Search: “framework”

A Vocabulary for Multi-Agent Automated Research Systems

arXiv:2607.22682v1 Announce Type: new Abstract: We introduce a vocabulary for automated research systems built from one or more agents to make their design choices easier to describe and compare. The

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Accuracy Hides How Language Models Fail: Measuring Failure States Under Matched Output Budgets

DGX agent

arXiv:2607.24268v1 Announce Type: new Abstract: Language-model benchmarks collapse two distinct measurement questions into a single accuracy score: whether a response reached an evaluable state, and w

model-releasesarxiv-cs-cl

28 Jul 2026

ACM: Agentic Context Management for Long Horizon Tasks

arXiv:2607.23809v1 Announce Type: new Abstract: Agentic tasks are inherently long-horizon and multi-turn, constantly accumulating context through interactions with the environment. Existing context co

Act, Think or Abstain: Complexity-Aware Adaptive Inference for Vision-Language-Action Models

arXiv:2603.05147v2 Announce Type: replace Abstract: Current research on Vision-Language-Action (VLA) models predominantly focuses on enhancing generalization through reasoning techniques. While effect

Adversarial Test-Hardening for AI-Written Code: An Instrument Autopsy and a Pre-Registered Causal Estimate of the Critic Loop

arXiv:2607.23002v1 Announce Type: cross Abstract: Large language models increasingly write both code and the tests meant to check it; coverage records what ran, not what was verified. We study an adve

Agentic Autoresearch for CT Reconstruction

arXiv:2607.22824v1 Announce Type: cross Abstract: Comparing CT reconstruction methods fairly is labor-intensive and largely manual, and many benchmarks use idealized data. We ask whether a large langu

AI-generated Images Challenge Visual Trust in High-risk Scenarios

arXiv:2607.22745v1 Announce Type: cross Abstract: Rapid advances in image generation are eroding the evidentiary value of visual content in settings where authenticity can affect public safety and per

Tutorials

AI Strategy: How to Choose What AI Product to Implement

arXiv:2607.23733v1 Announce Type: cross Abstract: Firms struggle to choose AI projects that pay off: two projects can look equally promising to smart, motivated stakeholders and yet deserve opposite d

tutorialsarxiv-cs-ai

An Interactive Vision Language Platform for Cognitive Remediation in Schizophrenia

arXiv:2607.22721v1 Announce Type: cross Abstract: Cognitive remediation tasks often require patients to perform structured actions involving object manipulation and sequential reasoning. For patients

Asymmetric Hierarchical Anchoring for Robust Audio-Visual Cross-Modal Generalization

arXiv:2602.03570v2 Announce Type: replace Abstract: Audio-visual joint representation learning under Cross-Modal Generalization (CMG) aims to transfer knowledge from a labeled source modality to an un

safetyarxiv-cs-lg

ATCNet-CIAM for Multi-Session Motor Imagery EEG Signal Classification

arXiv:2607.23522v1 Announce Type: new Abstract: Motor imagery (MI)-based electroencephalography is widely used in non-invasive brain--computer interfaces (BCIs), but robust decoding remains challengin

ATLAS: Automated Approximation of Transformers for Efficient Homomorphic Inference in One Hour

arXiv:2607.23478v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) provides strong cryptographic guarantees for private inference, but deploying transformer models under FHE remains

AutoWorld: Learning Multi-Agent Traffic Simulation with Self-Supervised World Models

arXiv:2603.28963v2 Announce Type: replace-cross Abstract: Simulation with realistic traffic agents is essential for validating autonomous driving systems. Existing data-driven simulators learn agent b

Local Ai

CADER: Confidence-Aware Dynamic Evidence Reasoning for Long-Video Understanding

arXiv:2607.24582v1 Announce Type: cross Abstract: Long-video understanding increasingly relies on large vision-language models and tool-augmented reasoning, but most systems apply the same inference p

local-aiarxiv-cs-ai

Calibrated Tree-Neural Fusion for Fine-Grained Vegetation Community Classification

arXiv:2607.24160v1 Announce Type: new Abstract: Accurate vegetation-community classification is essential for ecological monitoring, habitat assessment, and evidence-based environmental management in

researcharxiv-cs-lg

CallBench: A Benchmark for Dual-Goal Coordination in Phone Call Assistants

arXiv:2607.22635v1 Announce Type: new Abstract: Target-oriented dialogue systems have demonstrated strong capabilities in completing user goals through interactive conversations. However, existing stu

CALMRec: Causally Aligned Language Memory for Long-Horizon Recommendation

arXiv:2607.23647v1 Announce Type: cross Abstract: Large language models (LLMs) can summarize heterogeneous user evidence in natural language, but current LLM recommenders often collapse enduring prefe

Co-Evolving Graph and Text Memory for Training-Free Multi-Hop Question Answering

arXiv:2607.23278v1 Announce Type: new Abstract: Multi-hop question answering requires coordinating relational and textual evidence across reasoning steps, a combination neither a text corpus nor a kno

researcharxiv-cs-cl

Applications

Co-planning of Flight Corridors and Communication Infrastructure for Urban Drone Logistics Networks

arXiv:2607.23989v1 Announce Type: new Abstract: Reliable wireless connectivity is essential for urban air mobility (UAM) networks in dense urban environments. It is therefore imperative to carefully p

applicationsarxiv-cs-ro

Concept-based Visual Counterfactual Explanations with Diffusion Models

arXiv:2607.22544v1 Announce Type: new Abstract: Visual counterfactual explanations aim to answer 'what minimal change to this image would flip the model's prediction?', and are increasingly important

safetyarxiv-cs-ai

Continual Knowledge Consolidation LORA for Domain Incremental Learning

arXiv:2510.16077v2 Announce Type: replace-cross Abstract: Domain Incremental Learning (DIL) is a sub-branch of continual learning that aims to address the never-ending arrival of new domains without c

Continual-RL for Generalization in Autonomous Racing on the RoboRacer Platform

arXiv:2607.24320v1 Announce Type: new Abstract: A key challenge in modern robotics is to adapt to changing environments, a challenge that is exacerbated when simulations cannot encompass every possibl

safetyarxiv-cs-ro

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation

model-releasesarxiv-cs-cv

arXiv:2607.23860v1 Announce Type: cross Abstract: Deep ensembles provide the most reliable uncertainty estimates in deep learning, but their cost grows linearly with the number of members. Implicit en

Cost-Aware Recovery-Pathway Identification and Bayesian Optimization for Autonomous Materials Discovery

arXiv:2607.23896v1 Announce Type: new Abstract: Autonomous laboratories automate experimental execution, but a campaign must also decide which recovery pathway merits optimization. We formulate this a

Tutorials

Counterfactual Motion Reliability Learning for Robust UAV Tracking

arXiv:2607.23209v1 Announce Type: new Abstract: Infrared unmanned aerial vehicle (UAV) tracking is challenging because the target is often small, low-contrast, and easily confused with thermal distrac

tutorialsarxiv-cs-cv

Covariance Last-Layer Ensembles: Function-Space Diversity for Efficient Uncertainty Quantification

arXiv:2607.23856v1 Announce Type: new Abstract: A Last-Layer Ensemble (LLE), K linear units on one shared frozen feature map, is an efficient single-pass approach to the disagreement-based epistemic u

researcharxiv-cs-lg

Tutorials

CrossSpine: Multi-scale Cross-sequence Attention with Anatomical Priors for Automated Pfirrmann Grading

arXiv:2607.22728v1 Announce Type: new Abstract: Automated grading of Lumbar Disc Degeneration is essential for the objective quantification of structural changes associated with low back pain. Observi

tutorialsarxiv-cs-cv

CuraWeb: Joint Optimization of Quality, Redundancy, and Diversity for Web-Scale Pretraining Data

arXiv:2607.22662v1 Announce Type: new Abstract: Open-web corpora curated via highly selective filters, such as FineWeb-Edu and DCLM, constitute the core of LLM pretraining data and have significantly

Data-Driven Diffusion Processes on Differential Forms via the Projected Ambient Connection Laplacian

arXiv:2607.23192v1 Announce Type: cross Abstract: We develop a data-driven approximation of the projected ambient connection Laplacian acting on differential forms over smooth Riemannian manifolds sam

researcharxiv-cs-lg

DeepFaith: Evidence-Grounded LLMs for Faithful Incident Reporting in Multi-Stage APT Defense

arXiv:2607.24348v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) are difficult to detect and interpret due to their multi-stage and stealthy nature. While recent autonomous defense

DeepLens Diagnosis Agent: Agentic Workflow Design Lets a Small Reasoning Model Compete with Frontier LLMs

arXiv:2607.22555v1 Announce Type: new Abstract: Medical diagnosis is a multi-stage process: extract facts, consult knowledge, generate a differential analysis, and select the best diagnosis with expla

Dementia Etiology Diagnosis via Collaborative Meta Knowledge Enhancement

arXiv:2607.22770v1 Announce Type: cross Abstract: Although artificial intelligence (AI) has shown promising performance in several medical tasks, accurate dementia etiology diagnosis with AI remains c

safetyarxiv-cs-cv

Hardware

Developing Healthcare Robotics with GPU-Native Medical Physics Simulation

Healthcare robotics struggles with data scarcity, limited generalization to rare clinical scenarios, and slow prototyping due to the need for annotated demonstrations and costly experimental setups. N

hardwarenvidia-developer

Diffusion-Guided Search via Exponential Tilting (DiffTilt): An Application to Falsification of Safety-Critical Systems

model-releasesarxiv-cs-lg

arXiv:2607.23134v1 Announce Type: new Abstract: Discovering rare safety-critical failures in autonomous and cyber-physical systems is a fundamental challenge in verification and validation. Existing f

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video

arXiv:2607.23132v1 Announce Type: new Abstract: Assessing the severity of a traffic accident scenario is important to decide which emergency service to dispatch. Missing an ambulance dispatch on a ped

agentsarxiv-cs-cv

DreamStyle3D: Efficient 3D Stylized Asset Generation via Dual-Attention Disentanglement

arXiv:2607.24721v1 Announce Type: new Abstract: With the growth of gaming, animation, and virtual reality industries, the demand for efficient generation of stylized 3D assets is rapidly increasing. H

DSTFView: Multi-View Cloud-Edge Workload Forecasting with Dual-Input Spatio-Temporal-Frequency Modeling

arXiv:2607.22565v1 Announce Type: new Abstract: With the widespread deployment of edge-side AI inference, edge platforms are increasingly required to support latency-sensitive, highly concurrent, and

DuoAD: Leveraging [CLS] Dual Characteristics for Training-Free Few-Shot Anomaly Detection

arXiv:2607.23924v1 Announce Type: cross Abstract: Vision foundation models have enabled strong training-free anomaly detection (AD). However, most existing approaches rely primarily on independent loc

Effective Receptive Field Ordering Matters for Infrared Small Target Detection

arXiv:2607.23994v1 Announce Type: new Abstract: In this work, we investigate a previously unexplored architectural dimension for infrared small target detection: the organization of effective receptiv

Efficiency Matters in Autonomous Research

arXiv:2607.24647v1 Announce Type: new Abstract: AI-driven autonomous research (AR) systems are becoming increasingly effective across a broad range of tasks. Their performance, however, is still evalu

safetyarxiv-cs-ai

Epistemic Norms for AI Safety and Alignment Research

arXiv:2607.24243v1 Announce Type: new Abstract: Mainstream AI research emphasises capability growth and tolerates low failure rates when average-case performance is high. AI safety and alignment resea

safetyarxiv-cs-ai

Evaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests

arXiv:2607.22883v1 Announce Type: cross Abstract: While Large Language Models (LLMs) show great promise for automating unit test generation, recent studies suggest that the quality of generated tests

Evaluating LLMs as Interpretable Controllers for Dynamical Systems

arXiv:2607.22609v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for decision-making and reasoning tasks, yet their potential as controllers for physical systems rema

Applications

Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review

arXiv:2607.24601v1 Announce Type: cross Abstract: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to under

applicationsarxiv-cs-ai

Evidence Attribution in Visual Document Understanding without Coordinates or Region Labels

arXiv:2607.24651v1 Announce Type: cross Abstract: Reliable visual document understanding requires a model to attribute each answer to the evidence regions that support it. Recent benchmarks and system

researcharxiv-cs-cl

Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution

arXiv:2607.22546v1 Announce Type: new Abstract: Machine translation (MT) systems continue to produce gender-biased translations. In a time where self-expression is paramount, mistranslations based on

researcharxiv-cs-cl

Fairness Interventions in Classification: A Study on AI Explainability

arXiv:2407.14766v4 Announce Type: replace-cross Abstract: This paper presents a philosophical and experimental study of fairness interventions in AI classification, centered on the explainability and

Applications

FedSLIM: Privacy-Preserving Federated MDL-Based Descriptive Pattern Mining Across Data Silos

arXiv:2607.23236v1 Announce Type: cross Abstract: Federated learning has achieved considerable success for predictive modelling, yet federated descriptive analytics remains largely unexplored. Existin

applicationsarxiv-cs-ai