Search: “evaluation”

BCNet: Bronchus Classification via Structure Guided Representation Learning

model-releasesarxiv-cs-cv

arXiv:2205.06947v3 Announce Type: replace-cross Abstract: CT-based bronchial tree analysis is essential for diagnosing lung and airway diseases, yet automatic bronchus classification remains challengi

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Beyond Sentiment: Structured Information Extraction from Financial News

DGX agent

arXiv:2607.28496v1 Announce Type: new Abstract: Financial sentiment analysis has become a standard component in news-driven stock prediction, yet it reduces rich, multi-dimensional news articles to a

model-releasesarxiv-cs-cl

31 Jul 2026

Applications

BladeYOLO: Wind Turbine Blade Defect Detection with Limited Annotations and Weak-Saliency Awareness

arXiv:2607.28065v1 Announce Type: new Abstract: Wind turbine blade defect detection remains highly challenging in real-world inspection scenarios due to limited on-site data and the subtle visual char

applicationsarxiv-cs-cv

Bridging AI and Energy Forecasting: An Autonomous Workflow with Customized Toolkit

arXiv:2307.07191v3 Announce Type: replace Abstract: Energy forecasting is crucial for the power grid, but fundamentally different from general time series analysis: it highly relies on covariates like

Applications

CACHE-UK: A Stability-Aware Memory Editor for Sequentially Updated Quantized LLMs in Finance

arXiv:2607.28292v1 Announce Type: new Abstract: Large Language Models (LLMs) deployed in dynamic financial environments face a critical challenge: maintaining factual accuracy as market conditions, re

applicationsarxiv-cs-cl

Calibrate Before Reason: Robust Visual Token Reduction against Semantic Drift in VLMs

arXiv:2607.27700v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) suffer from prohibitive inference overhead due to long sequences of visual tokens. However, existing visual token re

Local Ai

Can Vision-Language Models Reason about AI Edits in Images?

arXiv:2607.28464v1 Announce Type: new Abstract: Detection and localization of AI-tampered images are critical for trustworthy AI, yet modern generative models have made such manipulations increasingly

local-aiarxiv-cs-cv

Tutorials

CDAE: Enhancing Perturbation Robustness in Pretrained Language Models with Contrastive Denoising

arXiv:2607.28236v1 Announce Type: cross Abstract: Pre-trained language models have significantly improved sentence representation learning, yet their embedding remain sensitive to semantic preserving

tutorialsarxiv-cs-cl

ClinLens: Towards Long-Horizon Coding Agents for Longitudinal Multimodal Clinical Data Science

model-releasesarxiv-cs-ai

arXiv:2607.26155v1 Announce Type: new Abstract: Clinical data-science agents must transform heterogeneous longitudinal records into auditable analyses, yet existing benchmarks largely isolate medical

Hardware

Complementary Matrix-Gated QKAN Fast-Weight Programmers for Quantum Dynamics Forecasting

arXiv:2607.27945v1 Announce Type: cross Abstract: Sequence models must decide what to write into memory and what to retain. In quantum and quantum-inspired sequence learning, nonlinear recurrent updat

hardwarearxiv-cs-lg

Compliance2LoRA: On-Demand Safety Alignment on Arbitrary Policy Subsets via Hypernetwork-Generated LoRA Adapters

arXiv:2607.27594v1 Announce Type: new Abstract: Post-training alignment in large reasoning models (LRMs) has significantly improved their adaptability to diverse safety compliance settings. However, a

safetyarxiv-cs-lg

Compression-Based Behavioral Similarity for Open-World Sybil Discovery on Ethereum

arXiv:2607.27370v1 Announce Type: new Abstract: Sybil attackers are Blockchain actors that adopt the characteristics of regular users to exploit airdrops or influence governance. Current methods of Sy

Concurrent training methods for Kolmogorov-Arnold networks: Disjoint datasets and FPGA implementation

arXiv:2512.18921v5 Announce Type: replace Abstract: The present paper introduces concurrency-driven enhancements to the training algorithm for the Kolmogorov-Arnold networks (KANs) that is based on th

Continuous-time reinforcement learning for optimal switching over multiple regimes

arXiv:2512.04697v3 Announce Type: replace-cross Abstract: This paper studies the continuous-time reinforcement learning (RL) for optimal switching problems across multiple regimes. We consider a type

Contrastive Reinforced Policy Optimization via Privileged Self-Distillation

arXiv:2607.28026v1 Announce Type: new Abstract: Recent advances in post-training Large Language Models (LLMs) increasingly rely on Reinforcement Learning with Verifiable Rewards (RLVR) or On-Policy Se

safetyarxiv-cs-lg

CoRE-UIR: Prior-guided common and residual experts for efficient all-in-one remote sensing image restoration

model-releasesarxiv-cs-cv

arXiv:2607.27898v1 Announce Type: new Abstract: Remote sensing images acquired by unmanned aerial vehicles (UAVs) and satellites are often degraded by adverse weather, illumination variation, and imag

Cross-Embodiment Transfer via Behavior-Aligned Representations

model-releasesarxiv-cs-cv

arXiv:2607.27549v1 Announce Type: cross Abstract: Recent progress in large-scale imitation learning for robot manipulation has been driven by leveraging datasets across a wide range of robot embodimen

DeepSeek V4 Flash 0731 in Hermes Agent and one prompt, took 32 minutes and cost 0.07$, this model is so cheap to the point where 2 dollars c…

model-releasesnous-research--x

**DeepSeek V4 Flash 0731 Performance Test** On July 31 2026, a single prompt executed via the Hermes Agent on DeepSeek V4 Flash 0731 completed in 32 minutes and incurred an estimated cost of 0.07 USD.

Digital Harf: A Clinically Integrated Multimodal AI System for Pervasive Arabic Speech and Language Therapy

arXiv:2607.27212v1 Announce Type: cross Abstract: Children with Autism Spectrum Disorder in Arabic-speaking countries face compounded barriers to effective speech and language therapy: a shortage of q

safetyarxiv-cs-cl

Divergence Decoding: Training-Free Capability Fusion

arXiv:2607.27248v1 Announce Type: cross Abstract: While large language models excel in reasoning, these generalists often lack knowledge for specialized scientific domains. Conversely, domain models~(

Driving up Inference Energy on SNNs: Per-Sample and Universal Sponge Attacks

arXiv:2607.27990v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) communicate through sparse binary spike events rather than dense activations, enabling energy-efficient inference on ne

Agents

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations

arXiv:2607.26201v1 Announce Type: cross Abstract: Security operations centers rely on anomaly detection systems to flag suspicious events. Feature-level explanations for anomaly detectors offer limite

agentsarxiv-cs-ai

Echoverse: Deep, Evolving Environments for Training Computer-Use Agents at Scale

arXiv:2607.28074v1 Announce Type: cross Abstract: Computer-use agents learn from what their actions change, so training one needs applications it can act on, break and reset. The applications that mat

EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents

model-releasesarxiv-cs-cl

arXiv:2607.28229v1 Announce Type: new Abstract: The web is increasingly accessed by AI agents rather than humans. Every agent needs knowledge, especially in the life-sciences, where agentic pipelines

EmoFeedback^2: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback

arXiv:2511.19982v3 Announce Type: replace Abstract: Continuous emotional image content generation (C-EICG) is emerging rapidly due to its ability to produce images aligned with both user descriptions

safetyarxiv-cs-cv

Energy-Driven Adaptive Visual Token Pruning for Efficient Vision-Language Models

arXiv:2603.05950v2 Announce Type: replace Abstract: Visual token reduction is critical for accelerating Vision-Language Models (VLMs), since visual inputs are represented as token sequences that intro

Epistemic diversity across language models mitigates knowledge collapse

arXiv:2512.15011v3 Announce Type: replace Abstract: Artificial intelligence (AI) increasingly generates the very content used to train future AI systems. This feedback loop can degrade model quality,

Agents

Even More Deception: Objective Misalignment in Mixed-Motive LLM Multi-Agent Systems

arXiv:2607.26120v1 Announce Type: new Abstract: Large Language Models (LLMs)-powered multi-agent systems are increasingly deployed in mixed-motive environments, where agents operate under asymmetric i

agentsarxiv-cs-ai

Exact Action Values Are Not Enough: Rollout-Verified Reinforcement Fine-Tuning of a Reasoning Model for Multi-Zone VAV Control

arXiv:2607.27914v1 Announce Type: new Abstract: Multi-zone variable-air-volume control must balance thermal comfort, indoor air quality, and electricity use across several continuous actuators. Model

Face and Voice Cross-modal Association with Learning Convex Feature Embedding

arXiv:2607.28129v1 Announce Type: new Abstract: Face-and-voice association learning is one of the most challenging tasks in deep learning. In this paper, we propose a simple but powerful cross-modal f

FADEx: Feature Attribution and Distortion-based Explanation of Dimensionality Reduction

arXiv:2607.27463v1 Announce Type: new Abstract: Dimensionality Reduction (DR) is a fundamental tool for high-dimensional data exploration, reducing the complexity of latent spaces of machine learning

Failure Detection for Surgical Robot Imitation Policies via Flow-Matching World Modeling

arXiv:2607.27511v1 Announce Type: new Abstract: Imitation learning has shown increasing promise for autonomous robotic surgery, yet safe deployment remains challenging due to the safety-critical natur

safetyarxiv-cs-ro

Agents

FaithEyes: Towards Faithful Tool Use via Multi-Agent Process-Image Verification

arXiv:2607.28225v1 Announce Type: new Abstract: Agentic vision-language models (VLMs), which interleave textual reasoning with explicit tool calls such as cropping and code-based image manipulation, h

agentsarxiv-cs-cv

Hardware

FARI: Robust One-Step Inversion for Watermarking in Diffusion Models

arXiv:2607.26723v1 Announce Type: cross Abstract: Inversion-based watermarking is a promising approach to authenticate diffusion-generated images, yet practical use is bottlenecked by inversion that i

hardwarearxiv-cs-ai

Hardware

FinCacheServe: Dependency-Consistent Answer Reuse for Cost-Efficient RAG Serving over Mutable Enterprise Documents

arXiv:2607.26076v1 Announce Type: cross Abstract: Retrieval-augmented generation services over mutable enterprise documents repeatedly execute semantically equivalent analysis requests. Answer reuse c

hardwarearxiv-cs-ai

Tutorials

Finding Change in Satellite Archives from Text: How to Combine Before-and-After Images Efficiently

arXiv:2607.28571v1 Announce Type: new Abstract: Operational Earth observation increasingly calls for answering queries such as ``find the image pairs where a new building appeared.'' This means search

tutorialsarxiv-cs-cv

Tutorials

FootprintNet: State-Transition-Guided Dynamic Footprint Learning for Multi-temporal Remote Sensing Change Detection

arXiv:2607.27969v1 Announce Type: new Abstract: Despite substantial progress in remote sensing multi-temporal change detection (MTCD), most existing MTCD methods still represent the dynamic process at

tutorialsarxiv-cs-cv

Foundation-Model Earth Representations Enable Regional-Scale Forest Aboveground Biomass Monitoring Across the Northeastern United States

arXiv:2607.27217v1 Announce Type: cross Abstract: Forest aboveground biomass (AGB) is a critical indicator of ecosystem productivity and terrestrial carbon storage, yet regional carbon monitoring rema

safetyarxiv-cs-lg

From Expert Reduction to Behavioral Divergence: Tracing Numerical State through Sparse MoE Inference

arXiv:2607.28097v1 Announce Type: new Abstract: Mathematically equivalent expert-reduction orders can produce observably different sparse-MoE executions. We isolate this effect in native DeepSeek-V4-F

From Single- to Cross-Document: Benchmarking Multi-Granularity Event Analysis of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.27654v1 Announce Type: new Abstract: Event analysis is an essential and fundamental direction of information extraction, involving various event-centric tasks at different granularity of do

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

model-releasesarxiv-cs-cl

arXiv:2607.28568v1 Announce Type: new Abstract: Recursive self-improvement (RSI) requires AI systems that improve the process of building AI (i.e., AI4AI); machine learning engineering (MLE) offers a

Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets

arXiv:2607.28537v1 Announce Type: cross Abstract: Metallic magnets exhibit complex spin dynamics governed by electronically generated interactions. Predictive simulations of such dynamics typically re

GuidedRAG: Semantic Steering of Retrieval-Augmented Generation

arXiv:2607.26071v1 Announce Type: cross Abstract: In this work, we propose GuidedRAG, a novel extension to traditional Retrieval-Augmented Generation (RAG) that introduces a dedicated selection stage

safetyarxiv-cs-ai

GuideSkill: Evolving Executable LLM Agent Skills for Guideline-Grounded Clinical Reasoning

model-releasesarxiv-cs-ai

arXiv:2607.26160v1 Announce Type: new Abstract: Clinical practice guidelines (CPGs) encode diagnostic criteria, but LLM systems typically retrieve guideline text or absorb it through training rather t

Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfer

arXiv:2607.28394v1 Announce Type: new Abstract: Hand-object interaction (HOI) modeling remains challenging because it requires joint reasoning about hand articulation, object geometry, contact, semant

Harness-G: A Graph-Structured Harness for Search Agents

arXiv:2607.27652v1 Announce Type: new Abstract: Reinforcement learning (RL) search agents commonly model retrieval as free-form natural-language query generation and optimize multi-turn interactions u

safetyarxiv-cs-cl

Applications

HealthCAT: An Interpretable Encoder-only Transformer Framework for Health Indicator Prediction and Temporal Interpretation of Wearable Sensor Data

arXiv:2607.27635v1 Announce Type: cross Abstract: Wearable sensors continuously capture fine-grained multivariate time-series data, providing opportunities to model behavioural patterns associated wit

applicationsarxiv-cs-lg

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs

arXiv:2607.27379v1 Announce Type: new Abstract: High-quality, diverse data are vital for large language models (LLMs) but remain scarce and costly. Data synthesis is a viable alternative and succeeds

safetyarxiv-cs-cl