Search: “evaluation”

An Interpretable Deep Learning Framework for Discovery and Clinical Validation of Deep Radiomic Signatures in Tumor Classification

arXiv:2607.03593v1 Announce Type: cross Abstract: Imaging signatures are quantitative features extracted from medical images that provide clinically meaningful information for tumor diagnosis, charact

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Safety

Anticipatory Reinforcement Learning for Trajectory Tracking

DGX agent

arXiv:2607.03132v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) in industrial control often suffers from lag and overshoot due to purely reactive control based on the current trackin

safetyarxiv-cs-lg

7 Jul 2026

Hardware

AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms

arXiv:2607.03513v1 Announce Type: cross Abstract: We present AquaGen, the first all-atom, explicit solvent, periodic-boundary-condition-aware generative model that produces molecular configurations fr

hardwarearxiv-cs-lg

Attention Limited Reward Learning

arXiv:2607.04590v1 Announce Type: new Abstract: Pairwise human comparisons are a primary interface through which modern AI systems learn human preferences. RLHF and related alignment pipelines typical

safetyarxiv-cs-ai

Benchmarking API Drift in LLM-Generated Quantum Code Across Successive SDK Versions

arXiv:2607.04072v1 Announce Type: cross Abstract: Large language models can generate plausible quantum code, but it is unclear whether they can reliably target the specific software development kit (S

Beyond Scene Priors: Fine-Grained Traffic Scene Reasoning with Benchmarking and Query-Guided Small-Object Focus

arXiv:2607.04149v1 Announce Type: new Abstract: In safety-critical traffic scenarios, answering complex questions relies on minute, localized visual cues. However, standard Multimodal Large Language M

Beyond the Need for Speed: Energy-Aware Code Generation via Simulation-Guided Reinforcement Learning

arXiv:2607.04577v1 Announce Type: new Abstract: Code models strictly prioritize functional correctness, leaving software energy efficiency as an unoptimized byproduct. Training models to generate ener

applicationsarxiv-cs-lg

Biomechanics-aware Multi-view Markerless Motion Capture of Dexterous Hand Movements

arXiv:2607.02796v1 Announce Type: new Abstract: Markerless motion capture (MMC) techniques have been widely beneficial in biomechanical analysis of human movement; however, application to complex moti

Local Ai

Can Model Merging Improve Aggregation in DiLoCo?

arXiv:2607.03011v1 Announce Type: cross Abstract: Model merging techniques, which aggregate independently finetuned models into one to combine their capabilities, have become a topic of significant in

local-aiarxiv-cs-ai

CausalGame: Benchmarking Causal Thinking of LLM Agents in Games

arXiv:2607.04293v1 Announce Type: cross Abstract: Building AI Scientist agents with Large Language Models (LLMs) has recently attracted growing attention. Since scientific discovery fundamentally reli

Claim-Level Rubric Rewards for Video Caption Reinforcement Learning

arXiv:2607.05150v1 Announce Type: new Abstract: In this paper, we introduce Claim-Level Rubric Rewards (CuRe), a structured reward framework designed to address the reward-design bottleneck in reinfor

safetyarxiv-cs-cv

Continual Model Merging with Test-Time Adaptation for Whole-Slide Image Analysis

arXiv:2607.04755v1 Announce Type: new Abstract: Model merging offers a practical alternative to conventional continual learning by integrating independently fine-tuned models without retaining previou

Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy

arXiv:2607.03959v1 Announce Type: cross Abstract: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, highlighting the need for accurate and accessible screening tools. Optica

Local Ai

Curated retrieval versus open web search in public AI information services: a coverage-trust trade-off

arXiv:2607.05217v1 Announce Type: cross Abstract: Public institutions increasingly use large language models (LLMs) to answer citizens' questions, often pairing a curated knowledge base with live web

local-aiarxiv-cs-cl

Deep Learning Network-Temporal Models For Traffic Prediction

arXiv:2603.11475v2 Announce Type: replace Abstract: Accurate prediction of multivariate time series is essential for emerging network intelligent control, observability, and management functions. Exis

researcharxiv-cs-lg

Tutorials

Detecting Answer-Driven Reasoning in LLM-Based Educational Tutors via Truncated Chain-of-Thought Auditing

arXiv:2607.04572v1 Announce Type: new Abstract: Large language model (LLM) tutors often produce fluent step-by-step explanations, but a correct and pedagogically formatted response does not guarantee

tutorialsarxiv-cs-ai

DOGE shut down USAID, established by JFK in 1961. Before being shut down, the US Agency for International Development (USAID) was the larges…

DOGE shut down USAID, established by JFK in 1961. Before being shut down, the US Agency for International Development (USAID) was the largest funding agency for humanitarian and development aid worldw

researchyann-lecun--x

Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality

arXiv:2607.03691v1 Announce Type: cross Abstract: Coding agents, autonomous systems that use large language models (LLMs) to resolve software engineering tasks, rely on agentic scaffolding: a middlewa

DrugAgent: Reliable Multi-Agent Integration of Conflicting Biomedical Evidence for Drug-Target Interaction Assessment

arXiv:2408.13378v5 Announce Type: replace Abstract: Workflows in drug-target interaction (DTI) assessment require integrating heterogeneous data from predictive models, curated resources, and observat

DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation

arXiv:2607.04927v1 Announce Type: cross Abstract: World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense super

safetyarxiv-cs-ai

Agents

EEG-SpikeAgent: Agentic Closed-Loop Program Synthesis for Automated EEG Spike Detection

arXiv:2607.04558v1 Announce Type: cross Abstract: Automated detection of interictal epileptiform discharges in scalp electroencephalography (EEG) is clinically important, but recent high-performing de

agentsarxiv-cs-ai

Effectiveness of LLM-based Software Diversity for Reliability Improvement -- an Empirical Study

arXiv:2607.03174v1 Announce Type: cross Abstract: Software diversity has been extensively studied as a means of reducing the risk of common-mode failures. Classic work showed that the central issue is

Embodied Operators and Benchmarking: Toward Reusable and Deployable Embodied Intelligence Systems

arXiv:2607.03283v1 Announce Type: new Abstract: Embodied intelligence systems require not only end-to-end policy models, but also reusable functional modules that transform multimodal observations, ro

Event Detection in Videos: A Framework for the Development of New Methods

arXiv:2607.04372v1 Announce Type: new Abstract: Event detection tasks in videos, the most important aspect of video surveillance, aim to detect events either at the pixel-level, frame-level, or clip-l

EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer

arXiv:2607.05202v1 Announce Type: new Abstract: Agent self-evolution in long-horizon LLM systems is largely procedural: useful experience is not merely stored information, but reusable procedures for

Exploring Context-aware and LLM-driven Locomotion for Immersive Virtual Reality

arXiv:2504.17331v3 Announce Type: replace-cross Abstract: Locomotion plays a crucial role in shaping the user experience within virtual reality environments. In particular, hands-free locomotion offer

Fixed-Confidence Best-Arm Identification for Causal Mediation Analysis

arXiv:2607.04315v1 Announce Type: cross Abstract: This paper studies the problem of identifying the treatment that maximizes the expected natural direct potential outcome (NDPO), which captures the po

Flash-BoN: Instant Drafts for Inference-Time Scaling in Diffusion Models

arXiv:2607.04461v1 Announce Type: new Abstract: Inference-time scaling for text-to-image generation has progressed from simple Best-of-N (BoN) sampling to guided search methods that verify and steer c

Agents

Flow-A11y: Flow-Aware Accessibility Testing

arXiv:2607.03100v1 Announce Type: cross Abstract: Modern web applications increasingly expose accessibility barriers through interaction flows rather than static page snapshots. Keyboard traps, focus

agentsarxiv-cs-ai

From Region Arrival to Instance-Level Grounding in Vision-and-Language Navigation

arXiv:2607.03792v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) agents may satisfy conventional success criteria while still failing to establish reliable object-level grounding

safetyarxiv-cs-cv

From Regulation to Requirements: An Automated Requirement Derivation and Explanation Pipeline

arXiv:2607.04448v1 Announce Type: cross Abstract: Ensuring software compliance with regulations such as the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (EU AI Act) po

Governed Individuation: Cryptographically Decoupling an Agent's Learning from Its Authority

arXiv:2607.04613v1 Announce Type: new Abstract: Autonomous agents are moving from sandboxed text generators to operators of code, data, and physical infrastructure, and they increasingly learn while d

Green for Go, Red for No: Visual Grounding via Semantic Segmentation for VLA Navigation Policies

arXiv:2607.05122v1 Announce Type: new Abstract: Vision-language-action (VLA) models enable robot navigation from natural language and visual goals, but remain susceptible to perceptual distractions an

GuideMe: Multi-Domain Task Guidance and Intervention in Streaming Video

arXiv:2607.02991v1 Announce Type: new Abstract: While multimodal Large Language Models (MLLMs) excel at offline video understanding, an interesting question of how far they are from serving as a real-

HCSU: A Dataset and Benchmark for Fine-Grained Historical Calligraphy Style Understanding

arXiv:2607.04147v1 Announce Type: cross Abstract: Automated fine-grained perception of calligraphy styles--a task vital to cultural heritage preservation--remains a critical challenge for Large Vision

Holo-Captioning: Toward the Text Equivalent of 3D Scenes

arXiv:2607.02908v1 Announce Type: new Abstract: This work introduces holo-captioning, a novel task that strives to seek the text equivalent of 3D scenes. As the initial step, we formulate holo-caption

HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis

arXiv:2603.01121v2 Announce Type: replace Abstract: While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable c

!Imperio, smolVLA: The Implications of Data Poisoning on Open Source Robotics

arXiv:2607.04146v1 Announce Type: cross Abstract: This work establishes that trigger-word data poisoning of vision language action models is practical, while at the same time the open-source robotics

Local Ai

Inpainting U-Net for seamless pedestrian-level wind prediction across urban morphologies

arXiv:2607.02560v1 Announce Type: new Abstract: Pedestrian-level wind prediction is essential for urban design and wind-comfort assessment, but high-fidelity simulations such as LES remain computation

local-aiarxiv-cs-cv

Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification

arXiv:2607.05393v1 Announce Type: cross Abstract: Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable la

iVISION-2DCD: A Long-Term Change Detection Dataset for Large-Scale Outdoor Construction Monitoring

arXiv:2607.03553v1 Announce Type: new Abstract: Automation in construction is essential for reducing costs and human errors in large-scale projects. We approach the construction progress monitoring fr

Knowing When Not to Answer: Lightweight KB-Aligned OOD Detection for Safe RAG

arXiv:2508.02296v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are increasingly deployed in high-stakes domains, where safety depends not only on how a system answers

safetyarxiv-cs-cl

Lacuna Inc. at SemEval-2026 Task 4: Structurally Gated State-Space Models for Disentangling Narrative Similarity

arXiv:2607.03482v1 Announce Type: new Abstract: In this paper, we present the Invariant-Variant Disentangled State-Space Model (IVD-SSM), our submission to SemEval-2026 Task 4 on Narrative Story Simil

safetyarxiv-cs-cl

Last Layer Hamiltonian Monte Carlo

arXiv:2507.08905v2 Announce Type: replace-cross Abstract: We explore the use of Hamiltonian Monte Carlo (HMC) sampling as a probabilistic last layer approach for deep neural networks (DNNs). While HMC

LLM-as-a-Verifier: A General-Purpose Verification Framework

arXiv:2607.05391v1 Announce Type: new Abstract: Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we id

LuxSQA: Ask Me in Luxembourgish with TTS-Augmented Spoken Question Answering

model-releasesarxiv-cs-cl

arXiv:2607.02763v1 Announce Type: new Abstract: Spoken Question Answering (SQA) remains largely focused on high-resource languages and carefully recorded speech, limiting the reach of speech-LLM metho

Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption

arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio

MoP-JEPA: Hard-Assigned Predictor Mixtures for Stochastic JEPA World Models

arXiv:2607.05238v1 Announce Type: new Abstract: JEPA world models predict the next latent state with a single deterministic predictor trained by latent regression. We show that this fails structurally