Search: “framework”

Benchmarking Open-Weight Foundation Models for Global AI Technical Governance

arXiv:2606.26099v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in artificial intelligence (AI) governance analysis across national and international organisat

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BetXplain: An Explanation-Annotated Dataset for Detecting Manipulative Betting Advertisements on Social Media

DGX agent

arXiv:2606.27274v1 Announce Type: new Abstract: The promotion of betting applications on social media platforms has increased significantly in recent years. Many of these advertisements use persuasive

researcharxiv-cs-lg

26 Jun 2026

Beyond Logical Forms: LLM-Extracted Patterns for Fallacy Classification

arXiv:2606.26698v1 Announce Type: cross Abstract: In today's fast-paced information era, logical fallacies, defined as defective patterns of reasoning, inevitably contribute to the growth of informati

BOWConnect: Parallel Bayesian Optimization over Windows with Learned Local Cost Maps for Sample-Efficient Kinodynamic Motion Planning

model-releasesarxiv-cs-ro

arXiv:2606.27292v1 Announce Type: new Abstract: This paper presents BOWConnect, a bidirectional parallel kinodynamic motion planner that addresses three fundamental limitations of existing sampling-ba

Capacity-Controlled Multi-View Stylization of 3D Gaussian Splatting

arXiv:2606.26754v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) provides an efficient and explicit representation for novel view synthesis, enforcing stylistic coherence across view

researcharxiv-cs-cv

Compiler-Driven Approximation Tuning for Hyperdimensional Computing

arXiv:2606.26547v1 Announce Type: cross Abstract: As Moore's law reaches its physical and economic limits, domain-specific approaches are increasingly employed to accelerate machine learning workloads

researcharxiv-cs-cl

Confidence-Aware Tool Orchestration for Robust Video Understanding

arXiv:2606.26904v1 Announce Type: cross Abstract: Video reasoning language models implicitly assume that every input frame is equally reliable. This leads to what we term the Blind Trust Problem: unde

ConflictScore: Identifying and Measuring How Language Models Handle Conflicting Evidence

arXiv:2606.26437v1 Announce Type: cross Abstract: Existing metrics for factuality and faithfulness evaluate whether an answer is supported or contradicted by its grounding documents, but they fail to

Agents

Content-Based Smart E-Mail Dispatcher Using Large Language Models

arXiv:2606.26593v1 Announce Type: new Abstract: Email communication has become an integral part of personal and professional life, but handling its vast volume is still a significant issue for large o

agentsarxiv-cs-ai

CoStream: Composing Simple Behaviors for Generalizable Complex Manipulation

arXiv:2606.26423v1 Announce Type: cross Abstract: Long-horizon, contact-rich complex manipulation tasks, such as seating a GPU into a PCIe slot, demand both millimeter high precision and out-of-the-bo

Local Ai

DanceOPD: On-Policy Generative Field Distillation

arXiv:2606.27377v1 Announce Type: cross Abstract: Modern image generation demands a single model that unifies diverse capabilities, including text-to-image (T2I), local editing, and global editing. Ho

local-aiarxiv-cs-cl

Dataset Usage Inference without Shadow Models or Held-out Data

arXiv:2606.26257v1 Announce Type: new Abstract: How much of my data was used to train a machine learning model? Dataset Usage Inference (DUI) aims to answer this by estimating what fraction of a datas

Decision-Aligned Evaluation of Uncertainty Quantification

arXiv:2606.26990v1 Announce Type: cross Abstract: Uncertainty estimates in machine learning are typically evaluated using generic metrics such as the negative log-likelihood and expected calibration e

Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search

arXiv:2606.27291v1 Announce Type: new Abstract: Job-search platforms rely on low-bandwidth query interfaces that often fail to capture the high-dimensional complexity of candidate profiles. We present

safetyarxiv-cs-lg

Detecting and Controlling Sycophancy with Cascading Linear Features

arXiv:2606.26155v1 Announce Type: new Abstract: Interpreting and controlling model behaviors through activation steering methods requires many pairs of contrastive samples that clearly exhibit desired

DMuon: Efficient Distributed Muon Training with Near-Adam Overhead

arXiv:2606.27153v1 Announce Type: cross Abstract: Matrix-orthogonalization-based optimizers, exemplified by Muon, have demonstrated strong convergence behavior across a wide range of modern deep learn

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents

arXiv:2606.26122v1 Announce Type: new Abstract: Recent methods train search agents via reinforcement learning from (question, answer, evidence) tuples without requiring expert trajectories. The tuples

safetyarxiv-cs-cv

Does AI Reviewer See the Full Picture? Attacking and Defending Multimodal Peer Review

model-releasesarxiv-cs-cl

arXiv:2606.12716v2 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) and Multimodal LLMs (MLLMs) into scientific peer-review workflows introduces novel and significant r

Dream machine -- the next creative economy

arXiv:2606.26114v1 Announce Type: cross Abstract: We examine the structural transformation of creative industries under generative artificial intelligence, drawing on 374 primary sources spanning poli

DroidBreaker: Practical and Functional Problem-Space Attacks on Machine-Learning Android Malware Detectors

arXiv:2606.26707v1 Announce Type: cross Abstract: Adversarial APKs are Android applications modified in the problem space to evade machine-learning malware detectors. In this work, we first show that,

Dual-Prior Guided Null-Space Learning with Mixture-of-Splines for Arbitrary Medical Slice Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2606.26716v1 Announce Type: cross Abstract: Arbitrary slice super-resolution reconstructs isotropic volumes from anisotropic clinical acquisitions by synthesizing intermediate slices at arbitrar

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM

arXiv:2606.26120v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) offer a promising alternative to autoregressive models, excelling in text generation tasks due to their bidirect

researcharxiv-cs-cl

Efficient foundation decoders for fault-tolerant quantum computing

arXiv:2606.27119v1 Announce Type: cross Abstract: Foundation decoders, a class of high-capacity neural decoders, are leading candidates for fault-tolerant quantum computing, with accurate and efficien

EMA-FS: Accelerating GBDT Training via Gain-Informed Feature Screening

model-releasesarxiv-cs-lg

arXiv:2606.26337v1 Announce Type: new Abstract: Gradient Boosted Decision Trees (GBDT), exemplified by LightGBM, spend a dominant fraction of training time -- typically 65-70% -- constructing per-feat

Agents

Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning

arXiv:2606.27330v1 Announce Type: cross Abstract: Multimodal web agents can assist humans in operating repetitive GUI tasks, where effective task planning is essential for decomposing complex tasks in

agentsarxiv-cs-ai

EO-WM: A Physically Informed World Model for Probabilistic Earth Observation Forecasting

arXiv:2606.27277v1 Announce Type: new Abstract: Earth Observation (EO) forecasting aims to predict future Earth surface dynamics from satellite observations under changing meteorological conditions. I

Escaping Iterative Parameter-Space Noise: Differentially Private Learning with a Hypernetwork

model-releasesarxiv-cs-lg

arXiv:2606.26772v1 Announce Type: new Abstract: Differentially private (DP) training of neural networks is often hindered by the large amount of noise required by gradient-based methods such as DP-SGD

Estimating Orbital Parameters of Direct Imaging Exoplanet Using Neural Network

model-releasesarxiv-cs-lg

arXiv:2510.17459v3 Announce Type: replace-cross Abstract: In this work, we propose a flow-matching Markov chain Monte Carlo (FM-MCMC) algorithm for estimating the orbital parameters of exoplanetary sy

Evaluation Pitfalls and Challenges in Multimedia Event Extraction

arXiv:2606.26775v1 Announce Type: new Abstract: Multimedia event extraction aims to jointly identify events and their arguments across multiple modalities, such as text and images, to support more com

applicationsarxiv-cs-cl

EVOM: Agentic Meta-Evolution of Actor-Critic Architectures for Reinforcement Learning

arXiv:2606.26327v1 Announce Type: cross Abstract: In actor-critic reinforcement learning, network architectures are typically manually designed. Automating this design is challenging because each cand

Agents

EvoOptiGraph: Weakness-Driven Coevolution via Graph-Based Structural Generation for Optimization Modeling

arXiv:2606.26578v1 Announce Type: new Abstract: Automating optimization modeling from natural language with large language models (LLMs) faces two key challenges. First, training corpora lack structur

agentsarxiv-cs-ai

FC-Vision: Real-Time Visibility-Aware Replanning for Occlusion-Free Aerial Target Structure Scanning in Unknown Environments

model-releasesarxiv-cs-ro

arXiv:2602.13720v2 Announce Type: replace Abstract: Autonomous aerial scanning of target structures is crucial for practical applications, requiring online adaptation to unknown obstacles during fligh

Fortress and Gatekeeper: Theorizing Transitive Trust in Third-Party Cybersecurity Risk Governance

arXiv:2606.26866v1 Announce Type: cross Abstract: Third-party vendors, such as analytics platforms, cloud services, identity providers, and software suppliers, are increasingly embedded in digital ser

From Clicks to Intent: Cross-Platform Session Embeddings with LLM-Distilled Taxonomy for Financial Services Recommendations

arXiv:2606.26277v1 Announce Type: cross Abstract: Sequential user behavior modeling is widely adopted in industrial recommender systems; however, significant gaps remain in financial services, where p

applicationsarxiv-cs-ai

Generative Models on Analog Hardware with Dynamics

arXiv:2606.27294v1 Announce Type: cross Abstract: Analog hardware platforms such as coupled oscillators and Analog Ising Machines naturally solve differential equations at a fraction of the energy cos

Generative Retrieval via Diffusion Transformer with Metric-Ordered Sequence Training and Hybrid-Policy Preference Optimization

arXiv:2606.26899v1 Announce Type: new Abstract: Embedding-based retrieval ranks items by their similarity to a query in a shared vector space and usually aims to return the highest-scoring items. In m

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models

arXiv:2506.15681v4 Announce Type: replace Abstract: Recent advancements in vision-language models (VLMs) have leveraged large language models (LLMs) to achieve performance on par with closed-source sy

applicationsarxiv-cs-cl

Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning

arXiv:2606.26973v1 Announce Type: new Abstract: Open-set semi-supervised learning aims to leverage unlabeled data that may contain out-of-distribution outliers while maintaining performance on in-dist

researcharxiv-cs-cv

Geometry-Aware Superpixel Graph Transformer with Metadata for Skin Lesion Classification

arXiv:2606.20390v2 Announce Type: replace Abstract: Automated skin cancer classification from dermoscopic images remains challenging due to heterogeneous lesion structure, strong intra-class variabili

researcharxiv-cs-cv

HarmVideoBench: Benchmarking Harmful Video Understanding in Large Multimodal Models

model-releasesarxiv-cs-cl

arXiv:2606.27187v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have recently shown immense potential in automated content moderation, sparking growing interest in developing ha

HauntAttack: When Attack Follows Reasoning as a Shadow

arXiv:2506.07031v5 Announce Type: replace-cross Abstract: Emerging Large Reasoning Models (LRMs) consistently excel in mathematical and reasoning tasks, showcasing remarkable capabilities. However, th

Heavy-Ball Q-Learning with Residual Weighting Correction

arXiv:2606.27112v1 Announce Type: cross Abstract: This paper proposes a corrected heavy-ball Q-learning method for reinforcement learning (RL) and establishes its convergence. It also identifies condi

High-Probability PL-SGD with Markovian Noise: Optimal Mixing and Tail Dependence

arXiv:2606.26316v1 Announce Type: new Abstract: We study first-order methods for smooth objectives satisfying the Polyak-L{}ojasiewicz (PL) condition when gradient samples are generated by an exogenou

safetyarxiv-cs-lg

History-Conditioned Spatio-Temporal Visual Token Pruning for Efficient Vision-Language Navigation

arXiv:2603.06480v2 Announce Type: replace Abstract: Vision-Language Navigation (VLN) enables robots to follow natural-language instructions in visually grounded environments, serving as a key capabili

applicationsarxiv-cs-ro

Identifying the Unknown: Prompt-Free Open Vocabulary Anomaly Recognition for Robot-Object Interaction

arXiv:2606.26829v1 Announce Type: new Abstract: Robots operating in real-world environments must in general be able to recognize previously unseen objects. As robotic systems move toward open-world au

applicationsarxiv-cs-cv

Improving General Role-Playing Agents via Psychology-Grounded Reasoning and Role-Aware Policy Optimization

arXiv:2606.27025v1 Announce Type: new Abstract: Building general-purpose role-playing agents that faithfully portray any character from a natural-language profile remains challenging. The dominant par

safetyarxiv-cs-cl

Improving Vision-Language-Action Model Fine-Tuning with Structured Stage and Keyframe Supervision

arXiv:2606.26801v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for generalizable robotic manipulation. During fine-tuning, however, action supervisio

safetyarxiv-cs-cv

Information-Aware KV Cache Compression for Long Reasoning

arXiv:2606.26875v1 Announce Type: cross Abstract: Reasoning capability has advanced rapidly in large language models (LLMs), leading to an increasing size of key-value (KV) cache in both prefilling an