pre-training Visual Dexterity in Simulation

arXiv:2608.15917v1 Announce Type: cross Abstract: Large-scale pre-training has made robot policy fine-tuning increasingly data-efficient, but this progress has largely been driven by datasets and embo

safetyarxiv-cs-ai