Search: “framework”

ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding

arXiv:2607.24743v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundam

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Closed-Loop Validation-Repair for Healthcare Interoperability: A Multi-Model Study of Schema Compliance in Clinical LLMs

DGX agent

arXiv:2607.24371v1 Announce Type: cross Abstract: Healthcare interoperability requires AI systems to produce structured outputs conforming to standardized schemas including ICD-10 for diagnostic codin

model-releasesarxiv-cs-ai

28 Jul 2026

Co-Harness: Co-Evolving Harnesses and Model Weights for LLM Agents

arXiv:2607.22688v1 Announce Type: new Abstract: Post-training agents for automated AI research requires optimizing not only model parameters, but also the runtime harness that shapes how research traj

Co-Learning for Missing Arbitrary Modalities in Multi-modal Classification

arXiv:2607.24683v1 Announce Type: cross Abstract: Multi-modal classification leverages complementary information across diverse data sources to enhance predictive performance. However, real-world scen

applicationsarxiv-cs-ai

Agents

Coherent Without Grounding, Grounded Without Success: Observability and Epistemic Failure

arXiv:2603.28371v2 Announce Type: replace-cross Abstract: When an agent can articulate why something works, we typically take this as evidence of genuine understanding. This presupposes that effective

agentsarxiv-cs-ai

Color Fundus Photography Analysis: Co-evolution of Data, Preprocessing, and Modeling toward Multimodal AI

arXiv:2607.23972v1 Announce Type: new Abstract: Color Fundus Photography (CFP) is a primary non-invasive imaging modality for large-scale screening of ophthalmic and systemic diseases. Existing survey

researcharxiv-cs-cv

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

arXiv:2607.23089v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled automated kernel generation and optimization, but most existing approaches rely on surface

Compressing LLMs with MoP: Mixture of Pruners

model-releasesarxiv-cs-lg

arXiv:2602.06127v2 Announce Type: replace Abstract: The high computational demands of Large Language Models (LLMs) motivate methods that reduce parameter count and accelerate inference. In response, m

ConFusion: Continuous Fusion Space Learning for Fine-Grained Controllable Infrared and Visible Image Fusion

arXiv:2607.23600v1 Announce Type: new Abstract: Controllable infrared-visible image fusion aims to integrate complementary thermal and structural information with flexible region-aware modulation, pro

safetyarxiv-cs-cv

Consistent Evidence, Robust Recognition: Faithful Attribution Regularization under Geometric Transformations

arXiv:2607.23835v1 Announce Type: new Abstract: Attribution methods are widely used to characterize the evidence underlying model predictions, yet their potential to improve model behavior remains und

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds

arXiv:2607.23448v1 Announce Type: cross Abstract: Expensive constrained optimization problems in real-world industry design often involve constraint thresholds that are difficult to determine in advan

Context-Aware Concept Distillation for Trustworthy Flood Prediction

arXiv:2607.23237v1 Announce Type: cross Abstract: Effective flood risk management relies on accurate forecasting, yet the 'black box' nature of stateof-the-art Deep Learning models creates a barrier t

Contrastive Parameter Disentanglement for Multi-modal Remote Sensing Image Generation

arXiv:2607.23673v1 Announce Type: new Abstract: Existing remote sensing image generation methods are largely confined to single-modality synthesis and therefore fail to exploit the complementary infor

Tutorials

Controlling Embedding Spaces with Text-Conditioned Transformations

arXiv:2607.22919v1 Announce Type: cross Abstract: Multimodal embedding spaces in models like CLIP enable powerful capabilities such as semantic similarity retrieval and cross-modal zero-shot classific

tutorialsarxiv-cs-ai

Coordinated Networking for On-Device Agent-Augmented Real-Time Communication

arXiv:2607.22854v1 Announce Type: new Abstract: AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents aut

Covariance-Boosted Gaussian Processes for Spatiotemporal Irregularities

arXiv:2607.23018v1 Announce Type: cross Abstract: Nonstationary Gaussian process (GP) models are powerful tools for capturing input-dependent variability by adapting to observed data. However, with li

safetyarxiv-cs-lg

CReF: Cross-modal and Recurrent Fusion for Depth-conditioned Humanoid Locomotion

arXiv:2603.29452v3 Announce Type: replace Abstract: Stable traversal over geometrically complex terrain increasingly requires exteroceptive perception, yet prior perceptive humanoid locomotion methods

applicationsarxiv-cs-ro

D3O: Dynamic Distribution Distillation for Ordinal Regression

arXiv:2607.23575v1 Announce Type: cross Abstract: Ordinal regression is widely used in scenarios where labels are discrete yet inherently ordered. In practice, however, ordinal labels are often obtain

safetyarxiv-cs-ai

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data

arXiv:2607.24717v1 Announce Type: cross Abstract: Pretraining data processing is critical to the downstream performance of Large Language Models (LLMs). However, many existing approaches define a fixe

Decentralized Granular Access Control for Agentic AI Systems in Critical Infrastructure

arXiv:2607.22611v1 Announce Type: new Abstract: The deployment of autonomous AI agents in production infrastructure introduces fundamental security challenges that traditional role-based access contro

Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data

arXiv:2602.10381v2 Announce Type: replace Abstract: Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches ar

applicationsarxiv-cs-lg

Dependency-Guided Code Generation: Structured Matrix Decomposition and Consistency-Guided Refinement

arXiv:2607.16692v2 Announce Type: replace-cross Abstract: The increasing complexity of modern software systems has made automated code generation a fundamental task in software engineering. However, e

safetyarxiv-cs-cl

Agents

DeReCo: Decoupling Representation and Coordination Learning for Object-Adaptive Decentralized Multi-Robot Cooperative Transport

arXiv:2603.08111v2 Announce Type: replace Abstract: Generalizing decentralized multi-robot cooperative transport across objects with diverse shapes and physical properties remains a fundamental challe

agentsarxiv-cs-ro

Development of Vision-Language Model-based GNSS Spoofing Detection for Autonomous Vehicle Navigation

arXiv:2607.23962v1 Announce Type: new Abstract: Autonomous vehicles (AVs) depend on Global Navigation Satellite Systems (GNSS) for localization and navigation, making them vulnerable to spoofing attac

local-aiarxiv-cs-cv

Direction-adaptive Mamba: Spatial-Frequency Dual-Domain Collaborative Learning for PolSAR Image Classification

arXiv:2607.23464v1 Announce Type: cross Abstract: Deep learning dominates polarimetric synthetic aperture radar (PolSAR) image classification, with Mamba architectures serving as favorable backbones d

applicationsarxiv-cs-cv

DishSeg24k: A Large-Scale Benchmark for Food Segmentation with Stochastic Expert Decoding

arXiv:2607.23070v1 Announce Type: new Abstract: Food segmentation is essential for applications such as intelligent catering, dietary assessment, and recommendation. However, existing benchmarks fail

Agents

Distributed Coordination for Resilient Multi-UAV Remote Sensing: A Photovoltaic Inspection Case Study

arXiv:2607.24482v1 Announce Type: new Abstract: Deploying multiple UAVs for remote sensing enables proportional reductions in mission time, but realizing these benefits requires the fleet to coordinat

agentsarxiv-cs-ro

Do LLMs Know Their Vulnerable Scenarios?

arXiv:2607.23496v1 Announce Type: new Abstract: Safety-aligned large language models are trained to refuse harmful requests, yet embedding the same requests in particular scenarios can bypass their sa

Does Faithfulness-Guided Alignment Hurt Accuracy? Unlocking Accurate and Faithful Post-Retrieval Reasoning

arXiv:2602.01348v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) can achieve strong answer accuracy on multi-hop questions, but outcome-level rewards often leave reasoning trac

safetyarxiv-cs-cl

DP-IVON-Gradsq: Differentially Private Squared-Gradient Improved Variational Online Newton

arXiv:2607.23649v1 Announce Type: new Abstract: Differential privacy provides formal privacy guarantees for training neural networks on sensitive data, while Bayesian deep learning offers a principled

researcharxiv-cs-lg

DraftExpert: Expansion-Aware Self-Speculative Decoding for End-Device MoE Inference

arXiv:2607.24434v1 Announce Type: cross Abstract: Large Mixture-of-Experts (MoE) language models are attractive for end-device deployment because only a small subset of experts is active per token, bu

DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces

arXiv:2603.05607v2 Announce Type: replace-cross Abstract: Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by sm

DY-LUT: Depth-Aware YCbCr Lookup Tables for Real-Time Underwater Image Enhancement

arXiv:2607.22801v1 Announce Type: cross Abstract: Underwater image enhancement is challenged by spatially non-uniform, wavelength-dependent attenuation. Propagation distance and wavelength govern this

DynaCalKV: Key-Value Cache Compression via Head Grouping and Adaptive Rank Allocation

model-releasesarxiv-cs-lg

arXiv:2607.24331v1 Announce Type: new Abstract: As the inference phase of Large Language Models (LLMs) requires handling long context windows, the Key-Value (KV) cache initially appears to address thi

EEGForceFusion: Joint Tokenised-Continuous Representation Learning for Subject-Independent Grasp Force Decoding

arXiv:2607.24126v1 Announce Type: cross Abstract: Brain-machine interfaces provide a link between neural activity and external devices, enabling restoration of motor function and advancing human-machi

Embeddings based Anomaly Detection for Cleaning Global Crop Type Reference Datasets

arXiv:2607.23908v1 Announce Type: new Abstract: High quality reference data remain a critical bottleneck for crop-type mapping at any spatial and temporal scale. Operational systems such as WorldCerea

local-aiarxiv-cs-cv

Hardware

Energy Constrained Hierarchical Underwater Monitoring via Local Multi-Agent RAG

arXiv:2607.24313v1 Announce Type: cross Abstract: Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data fr

hardwarearxiv-cs-cv

Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection

arXiv:2512.07246v2 Announce Type: replace Abstract: Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent s

researcharxiv-cs-cl

Escaping the Euclidean Void: Manifold-Informed Flow Matching for Sequential Recommendation

arXiv:2607.23762v1 Announce Type: cross Abstract: Conventional recommenders capture users' preferences by optimizing observed user-item relations, whereas continuous generative recommendation addition

EventOD: Event-Aware OD Flow Generation via LLM-Guided Semantic Modulation

arXiv:2607.22655v1 Announce Type: new Abstract: Estimating origin-destination (OD) flows under disruptive events is important for disaster response and urban resilience. Existing deep OD models traine

Every Client Is an Environment: Federated De-confounding for Spatio-Temporal Forecasting

arXiv:2607.24218v1 Announce Type: cross Abstract: Federated learning has emerged as a promising paradigm for spatio-temporal forecasting (STF), enabling collaborative model training without sharing ra

Eviction as Estimation: A Fixed-Lag Smoothing View of Test-Time Memory, and When Measuring Beats Accumulating

arXiv:2607.24667v1 Announce Type: new Abstract: A language model with a bounded working memory must repeatedly decide which stored items to keep. Every deployed method decides the moment an item arriv

safetyarxiv-cs-ai

Hardware

Evo-DKD: Dual-Knowledge Decoding for Autonomous Ontology Evolution in Large Language Models

arXiv:2507.21438v2 Announce Type: replace Abstract: Ontologies and knowledge graphs require continuous evolution to remain comprehensive and accurate, but manual curation is labor intensive. Large Lan

hardwarearxiv-cs-ai

Evolving from Lessons: Skill-Augmented Table Graph Reasoning for Operation-wise Table Question Answering

arXiv:2607.22633v1 Announce Type: new Abstract: Table Question Answering (TableQA) aims to reason over tables to answer user queries. Existing research treats all questions uniformly and evaluates sol

Explainable Reinforcement Learning via Physics-Aware Policy Distillation

model-releasesarxiv-cs-lg

arXiv:2607.24672v1 Announce Type: new Abstract: In safety-critical sectors such as robotics and automotive engineering, the deployment of Deep Reinforcement Learning (DRL) is often hindered by the bla

Explaining BiomedCLIP with Weighted Banzhaf Interactions Supported by Tree-Gram Parsing

arXiv:2607.23368v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are demonstrating significant capabilities in medical tasks like radiology analysis, yet providing faithful and interpre

Falsifiable Commitment Planning for Self-Correcting Web Agents

arXiv:2607.24167v1 Announce Type: new Abstract: Long-horizon web agents often go off track before final failure: a trajectory can remain locally plausible even after the current state, reused skill, o

Fashion-3DLR: A Controllable 3D Garment Generation Using Pairwise Fashion Elements for Intelligent Design

arXiv:2607.23189v1 Announce Type: cross Abstract: AI-generated content (AIGC) has made significant progress, with 2D generative models becoming ready-to-use tools for the digital fashion industry. How