Search: “framework”

arXiv:2410.11378v3 Announce Type: replace-cross Abstract: Personalized collaborative learning in federated settings faces a critical trade-off between customization and participant trust. Existing app

local-aiarxiv-cs-ai

Hardware

Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing

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DGX agent

arXiv:2607.06136v1 Announce Type: new Abstract: Recent diffusion-based generative models have shown impressive performance in image generation and editing. However, due to memory limitations and the h

hardwarearxiv-cs-cv

8 Jul 2026

Uncovering Latent Depression Severity for Binary Depression Detection via Advantage-weighting Ranking

arXiv:2607.05901v1 Announce Type: new Abstract: Automatic depression detection using audio-visual data faces significant challenges, particularly in disentangling overlapping feature distributions and

researcharxiv-cs-ai

Tools

Use any Chat SDK adapter with eve

Eve's Chat SDK now supports multiple adapter options, allowing developers to integrate various chat platforms and services without being locked into a single solution. This flexibility enables teams t

toolsvercel-blog

Variational Learning of Disentangled Representations

arXiv:2506.17182v3 Announce Type: replace Abstract: Disentangled representations separate factors that are shared across conditions from those that are condition-specific. Such separation is needed fo

VaseMuseum: Digital Intelligent Museum for Ancient Greek Pottery

arXiv:2607.06374v1 Announce Type: new Abstract: Vision-language models (VLMs) have made interactive digital museums increasingly feasible by connecting 3D digitization with natural-language artifact e

VisCoP: Visual Probing for Video Domain Adaptation of Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2510.13808v2 Announce Type: replace Abstract: Large Vision Language Models (VLMs) excel at general visual reasoning but experience significant performance degradation when deployed in novel doma

Visual graphs for image classification: does the structure affect performance?

arXiv:2607.06295v1 Announce Type: new Abstract: Deep learning models have emerged in machine learning and related fields, demonstrating astonishing performance in various visual tasks. Despite their g

researcharxiv-cs-cv

Volumetric Directional Diffusion: Anchoring Uncertainty Quantification in Anatomical Consensus for Ambiguous Medical Image Segmentation

arXiv:2603.04024v2 Announce Type: replace-cross Abstract: Ambiguous 3D medical image segmentation often involves boundaries where different expert delineations are non-identical yet clinically plausib

Whose fairness? Structural concentration in AI bias research

arXiv:2607.05574v1 Announce Type: cross Abstract: Artificial intelligence increasingly mediates consequential decisions in healthcare, law, and public services, and the field has responded with an ext

WordVoice: Explicit and Decoupled Multi-Dimensional Word-Level Control for LLM-Based TTS

arXiv:2607.06461v1 Announce Type: cross Abstract: While recent Large Language Model (LLM)-based Text-to-Speech (TTS) systems have achieved remarkable naturalness, they predominantly rely on implicit e

safetyarxiv-cs-cl

Tutorials

WristMimic: Full-Body Humanoid Control with Wrist-Guided Manipulation

arXiv:2607.06438v1 Announce Type: cross Abstract: Retargeting human object interaction demonstrations to physics based simulation requires reproducing not only body motion but also the object motion a

tutorialsarxiv-cs-cv

X-FEMR: A Token-level Explainable Approach for Electronic Health Records Foundation Models using Transformer-based Models

arXiv:2607.06163v1 Announce Type: cross Abstract: Foundation Models for Electronic Health Records (FEMRs) are pretrained on large-scale structured patient data, enabling them to convert longitudinal p

A Cost-Aware, Paired Protocol for Auditing Dynamic Tool Synthesis in Agentic Video Question Answering

arXiv:2607.01469v2 Announce Type: replace Abstract: Agentic Video Question Answering (VideoQA) systems invoke tools during inference, but their tool libraries are fixed, so recurring procedures are re

Tutorials

A harmonised dataset for Earth system foundation models

arXiv:2607.03298v1 Announce Type: cross Abstract: Foundation models for Earth systems have so far been trained primarily on physical climate and weather data, with limited representation of the human

tutorialsarxiv-cs-ai

A Perception-Manipulation Robotics System for Food Cutting

arXiv:2607.04367v1 Announce Type: new Abstract: In the development of cooking robots, mastering the task of cutting is crucial. A significant challenge lies in the diverse properties of food, which ne

safetyarxiv-cs-ro

A Random Matrix Theory Perspective on the Consistency of Diffusion Models

arXiv:2602.02908v2 Announce Type: replace-cross Abstract: Diffusion models trained on different, non-overlapping subsets of a dataset often produce strikingly similar outputs when given the same noise

researcharxiv-cs-ai

Applications

A Sliding-Window-Based Reinforcement Learning for Dynamic Assembly Flow Shop Scheduling with Multi-Product Delivery

arXiv:2607.02941v1 Announce Type: new Abstract: Multi-product kitting delivery imposes significant challenges for real-time scheduling in hybrid manufacturing systems that integrate processing and ass

applicationsarxiv-cs-ai

A Step Towards Robust Unsupervised Domain Adaptation via Fine-Tuning and Reinforcement Learning

arXiv:2607.03600v1 Announce Type: cross Abstract: Adversarial robustness in Unsupervised Domain Adaptation (UDA) remains a significant challenge due to noisy pseudo labels and inherent distributional

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving

arXiv:2509.08269v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly integrated with evolutionary computation to support optimization tasks. This survey primarily fo

A Technical Survey of Reinforcement Learning Techniques for Large Language Models

arXiv:2507.04136v2 Announce Type: replace Abstract: This survey offers a comprehensive foundation on the integration of RL with language models, highlighting prominent algorithms such as Proximal Poli

A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning

arXiv:2606.16933v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) systems often degrade when operating conditions differ from those previously encountered, reflecting distributiona

ACE: Agentic Control for Embodied Manipulation via Zero-shot Workflow Reasoning

arXiv:2607.04162v1 Announce Type: cross Abstract: Open-ended tabletop manipulation requires agents to not only understand natural language but also adapt to dynamic environments and execution failures

safetyarxiv-cs-lg

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI

arXiv:2607.04426v1 Announce Type: new Abstract: Embodied AI is moving from isolated perception or action modules toward physical agents that understand, plan under goals, act through robot bodies, mon

agentsarxiv-cs-ro

ACPO: Adaptive Credit Policy Optimization via Fine-Grained Surrogate Entropy

arXiv:2607.03126v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has substantially improved the reasoning ability of large language models (LLMs), but sparse outcome rewards still make to

Adaptive Time-step Training for Enhancing Spike-Based Neural Radiance Fields

arXiv:2507.23033v2 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) provide an energy-efficient computing paradigm for neural rendering, but existing spike-based Neural Radiance Field (

researcharxiv-cs-cv

Adversarial LassoNet: Robust Feature Selection via Stability-Driven Sparse Learning

model-releasesarxiv-cs-lg

arXiv:2607.03839v1 Announce Type: new Abstract: Sparse feature selection is critical for high-dimensional machine learning, yet traditional ell_1-regularized methods are often brittle under observatio

Agent-driven Long-tail Simulation for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2607.04331v1 Announce Type: cross Abstract: Evaluating autonomous driving systems in closed-loop settings requires realistic and interactive simulation, yet existing simulators largely rely on l

Local Ai

Agent Reinforcement Learning via Pivotal-Aware Self-Feedback Retry

arXiv:2607.03702v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong decision-making capabilities in long-horizon interactive tasks, yet they still struggle to effective

local-aiarxiv-cs-ai

Agent Step Value: State-Transition Measurement with State-Grounded LLM Evaluators

arXiv:2607.04419v1 Announce Type: new Abstract: Most agent evaluations collapse a multi-step trace into a final answer, a success flag, or a trajectory-level score. These aggregates obscure the diagno

AgentFoX: LLM Agent-Guided Fusion with eXplainability for AI-Generated Image Detection

arXiv:2603.23115v2 Announce Type: replace Abstract: The realism of AI-generated images (AIGI) poses increasing challenges for reliable forensic detection, where heterogeneous expert detectors may prod

AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World Environments

arXiv:2607.05174v1 Announce Type: new Abstract: Language agents, i.e., LLM agents, progress rapidly and are increasingly deployed in production environments. This trend underscores the urgent need for

Agentic AI-RAN: Enabling Intent-Driven, Explainable and Self-Evolving Open RAN Intelligence

arXiv:2602.24115v2 Announce Type: replace Abstract: Open RAN (O-RAN) exposes rich control and telemetry interfaces across the Non-RT RIC, Near-RT RIC, and distributed units, but also makes it harder t

agentsarxiv-cs-lg

Agentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions

arXiv:2607.03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intel

agentsarxiv-cs-ai

Agentic IoT: Architectures, Applications, and Challenges Toward the Internet of Agents

arXiv:2607.04219v1 Announce Type: new Abstract: The integration of AI into Internet of Things (AIoT) systems has gradually transformed them from passive data collection infrastructures into intelligen

agentsarxiv-cs-ai

Local Ai

Agentic-V2X: Small Language Model Agents for Deadline-Aware V2X Scheduling in 5G/6G Networks

arXiv:2607.04290v1 Announce Type: cross Abstract: Large Language Models (LLMs) are proposed as control interfaces for next-generation networks, but their latency, hallucinations, and lack of control g

local-aiarxiv-cs-ai

Agentic Very Long Video Understanding

arXiv:2601.18157v3 Announce Type: replace Abstract: The advent of always-on personal AI assistants, enabled by all-day wearable devices such as smart glasses, demands a new level of contextual underst

AGL-1: The Enterprise AI Governance Layer as a Control Plane for Trusted Enterprise Intelligence

arXiv:2607.03516v1 Announce Type: cross Abstract: Enterprise artificial intelligence is moving from isolated experimentation toward operational dependency across copilots, retrieval-augmented generati

Air-Plan: Query-Optimized Topology Selection for Over-the-Air Decentralized Federated Learning

arXiv:2607.04254v1 Announce Type: cross Abstract: Over-the-air (OTA) aggregation exploits the superposition property of wireless multiple-access channels to aggregate model updates from multiple devic

Aligning Language Models with Selective Prediction

arXiv:2607.03528v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as critical decision-making components in high-stakes real-world AI systems, rendering LLM reli

Alleviating Sparse Rewards by Modeling Step-Wise and Long-Term Sampling Effects in Flow-Based GRPO

arXiv:2602.06422v2 Announce Type: replace Abstract: Deploying GRPO on Flow Matching models has proven effective for text-to-image generation. However, existing paradigms typically propagate an outcome

researcharxiv-cs-cv

An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression

arXiv:2504.18433v3 Announce Type: replace Abstract: Uncertainty quantification is crucial in machine learning, yet most (axiomatic) studies of uncertainty measures focus on classification, leaving a g

Analytical Standard Errors for Exploratory Factor Solutions

arXiv:1811.05336v2 Announce Type: replace-cross Abstract: Inference for factor models is often hampered by the lack of tractable and accurate variance estimates, which can materially distort downstrea

AnchorVLA: Bridging Discrete Decisions and Continuous Trajectories for Vision-Language-Action Planning

arXiv:2607.03182v1 Announce Type: cross Abstract: Autonomous driving planning requires translating navigation intent, traffic rules, dynamic interactions, and language instructions into executable con

Applications

AnyDesign: Versatile Area Fashion Editing via Mask-Free Diffusion

arXiv:2408.11553v5 Announce Type: replace Abstract: Fashion image editing aims to modify a person's appearance based on a given instruction. Existing methods require auxiliary tools like segmenters an

applicationsarxiv-cs-cv

AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compression

arXiv:2512.13956v4 Announce Type: replace-cross Abstract: Cloud-native systems have made operational work both more powerful and harder to automate: incidents unfold across microservices, logs and met

agentsarxiv-cs-ai

Applications

Aperture-aware Dispersion 5-D Light-field Imaging Spectrometer

arXiv:2607.04635v1 Announce Type: new Abstract: Enhancing perceptual dimensions while miniaturizing imaging systems presents significant challenges for high-dimensional visual sensing. Conventionally,

applicationsarxiv-cs-cv

AquaStereo: Enabling Underwater Stereo Matching via Depth-Conditioned Diffusion and Geometry Self-Distillation

arXiv:2607.04303v1 Announce Type: new Abstract: Learning-based stereo matching models struggle in underwater environments due to scarce in-domain data and the difficulty of extracting discriminative c

safetyarxiv-cs-cv