Search: “benchmark”

Vision Inference Former: Sustaining Visual Consistency in Multimodal Large Language Models

arXiv:2605.18160v1 Announce Type: cross Abstract: In recent years, multimodal large language models (MLLMs) have achieved remarkable progress, primarily attributed to effective paradigms for integrati

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Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation

DGX agent

arXiv:2605.18740v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) still struggle with fine-grained visual understanding, where answers often depend on small but decisive evide

local-aiarxiv-cs-ai

19 May 2026

VVitCutLER: Towards Unsupervised Object Detection and Segmentation in Videos

arXiv:2605.17584v1 Announce Type: new Abstract: Unsupervised pixel-level video understanding remains challenging in real-world scenarios, where motion blur, occlusion, and fast object dynamics often c

applicationsarxiv-cs-cv

Weighted Reverse Convolution for Feature Upsampling

arXiv:2605.17472v1 Announce Type: new Abstract: Pre-trained vision foundation models (VFMs) provide strong semantic representations, yet their patch-level features are inherently coarse, limiting thei

researcharxiv-cs-cv

What Matters for Grocery Product Retrieval with Open Source Vision Language Models

arXiv:2605.18029v1 Announce Type: new Abstract: Multimodal product retrieval (MPR) underpins checkout-free retail and automated inventory systems, yet it demands fine-grained SKU discrimination that s

researcharxiv-cs-cv

Local Ai

When Molecular Similarity Works: Property Cliffs Reveal Hidden Errors

arXiv:2605.17265v1 Announce Type: new Abstract: Accurate prediction of molecular properties underpins drug discovery and material design, yet even state-of-the-art models remain vulnerable to localize

local-aiarxiv-cs-lg

When Personalization Legitimizes Risks: Uncovering Safety Vulnerabilities in Personalized Dialogue Agents

arXiv:2601.17887v2 Announce Type: replace Abstract: Long-term memory enables large language model (LLM) agents to support personalized and sustained interactions. However, most work on personalized ag

When Vision Speaks for Sound

arXiv:2605.16403v1 Announce Type: new Abstract: Despite rapid progress in video-capable MLLMs, we find that their apparent audio understanding in videos is often vision-driven: models rely on visual c

safetyarxiv-cs-cv

Why Modeling Human Haptic Material Perception with AI Is Difficult

arXiv:2605.16602v1 Announce Type: cross Abstract: Touch plays a central role in how humans perceive and recognize materials through physical contact. Despite decades of research, the mechanisms by whi

WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens

arXiv:2605.18115v1 Announce Type: new Abstract: Building a unified visual tokenizer is essential for bridging the gap between visual understanding and generation. Yet existing approaches struggle with

WOW-Seg: A Word-free Open World Segmentation Model

arXiv:2605.16903v1 Announce Type: new Abstract: Open world image segmentation aims to achieve precise segmentation and semantic understanding of targets within images by addressing the infinitely open

XCTFormer: Leveraging Cross-Channel and Cross-Time Dependencies for Enhanced Time-Series Analysis

arXiv:2605.18534v1 Announce Type: new Abstract: Multivariate time-series analysis involves extracting informative representations from sequences of multiple interdependent variables, supporting tasks

applicationsarxiv-cs-lg

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations

arXiv:2511.06516v3 Announce Type: replace Abstract: Many LLM applications require only narrow capabilities, yet standard post-training quantization (PTQ) methods allocate precision without considering

researcharxiv-cs-cl

3DEditSafe: Defending 3D Editing Pipelines from Unsafe Generation

arXiv:2605.15398v1 Announce Type: cross Abstract: Recent advances in 3D generative editing, particularly pipelines based on 3D Gaussian Splatting (3DGS), have achieved high-fidelity, multi-view-consis

A Model Can Help Itself: Reward-Free Self-Training for LLM Reasoning

arXiv:2510.18814v3 Announce Type: replace-cross Abstract: Can language models improve their reasoning performance without external rewards, using only their own sampled responses for training? We show

A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement

arXiv:2507.14200v2 Announce Type: replace-cross Abstract: Existing multi-LLM collaboration systems often encounter scalability challenges when integrating new LLMs and tasks, leading to suboptimal per

A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature

arXiv:2605.16208v1 Announce Type: cross Abstract: Flexible continuous-time survival modeling is critical for capturing complex time-varying hazard dynamics in high-dimensional data; however, training

applicationsarxiv-cs-lg

A Statistical Analysis for Per-Instance Evaluation of Stochastic Optimizers: Avoiding Unreliable Conclusions

arXiv:2503.16589v2 Announce Type: replace Abstract: A key trait of stochastic optimizers is that multiple runs of the same optimizer in attempting to solve the same problem can produce different resul

researcharxiv-cs-lg

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making

arXiv:2605.16054v1 Announce Type: cross Abstract: Recent work has framed decision-making as a sequence modeling problem using generative models such as diffusion models. Although promising, these appr

safetyarxiv-cs-ai

Adapting Foundation Vision-Language Models to Medical Diagnosis via Query-Driven Expert Bridging

arXiv:2505.21698v3 Announce Type: replace Abstract: Vision-language foundation models achieve promising performance in natural image classification, yet their direct application to medical imaging is

ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking

arXiv:2510.13842v2 Announce Type: replace-cross Abstract: Knowledge poisoning poses a critical threat to Retrieval-Augmented Generation (RAG) systems by injecting adversarial content into knowledge ba

applicationsarxiv-cs-ai

Agents

Agent4POI: Agentic Context-Conditioned Affordance Reasoning for Multimodal Point-of-Interest Recommendation

arXiv:2605.15203v1 Announce Type: cross Abstract: We introduce Agent4POI, the first POI recommendation framework that generates context-conditioned multimodal representations at recommendation time, r

agentsarxiv-cs-ai

Local Ai

AgentStop: Terminating Local AI Agents Early to Save Energy in Consumer Devices

arXiv:2605.15206v1 Announce Type: cross Abstract: Autonomous agents powered by large language models (LLMs) are increasingly used to automate complex, multi-step tasks such as coding or web-based ques

local-aiarxiv-cs-ai

ALSO: Adversarial Online Strategy Optimization for Social Agents

arXiv:2605.15768v1 Announce Type: new Abstract: Social simulation provides a compelling testbed for studying social intelligence, where agents interact through multi-turn dialogues under evolving cont

AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training

arXiv:2605.15793v1 Announce Type: new Abstract: Pre-training neural operators on diverse partial differential equation (PDE) datasets has emerged as a promising direction for building general-purpose

researcharxiv-cs-lg

ART: Articulated Reconstruction Transformer

arXiv:2512.14671v3 Announce Type: replace Abstract: We introduce ART, Articulated Reconstruction Transformer -- a category-agnostic, feed-forward model that reconstructs complete 3D articulated object

researcharxiv-cs-cv

Attention Dispersion in Dynamic Graph Transformers: Diagnosis and a Transferable Fix

arXiv:2605.16112v1 Announce Type: cross Abstract: Transformer-based architectures have become the dominant paradigm for Continuous-Time Dynamic Graph (CTDG) learning, yet their performance remains lim

Autoguided Online Data Curation for Diffusion Model Training

arXiv:2509.15267v2 Announce Type: replace-cross Abstract: The costs of generative model compute rekindled promises and hopes for efficient data curation. In this work, we investigate whether recently

Beyond Objective-Based Improvement: Stationarity-Aware Expected Improvement for Bayesian Optimization

arXiv:2601.21357v2 Announce Type: replace Abstract: Bayesian Optimization (BO) is a principled framework for optimizing expensive black-box functions, with Expected Improvement (EI) among its most wid

safetyarxiv-cs-lg

Beyond the Query: 5 Scenarios Laying the Foundation for the Agentic Era

model-releasesgoogle-cloud-ai

Accessing enterprise data is shifting from static reports to dynamic use by autonomous systems. To keep up, organizations must route fragmented data from SaaS, IoT, and legacy sources into secure, sca

Bidirectional Fusion Guided by Cardiac Patterns for Semi-Supervised ECG Segmentation

arXiv:2605.15722v1 Announce Type: cross Abstract: Accurate delineation of electrocardiogram (ECG), the segmentation of meaningful waveform features, is crucial for cardiovascular diagnostics. However,

BiomedAP: A Vision-Informed Dual-Anchor Framework with Gated Cross-Modal Fusion for Robust Medical Vision-Language Adaptation

arXiv:2605.15736v1 Announce Type: cross Abstract: Biomedical Vision--Language Models (VLMs) have shown remarkable promise in few-shot medical diagnosis but face a critical bottleneck: extit{fragility

Agents

BootstrapAgent: Distilling Repository Setup into Reusable Agent Knowledge

arXiv:2605.15815v1 Announce Type: cross Abstract: Code agents increasingly help developers work with unfamiliar repositories, but every such task depends on a costly prerequisite: bootstrapping the re

agentsarxiv-cs-cl

Breakeven complexity: A new perspective on neural partial differential equation solvers

arXiv:2605.15399v1 Announce Type: cross Abstract: Neural surrogate solvers of partial differential equations (PDEs) promise dramatic speedups over numerical methods, especially in scenarios requiring

CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning

arXiv:2605.15513v1 Announce Type: new Abstract: Parallel reasoning, where a generator samples many candidate solutions and an aggregator selects the best, is one of the most effective forms of test-ti

Local Ai

ChangeFlow -- Latent Rectified Flow for Change Detection in Remote Sensing

arXiv:2605.15375v1 Announce Type: cross Abstract: Remote sensing change detection (RSCD) aims to localise changes between two images of the same geographic region. In practice, change masks often foll

local-aiarxiv-cs-ai

CLARE: Continual Learning for Vision-Language-Action Models via Autonomous Adapter Routing and Expansion

model-releasesarxiv-cs-lg

arXiv:2601.09512v2 Announce Type: replace-cross Abstract: To teach robots complex manipulation tasks, a common approach is to fine-tune a pre-trained vision-language-action model (VLA) on task-specifi

ColPackAgent: Agent-Skill-Guided Hard-Particle Monte Carlo Workflows for Colloidal Packing

arXiv:2605.15625v1 Announce Type: new Abstract: We introduce ColPackAgent, an agent framework that autonomously runs Monte Carlo simulations of colloidal packing through a Model Context Protocol (MCP)

Confirming Correct, Missing the Rest: LLM Tutoring Agents Struggle Where Feedback Matters Most

arXiv:2605.16207v1 Announce Type: new Abstract: Effective tutoring requires distinguishing optimal, valid but suboptimal, and incorrect student solutions, a distinction central to intelligent tutoring

Context-aware Entity-Relation Extraction for Threat Intelligence Knowledge Graphs

model-releasesarxiv-cs-lg

arXiv:2605.15904v1 Announce Type: new Abstract: Cybersecurity Knowledge Graphs (CKGs) unify diverse Cyber Threat Intelligence (CTI) sources into structured, queryable formats, offering scalable soluti

Agents

Context Pruning for Coding Agents via Multi-Rubric Latent Reasoning

arXiv:2605.15315v1 Announce Type: new Abstract: LLM-powered coding agents spend the majority of their token budget reading repository files, yet much of the retrieved code is irrelevant to the task at

agentsarxiv-cs-ai

Continual Learning of Domain-Invariant Representations

model-releasesarxiv-cs-lg

arXiv:2605.15775v1 Announce Type: new Abstract: Continual learning (CL) aims to train models sequentially over multiple domains without forgetting previously learned knowledge. However, existing CL me

Controllable Molecular Generative Foundation Models

arXiv:2605.15354v1 Announce Type: new Abstract: Despite the success of foundation models in language and vision, molecular graph generation still lacks a unified framework for heterogeneous design tas

safetyarxiv-cs-lg

COPRA: Conditional Parameter Adaptation with Reinforcement Learning for Video Anomaly Detection

arXiv:2605.15325v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong performance in video anomaly detection (VAD) while providing interpretable predictions. However, existin

CTF4Nuclear: Common Task Framework for Nuclear Fission and Fusion Models

arXiv:2605.15549v1 Announce Type: cross Abstract: The demand for clean energy is ever increasing, with new nuclear technologies presenting a complementary solution to renewable energies. However, desi

safetyarxiv-cs-ai

Tutorials

Curriculum Learning of Physics-Informed Neural Networks based on Spatial Correlation

arXiv:2605.15254v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) combine deep learning with physical constraints for solving partial differential equations (PDEs), and are wide

tutorialsarxiv-cs-lg

Decentralized LoRA augmented transformer with multi-scale feature learning for secured eye diagnosis

arXiv:2505.06982v3 Announce Type: replace Abstract: Accurate and privacy-preserving diagnosis of ophthalmic diseases remains a critical challenge in medical imaging, particularly given the limitations

DecomPose: Disentangling Cross-Category Optimization Contention for Category-Level 6D Object Pose Estimation

arXiv:2605.15728v1 Announce Type: cross Abstract: Category-level 6D object pose estimation is typically formulated as a multi-category joint learning problem with fully shared model parameters. Howeve