Search: “framework”

CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning

arXiv:2507.09471v2 Announce Type: replace Abstract: Continual Learning (CL) empowers AI models to continuously learn from sequential task streams. Recently, parameter-efficient fine-tuning (PEFT)-base

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Co-RL: Unsupervised Reasoning Emerges from Diverse Cohort in Multi-agent RL

DGX agent

arXiv:2608.17253v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as a powerful approach for improving reasoning in language and vision-language models, yet its strongest succe

agentsarxiv-cs-ai

19 Aug 2026

ComNetX: Local Hierarchical Adaptation for Dynamic Community Detection

arXiv:2608.16906v1 Announce Type: cross Abstract: Dynamic community detection is commonly addressed either by full-snapshot recomputation or by solver-specific dynamic procedures. Full recomputation p

local-aiarxiv-cs-ai

Comparative Study of Out-of-the-Box Technology for Automatic Target Detection and Recognition

arXiv:2608.17917v1 Announce Type: cross Abstract: Automatic Target Detection and Recognition (ATD/R) is critical for military decision support and (semi-)autonomous operations. Recent advances in obje

Composing Flow-Matching Energies with Known Physics: Generation, OOD Detection, and Inversion on PDE Fields

arXiv:2608.18004v1 Announce Type: new Abstract: Probabilistic modeling of physical fields benefits from both a data-driven prior and known physical structure such as the governing equations. Energy-ba

Continuous Evolution Pool: Taming Recurring Concept Drift in Online Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2506.14790v3 Announce Type: replace Abstract: Recurring concept drift is pervasive in real-world online time series, where the underlying data-generating process repeatedly alternates between a

ControlledShifts: Towards Standardizing Robustness Evaluation in Trajectory Prediction Under Distribution Shifts

model-releasesarxiv-cs-ro

arXiv:2608.17882v1 Announce Type: new Abstract: Trajectory prediction is central to safety in autonomous driving, yet learning-based predictors tend to degrade sharply when encountering scenarios poor

Counterfactual Anatomy-guided Spatial-Temporal Decoding for Annotation-Free Hallucination Mitigation in Medical VLMs

arXiv:2608.17427v1 Announce Type: new Abstract: Medical vision-language models (Med-VLMs) have demonstrated strong performance on medical visual question answering, yet they remain prone to hallucinat

Deep Academic Survey: Stateful Agentic Closed-Loop Paradigm for Academic Survey Automation

arXiv:2608.18034v1 Announce Type: new Abstract: Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coh

Agents

Delegation Asymmetry in Agentic Recommender Systems: Measuring Two-Sided Receptivity in Online Dating

arXiv:2608.18058v1 Announce Type: new Abstract: Autonomous LLM agents that converse on a user's behalf are an emerging design pattern in matching platforms, yet their viability depends on a condition

agentsarxiv-cs-ai

Diff-DDoS: Realistic Cyber-Physical Attack Synthesis and Robust Detection for 5G-Enabled CPS Using Tabular Diffusion Models

arXiv:2608.17796v1 Announce Type: cross Abstract: Deep learning-based DDoS detectors for 5G-enabled cyber-physical systems face scarce labeled attack data and unrealistic synthetic substitutes, which

Agents

Diffusion Models for Smarter UAVs: Decision-Making and Modeling

arXiv:2501.05819v2 Announce Type: replace-cross Abstract: Uncrewed Aerial Vehicles (UAVs) are increasingly used in modern communication networks. However, challenges in decision-making and digital mod

agentsarxiv-cs-ai

Do Large Language Models Play Six Degrees of Separation? Measuring Topological Compression in Long-Context Manifolds

arXiv:2608.17950v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable multi-hop reasoning capabilities over long contexts, yet the internal mechanisms enabling these dist

researcharxiv-cs-cl

Safety

DynaForcing: Overcoming Dynamic Collapse in Self-Forcing Distillation for Streaming Avatar Generation

arXiv:2608.17707v1 Announce Type: new Abstract: Audio-driven avatar generation requires realistic lip-sync, expressive motion, and real-time streaming. Recent work achieves the latter via self-forcing

safetyarxiv-cs-cv

Dynamic Regime-Aware Conformal Calibration for Reliable Economic Forecast Intervals under Multiple Distribution Shifts

arXiv:2608.17079v1 Announce Type: new Abstract: Conformal prediction provides distribution-free prediction intervals but relies on exchangeability, an assumption often violated in economic forecasting

EATR-Stereo: Embodiment-Aware Routing of Paired Stereo Evidence for Humanoid Vision-Language-Action Control

arXiv:2608.17453v1 Announce Type: new Abstract: Long-horizon humanoid vision--language--action (VLA) control with head-mounted stereo cameras requires visual interfaces that can exploit complementary

researcharxiv-cs-ro

EDITBRIDGE: Towards Faithful and Efficient Ultra-High-Resolution Image Editing

arXiv:2608.18063v1 Announce Type: new Abstract: High-resolution image editing is increasingly demanded in professional workflows, yet existing diffusion-based models remain constrained to resolutions

EMAN: Optimization-Driven Capacity Growth through Path Emergence in Multi-Task Learning

arXiv:2608.16930v1 Announce Type: cross Abstract: Existing multi-task learning methods rely on hard sharing, multiple paths or experts, adaptive sharing, and dynamic expansion. However, their capacity

Safety

Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation

arXiv:2608.17512v1 Announce Type: new Abstract: Although Large Vision-Language Models (VLMs) have significantly advanced embodied navigation, their direct deployment remains challenging, as existing m

safetyarxiv-cs-ro

Environment-Invariant Subspace Learning for Generalizable Deepfake Detection

arXiv:2608.17700v1 Announce Type: new Abstract: Cross-distribution generalization remains a critical bottleneck in deepfake detection. While recent efforts leverage the semantic priors of large-scale

tutorialsarxiv-cs-cv

Evaluating the Diversity of AI-Generated Content with Diversity Profiles

arXiv:2608.17731v1 Announce Type: new Abstract: Diversity is a fundamental criterion for evaluating generative artificial intelligence (AI) systems, yet its measurement remains inherently ambiguous. E

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification

model-releasesarxiv-cs-lg

arXiv:2507.15240v2 Announce Type: replace Abstract: For classification with imbalanced class frequencies, i.e., imbalanced classification (IC), standard accuracy is known to be misleading as a perform

Exploring Efficient Open-Vocabulary Segmentation in the Remote Sensing

arXiv:2509.12040v3 Announce Type: replace-cross Abstract: Open-Vocabulary Remote Sensing Image Segmentation (OVRSIS), an emerging task that adapts Open-Vocabulary Segmentation (OVS) to the remote sens

Force-Based Offset Estimation for Keyed Peg-in-Hole Assembly Using Local Gaussian Process Regression

arXiv:2608.17691v1 Announce Type: new Abstract: Key-keyway assembly tasks impose strict geometric constraints and are highly sensitive to grasp pose deviations in uncertain environments. This work pre

local-aiarxiv-cs-ro

Fourth-Moment Geometry of Rademacher Sums

arXiv:2608.17802v1 Announce Type: new Abstract: Let arepsilon_1,ldots,arepsilon_n be independent Rademacher signs and let a=(a_1,ldots,a_n)inR^n satisfy the normalization below. For the normalized Rad

From Corpora to Co-Evolving Capabilities: Capability-Centric Data Design for Generalist Image Generation

arXiv:2608.18076v1 Announce Type: cross Abstract: Large-scale image generation has benefited from advances in data scale, quality, rebalancing, and recaptioning, yet conventional pipelines typically o

tutorialsarxiv-cs-ai

From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector

arXiv:2608.17827v1 Announce Type: new Abstract: Public institutions face a persistent challenge in selecting LLMs suited to their specific context. Existing benchmarks, however, are of limited use as

researcharxiv-cs-cl

GeoWeaver: Accurate Long-Sequence 3D Reconstruction via Hierarchical Geometric Assembly

arXiv:2608.17389v1 Announce Type: new Abstract: Long-sequence 3D reconstruction from RGB videos requires both accurate local geometry and globally consistent camera motion. Feed-forward models provide

local-aiarxiv-cs-cv

Gradient Heterogeneity Complements Hessian Heterogeneity in Transformer Optimization

arXiv:2502.00213v5 Announce Type: replace-cross Abstract: Transformers are difficult to optimize with stochastic gradient descent (SGD) and largely rely on adaptive optimizers such as Adam. Despite ex

Agents

Graphectory Viewer: A Tool for Process-Centric Analysis of Agentic Software Trajectories

arXiv:2608.17195v1 Announce Type: cross Abstract: We present Graphectory Viewer, a web-based tool for interactive, process-centric analysis of software-agent trajectories. Building on the Graphectory

agentsarxiv-cs-ai

GS-Voxel: Fitting-Free Structured Latents for Large-Scale 3DGS Generation

arXiv:2608.17988v1 Announce Type: new Abstract: Many scalable latent 3D generators operate on structured tensors, whereas pre-optimized 3D Gaussian Splatting (3DGS) reconstructions are unordered, spat

local-aiarxiv-cs-cv

Harnessing Magnitude-Only and Complex Measurements for Improved Dynamic MRI Reconstruction with Learned Priors

arXiv:2608.18036v1 Announce Type: cross Abstract: MRI reconstruction methods for undersampled k-space data naturally utilize complex-valued measurements. Parallel developments in sparse phase retrieva

HeteRo-Select: Informativeness as the Participation Driver in Heterogeneous Federated Learning

model-releasesarxiv-cs-lg

arXiv:2508.06692v3 Announce Type: replace Abstract: Federated learning systems typically allocate gradient compression by link speed. This is sensible when bandwidth and data informativeness align. Ho

Heterogeneity-Aware Deep Learning for Tumour Classification from Multiparametric MRI

arXiv:2608.17254v1 Announce Type: new Abstract: Intra-tumoural heterogeneity (ITH) reflects spatial variation in tumour biology and is an important determinant of tumour behaviour, prognosis, and trea

local-aiarxiv-cs-cv

Hidden Prompts in Manuscripts Exploit AI-Assisted Peer Review

arXiv:2507.06185v2 Announce Type: replace-cross Abstract: In July 2025, 18 academic manuscripts on arXiv contained hidden instructions that manipulated AI-assisted peer review (indirect prompt injecti

Initialization-Free Bundle Adjustment Revisited: A Controlled Experimental Study

arXiv:2608.18028v1 Announce Type: new Abstract: Initialization-free bundle adjustment (InitFree BA) aims to recover camera poses and scene structure directly from image observations, avoiding the geom

Interpretable Humans, Alien LLMs: Expert Analysis of Latent Structures in Assessment Responses

arXiv:2608.17810v1 Announce Type: cross Abstract: The evaluation of large language models (LLMs) relies heavily on human-designed assessments, implicitly assuming that AI and humans employ similar und

Iterative tensor network transformations for element-wise evaluation of elementary and filtering functions

arXiv:2608.17135v1 Announce Type: cross Abstract: Tensor networks are powerful formats for compressing large-scale data. However, their application to general data processing has been limited by the d

Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models

arXiv:2603.22782v2 Announce Type: replace Abstract: Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity o

KnowSim: Evaluating Information Calibration in LLM Assistants with User Simulators that Learn

arXiv:2608.17150v1 Announce Type: new Abstract: To effectively collaborate with users on knowledge-intensive tasks, Large Language Models (LLMs) must perform information calibration: matching content

tutorialsarxiv-cs-ai

Learning What Not to Learn: Adversarial Disentangled Prompt Tuning for Robust Vision-Language Models

arXiv:2608.17306v1 Announce Type: cross Abstract: While adversarial prompt tuning can enhance robustness of vision-language models efficiently, we find that existing methods aggravate robust generaliz

tutorialsarxiv-cs-ai

Learning Where and What to Lift for Bi-planar X-ray-to-CT Reconstruction

arXiv:2608.17255v1 Announce Type: cross Abstract: X-ray imaging can be approximately modeled as the projection of an underlying volumetric attenuation field, with each measurement recording the accumu

LEGO-RL: Harness-Native Reinforcement Learning for Coding Agents

arXiv:2608.17393v1 Announce Type: new Abstract: Reinforcement learning for coding agents increasingly relies on long-running agent harnesses to manage tool integration, repository contexts, and execut

Leveraging Association Context Retrieval in Knowledge Edit- ing to Build White-Box Attacks on LLMs

arXiv:2608.17836v1 Announce Type: new Abstract: As large language models (LLMs) are granted increasing autonomy, it is essential to investigate methods that can induce unsafe behavior. We propose a no

Leveraging generative hallucination and biophysics-informed modeling for unified biomolecular sequence-structure co-design

arXiv:2608.17381v1 Announce Type: cross Abstract: Biomolecular design underpins applications from molecular recognition to therapeutics and synthetic biology, yet de novo interaction design remains ch

LinCa: Accelerating Diffusion Models via Learnable Decomposed Feature Caching

arXiv:2608.17973v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in image and video generation, yet the high computational cost of iterative sampling remains a critica

Live Interactive Training for Video Segmentation

arXiv:2603.26929v2 Announce Type: replace Abstract: Interactive video segmentation often requires many user interventions for robust performance in challenging scenarios (e.g., occlusions, object sepa

tutorialsarxiv-cs-cv

MagViT: Interpretable Multi-Magnification Transformers with Patient-Level Model Selection for Breast Histopathology

arXiv:2608.16959v1 Announce Type: cross Abstract: Breast cancer is one of the most common types of cancer among women around the world. Rapid detection and early treatment can hinder its progress to m