Search: “benchmark”

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

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

DGX agent

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

18 May 2026

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

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

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

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

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

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

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

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

Decomposed Vision-Language Alignment for Fine-Grained Open-Vocabulary Segmentation

arXiv:2605.15942v1 Announce Type: cross Abstract: Open-vocabulary segmentation models often struggle to generalize to unseen combinations of object categories and attributes, because fine-grained desc

Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training

arXiv:2602.00747v2 Announce Type: replace-cross Abstract: Determining an effective data mixture is a key factor in Large Language Model (LLM) pre-training, where models must balance general competence

Tutorials

Deep Learning Alternatives of the Kolmogorov Superposition Theorem

arXiv:2410.01990v3 Announce Type: replace Abstract: This paper explores alternative formulations of the Kolmogorov Superposition Theorem (KST) as a foundation for neural network design. The original K

tutorialsarxiv-cs-lg

DeepSlide: From Artifacts to Presentation Delivery

arXiv:2605.15202v1 Announce Type: new Abstract: Presentations are a primary medium for scholarly communication, yet most AI slide generators optimize the artifact (a visually plausible deck) while und

DeltaPrompts: Escaping the Zero-Delta Trap in Multimodal Distillation

arXiv:2605.15532v1 Announce Type: cross Abstract: Distillation enables compact Vision-Language Models (VLMs) to obtain strong reasoning capabilities, yet the prompts driving this process are typically

Density Estimation via Binless Multidimensional Integration

arXiv:2407.08094v3 Announce Type: replace-cross Abstract: We introduce the Binless Multidimensional Thermodynamic Integration (BMTI) method for nonparametric, robust, and data-efficient density estima

researcharxiv-cs-lg

Deterministic Event-Graph Substrates as World Models for Counterfactual Reasoning

arXiv:2605.15967v1 Announce Type: new Abstract: We study event-graph substrates: a class of world models that represent agent state as an append-only log of typed RDF triples and answer counterfactual

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models

arXiv:2605.15706v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existi

agentsarxiv-cs-lg

DimMem: Dimensional Structuring for Efficient Long-Term Agent Memory

model-releasesarxiv-cs-cl

arXiv:2605.15759v1 Announce Type: new Abstract: Large language model (LLM) agents require long-term memory to leverage information from past interactions. However, existing memory systems often face a

Do Biological Structural Guarantees Earn Their Complexity?

arXiv:2605.15225v1 Announce Type: cross Abstract: Biologically-inspired AI agent frameworks claim reliability benefits through structural guarantees adapted from gene regulatory networks, immune syste

agentsarxiv-cs-ai

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

arXiv:2511.19399v3 Announce Type: replace-cross Abstract: Deep research agents perform multi-step research to produce long-form, well-attributed answers. However, most open deep research agents are tr

Dynamic Chunking for Diffusion Language Models

model-releasesarxiv-cs-cl

arXiv:2605.15676v1 Announce Type: new Abstract: Block discrete diffusion language models factorize a sequence autoregressively over fixed-size positional blocks, decoupling within-block parallel denoi

Ensuring Logic in the Fog: Sound POMDP Synthesis with LTL Objectives

arXiv:2605.12581v1 Announce Type: cross Abstract: Synthesising autonomous agents that can navigate uncertain environments while adhering to complex temporal constraints remains a fundamental challenge

Entropy Across the Bridge: Conditional-Marginal Discretization for Flow and Schrodinger Samplers

arXiv:2605.16126v1 Announce Type: cross Abstract: For a fixed flow-based generative model under a small inference budget, sample quality can depend strongly on where the sampler spends its few functio

Evaluating Design Video Generation: Metrics for Compositional Fidelity

arXiv:2605.16223v1 Announce Type: cross Abstract: Generative video models are increasingly used in design animation tasks, yet no standardized evaluation framework exists for this domain. Unlike natur

Federated Learning of Spiking Neural Networks under Heterogeneous Temporal Resolutions

arXiv:2605.15355v1 Announce Type: new Abstract: Spiking neural networks (SNNs) are biologically inspired energy-efficient models that use sparse binary spike-based communication between neurons, makin

Few-Step Diffusion Language Models via Trajectory Self-Distillation

arXiv:2602.12262v3 Announce Type: replace Abstract: Diffusion large language models (DLLMs) have emerged as powerful generative models with the promise of fast text generation through parallel decodin

researcharxiv-cs-cl

FFAvatar: Few-Shot, Feed-Forward, and Generalizable Avatar Reconstruction

arXiv:2605.15320v1 Announce Type: cross Abstract: Avatar reconstruction has traditionally relied on per-subject optimization that requires hours of computation or on expensive preprocessing that limit

ForMaT: Dataset for Visually-Grounded Multilingual PDF Translation

model-releasesarxiv-cs-cl

arXiv:2605.15794v1 Announce Type: new Abstract: We present ForMaT (Format-Preserving Multilingual Translation), a parallel corpus of 3,956 PDFs across 15 language pairs that preserves original layout

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding

arXiv:2605.15951v1 Announce Type: new Abstract: Finetuning Large Vision-Language Models with reinforcement learning has emerged as a promising approach to enhance their capability in object-level grou

researcharxiv-cs-cv