Search: “models”

Credit Without Ground Truth: Auditing Step-Level Credit Assignment in LLM Agents Against Executed Replay

arXiv:2608.19760v1 Announce Type: cross Abstract: Audited against causal ground truth from executed replay in a single-agent tool environment (ALFWorld), none of the step-level credit signals used to

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Demons on a Budget: Adaptive Measurement Placement at the Entanglement Phase Transition

DGX agent

arXiv:2608.19248v1 Announce Type: cross Abstract: Monitored quantum circuits exhibit a measurement-induced phase transition between volume-law and area-law entanglement as a function of the measuremen

model-releasesarxiv-cs-lg

21 Aug 2026

DIFFCZSL: Compositional Zero-Shot Learning Regularized by Diffusion Representations

arXiv:2608.19871v1 Announce Type: new Abstract: Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object compositions by leveraging knowledge of primitive concepts learned fro

safetyarxiv-cs-cv

Tutorials

DPC-Net: Dual-Prior Collaborative Network for All-in-One Image Restoration

arXiv:2608.20141v1 Announce Type: new Abstract: All-in-One Image Restoration (AiOIR) aims to handle diverse degradations within a unified model. However, existing methods often overlook image semantic

tutorialsarxiv-cs-cv

Agents

FlowEvo: Self-Evolving Agents through the Co-Evolution of Workflows and Executable Skills

arXiv:2607.21596v2 Announce Type: replace Abstract: Large language model agents can adapt to complex tasks by constructing workflows at inference time, but procedures discovered in one episode are usu

agentsarxiv-cs-ai

From Street View Imagery to Street Quality Indicators: Vision Language Inference for the Suburban 15-minute City

arXiv:2608.20026v1 Announce Type: new Abstract: Streetscape quality has become a central concern in contemporary urban planning, particularly within the framework of the pedestrian-friendly 15-minute

applicationsarxiv-cs-cv

G-CARL: Grounded Checklist-Aligned Reward Learning for Patient-Oriented Medical Report Interpretation

arXiv:2608.20331v1 Announce Type: cross Abstract: Personalized interpretation of medical reports has emerged as an increasingly important need among patients. Addressing this need requires both eviden

G3Ego: Gaze-Guided Graphs for Egocentric Action Understanding

arXiv:2608.20157v1 Announce Type: new Abstract: Egocentric action understanding is often addressed using large video models pretrained on extensive exocentric datasets. However, many first-person acti

researcharxiv-cs-cv

Grounded verification of chemical and materials reasoning: detection is the bottleneck

arXiv:2607.17417v2 Announce Type: replace Abstract: Language models are moving into chemistry and materials discovery workflows, where a wrong molecular formula, space group, or formation energy can s

researcharxiv-cs-lg

HarmoHOI: Harmonizing Appearance and 3D Motion for Multi-view Hand-Object Interaction Synthesis

arXiv:2607.17097v2 Announce Type: replace Abstract: Hand-Object Interaction (HOI) synthesis is a cornerstone for animation production and embodied AI. Despite the strong priors of video foundation mod

applicationsarxiv-cs-cv

Learning-Augmented Power System Operations: A Unified Optimization View

arXiv:2505.05203v3 Announce Type: replace-cross Abstract: With the increasing penetration of renewable energy and inverter-based resources, traditional physics-based power-system operation faces growi

Learning how to Forget: Fine-tuning for Long-Context Sparse Attention

arXiv:2608.19920v1 Announce Type: new Abstract: A lot of prior work addressed key-value (KV) cache selection and compression by sparse attention to enable long-context inference for transformer langua

safetyarxiv-cs-cl

Learning piecewise-smooth dynamical systems

arXiv:2608.19785v1 Announce Type: cross Abstract: Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine lear

Longitudinal Bayesian Learning of Continuous Disease Position across the Alzheimer's Disease Continuum

arXiv:2608.19436v1 Announce Type: cross Abstract: Alzheimer's disease (AD) progresses as a continuous biological process, whereas most existing neuroimaging-based artificial intelligence methods remai

Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

arXiv:1905.11395v2 Announce Type: replace Abstract: Graph convolution network based approaches have been recently used to model region-wise relationships in region-level prediction problems in urban c

applicationsarxiv-cs-lg

Neural Prior Estimation: Learning Class Priors from Latent Representations

arXiv:2602.17853v2 Announce Type: replace-cross Abstract: Logit adjustment corrects class imbalance using the empirical class prior. We study whether a comparable class-frequency signal can instead be

researcharxiv-cs-cv

One Success Isn't Reliability: Thinkingbox, a Sandbox and Benchmark for Agents in Stateful Business Workflows

model-releasesarxiv-cs-cl

arXiv:2608.19741v1 Announce Type: new Abstract: Recent agent benchmarks increasingly ground evaluation in executable environments, from code repair to web navigation, app APIs, and function calling. Y

PhysSFI-Net: Physics-informed Geometric Learning of Skeletal and Facial Interactions for Orthognathic Surgical Outcome Prediction

arXiv:2601.02088v3 Announce Type: replace Abstract: Orthognathic surgery repositions jaw bones to restore occlusion and enhance facial aesthetics. Accurate simulation of postoperative facial morpholog

researcharxiv-cs-cv

PL-NBA: A Possession-level Universal Basketball Video Dataset Supporting Multiple Visual Understanding Tasks

model-releasesarxiv-cs-cv

arXiv:2608.19646v1 Announce Type: new Abstract: Visual understanding in sports has emerged as a hot topic in computer vision in recent years. Most existing basketball video datasets adopt single actio

PO-PDDL: Learning Symbolic POMDPs from Visual Demonstrations for Robot Planning Under Uncertainty

arXiv:2606.15654v2 Announce Type: replace-cross Abstract: Real-world robot task planning must operate under both stochastic action execution and partial observability, yet constructing Partially Obser

applicationsarxiv-cs-ai

Quantum Kernel Estimation for the Discovery of Early Lung Cancer Detection

arXiv:2608.19304v1 Announce Type: cross Abstract: Lung cancer screening with low-dose chest computed tomography reduces mortality, but its impact is limited by uptake, adherence, and management challe

Scale-Separated Conditioning for Style-Encoder-Free Diffusion Stylization

arXiv:2608.19719v1 Announce Type: cross Abstract: Reference-based diffusion stylization requires separating target geometry from transferable appearance. Existing tuning-based methods often rely on al

Stopping and Routing LLM Judge Panels

arXiv:2608.19802v1 Announce Type: new Abstract: LLM evaluation pipelines often have many candidate judges: general LLM-as-a-judge prompts, reward models, safety classifiers, confidence variants, and t

safetyarxiv-cs-cl

StreamSoccer: Event-Driven Memory for Streaming Soccer Commentary

arXiv:2608.19723v1 Announce Type: cross Abstract: Streaming video understanding requires models to causally update state as video arrives and organize growing history into semantic units that can evol

researcharxiv-cs-cl

SWE-bench Science: Can Coding Agents Resolve Engineering Tasks in Science?

model-releasesarxiv-cs-cl

arXiv:2608.19799v1 Announce Type: new Abstract: Software increasingly functions as part of the scientific instrument itself, making failures in scientific code capable of compromising not only program

Task-CoEvolve: Efficient Harness Optimization via Adaptive Validation Task Selection

arXiv:2608.20169v1 Announce Type: cross Abstract: We present a novel approach to efficient LLM agent harness optimization through adaptive validation task selection. Harness optimization iteratively r

TCP_alpha: Margin-Controlled Confidence estimation for reliable Music Information Retrieval

arXiv:2608.20326v1 Announce Type: cross Abstract: Deep neural networks are often overconfident, assigning high confidence even to incorrect predictions. Consequently, users lack a reliable signal for

Time-Uniform Self-Normalized Concentration for Discounted Least Squares: Limits and Corrections

arXiv:2608.19643v1 Announce Type: new Abstract: Self-normalized concentration inequalities are standard tools in bandit and reinforcement-learning analyses. A widely used weighted extension claims an

Towards On-Board Implementation of ML-Based Helicopter Weight Estimator

arXiv:2608.19210v1 Announce Type: cross Abstract: This paper focuses on the implementation of a novel supervised Machine Learning model for estimating helicopter weight during takeoff, utilizing exten

Ultra-High-Definition Restoration Transformers with Correlation Matching Transformation

model-releasesarxiv-cs-cv

arXiv:2608.20263v1 Announce Type: new Abstract: We propose UHDformer++, a general Transformer-based framework to solve numerous Ultra-High-Definition (UHD) image restoration tasks. UHDformer++ operate

When to Retrain: An Empirical Study of Retraining Policies for Streaming ML Under Concept Drift, Budget, and Latency Constraints

arXiv:2608.19488v1 Announce Type: new Abstract: Production machine learning systems degrade under concept drift, yet practitioners have little principled guidance on when to retrain. Retraining is cos

safetyarxiv-cs-lg

Your Turn: At Home Turning Angle Estimation for Parkinson's Disease Severity Assessment

arXiv:2408.08182v5 Announce Type: replace-cross Abstract: People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease

A Framework and Prototype for a Navigable Map of Datasets in Engineering Design and Systems Engineering

arXiv:2603.15722v3 Announce Type: replace-cross Abstract: The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Syste

Atrial Fibrillation Detection with Arbitrary Leads via a Codebook-Based Reconstruction-Classification Framework

arXiv:2608.18451v1 Announce Type: new Abstract: extbf{Background and Objective}: Reliable atrial fibrillation (AF) detection from electrocardiogram (ECG) signals remains challenging in real-world clin

Budget-First Tariff Recommendation (BFTR): A Complete Algorithmic Framework for Telecom Plan Recommendation without Overcharging

arXiv:2608.18723v1 Announce Type: cross Abstract: Telecom operators traditionally offer predefined tariff grids, forcing users to choose from a limited set of plans. This paper proposes BFTR (Budget-F

Competence, Not Accuracy: A Diagnostic for Reference-Free Judge Gates in Skill Optimization

arXiv:2608.18719v1 Announce Type: new Abstract: Text-space skill optimization adapts a frozen agent by evolving a natural-language skill document, accepting each candidate through a validation gate. E

DART-SD: Diamond-topology Aware Retrieval and Tuning for Self-Distillation of Multi-Turn Tool-Calling Agents

arXiv:2608.18524v1 Announce Type: cross Abstract: Equipping Large Language Models (LLMs) with multi-turn tool-calling capabilities is essential for building autonomous agents. However, progress is fun

safetyarxiv-cs-ai

Decomposing Wrong-Consensus Agreement in LLM Self-Consistency: A GPT-4.1 Case Study

arXiv:2608.18795v1 Announce Type: cross Abstract: Majority voting over multiple LLM samples is widely used to raise answer accuracy, yet its gain varies erratically: on hard questions it can even back

Escaping Local Minima Provably in Non-convex Matrix Sensing: A Deterministic Framework via Simulated Lifting

arXiv:2602.05887v3 Announce Type: replace Abstract: Low-rank matrix sensing is a fundamental yet challenging nonconvex problem whose optimization landscape typically contains numerous spurious local m

Local Ai

EVADE: Evidence-Verified Agentic Diagnosis with Escape

arXiv:2608.18833v1 Announce Type: new Abstract: Medical vision-language models (VLMs) can achieve high accuracy but remain unreliable: they are systematically overconfident, benefit little from test-t

local-aiarxiv-cs-cv

Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions

arXiv:2608.18539v1 Announce Type: cross Abstract: The remarkable capabilities of large language models (LLMs) are often undermined by their instability. Even subtle and semantically irrelevant changes

FACET: Preserving Source Intent and Executable State in Terminal Task Synthesis

arXiv:2608.18580v1 Announce Type: new Abstract: Training terminal agents requires scalable executable supervision, yet synthesizing high-quality terminal tasks remains challenging. Each task couples a

safetyarxiv-cs-ai

FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning

arXiv:2608.18311v1 Announce Type: cross Abstract: Federated multimodal models often assume every site has every modality, although hospitals differ in access to EHRs, chest radiographs, and ECGs. We s

applicationsarxiv-cs-ai

Finetuning Strategies for Querying Sounds by Vocal Imitation

arXiv:2608.19174v1 Announce Type: cross Abstract: This technical report describes our winning submission to the AES AIMLA 2025 Challenge on querying sound effects by vocal imitation. We investigate tw

FraudBench: Stress-Testing Policy-Grounded Banking Agents Against Adaptive Fraud

arXiv:2608.18136v1 Announce Type: new Abstract: Conversational agents now act for end users through tools while holding access to customer databases and internal policy documents that a caller can rea

GAPL: Grounded Action-effect Policy Learning for LLM-Based Trajectory Planning

arXiv:2608.18254v1 Announce Type: new Abstract: Trajectory planning for autonomous driving requires both high-level reasoning and precise low-level control. Large Language Models (LLMs) offer semantic

safetyarxiv-cs-ro

GreekBarRetrieval: A Benchmark for Greek Statutory Retrieval

model-releasesarxiv-cs-cl

arXiv:2608.18752v1 Announce Type: cross Abstract: Statutory retrieval is necessary for citation-grounded legal question answering, but remains underexplored for Greek. We introduce GreekBarRetrieval,

GS-VLA: Plug-and-Play Viewpoint Canonicalization for Frozen VLA Policies via Gaussian Splatting

arXiv:2608.19066v1 Announce Type: cross Abstract: This paper proposes a lightweight, plug-and-play framework that improves robustness to viewpoint shifts in Vision-Language-Action (VLA) policies witho