Search: “benchmark”

Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks

arXiv:2603.11689v2 Announce Type: replace Abstract: Frontier Multimodal Large Language Models (MLLMs) exhibit remarkable capabilities in Visual-Language Comprehension (VLC) tasks. However, they are of

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Research

Exploring Trust Calibration in XAI - The Impact of Exposing Model Limitations to Lay Users

DGX agent

arXiv:2605.18036v1 Announce Type: cross Abstract: Trust calibration -- aligning user trust judgment with model capability -- is crucial for safe deployment of explainable AI (XAI), yet is often evalua

researcharxiv-cs-ai

19 May 2026

exttt{SynC}: Synergistic Boosting of Structure and Representation for Deep Graph Clustering

arXiv:2406.15797v2 Announce Type: replace-cross Abstract: Employing graph neural networks (GNNs) for graph clustering has shown promising results in deep graph clustering. However, existing methods di

Factorized Latent Dynamics for Video JEPA: An Empirical Study of Auxiliary Objectives

arXiv:2605.17165v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPA) are a promising framework for self-supervised video representation learning, yet the behavior of auxilia

Tutorials

Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation

arXiv:2605.16350v1 Announce Type: cross Abstract: We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules,

tutorialsarxiv-cs-ai

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints

arXiv:2509.06984v3 Announce Type: replace-cross Abstract: Federated Learning with LoRA fine-tuning offers an efficient and privacy-aware solution for institutions to collaboratively leverage their lar

Fidelity Probes for Specification--Code Alignment

arXiv:2605.17246v1 Announce Type: cross Abstract: We introduce fidelity probes: natural-language questions generated from a reference artifact with code-derived ground-truth answers, answered from a c

Fine-grained List-wise Alignment for Generative Medication Recommendation

arXiv:2505.20218v2 Announce Type: replace Abstract: Accurate and safe medication recommendations are critical for effective clinical decision-making, especially in multimorbidity cases. However, exist

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization

arXiv:2605.17693v1 Announce Type: cross Abstract: Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and ma

Firefly: Illuminating Large-Scale Verified Tool-Call Data Generation from Real APIs

model-releasesarxiv-cs-cl

arXiv:2605.17558v1 Announce Type: cross Abstract: Training tool-calling agents requires large-scale trajectory data with verifiable labels, yet existing approaches either synthesize environments that

Flow Matching with Optimized Subclass Priors for Medical Image Augmentation

arXiv:2605.16469v1 Announce Type: cross Abstract: Rare diseases dominate the diagnostic challenge in medical imaging yet are severely underrepresented in clinical datasets, causing classifiers to fail

safetyarxiv-cs-cv

Form and Function: Machine Unlearning as a Problem of Misaligned States

arXiv:2605.17590v1 Announce Type: new Abstract: We formulate machine unlearning for online L-BFGS as a counterfactual state-alignment problem. Given an actual event stream and a deletion-edited counte

Tutorials

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster

arXiv:2605.18204v1 Announce Type: cross Abstract: Discrete diffusion models are a powerful class of generative models with strong performance across many domains. For efficiency, however, discrete dif

tutorialsarxiv-cs-lg

Fourier Compressor: Frequency-Domain Visual Token Compression for Vision-Language Models

arXiv:2508.06038v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) incur substantial computational overhead and inference latency due to the large number of vision tokens introduc

Fre-Res: Frequency-Residual Video Token Compression for Efficient Video MLLMs

arXiv:2605.16366v1 Announce Type: cross Abstract: Video MLLMs face a persistent tension between spatial fidelity and temporal coverage: preserving fine-grained visual details requires many spatial tok

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction

arXiv:2605.16927v1 Announce Type: new Abstract: Clinical decision-making is a feedback system where risk estimates influence treatment, which in turn changes disease trajectories, and both shape clini

Local Ai

From Volume to Value: Preference-Aligned Memory Construction for On-Device RAG

arXiv:2605.18271v1 Announce Type: cross Abstract: With the rapid emergence of personal AI agents based on Large Language Models (LLMs), implementing them on-device has become essential for privacy and

local-aiarxiv-cs-ai

Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps

arXiv:2605.16928v1 Announce Type: cross Abstract: Long-context inference in large language models is bottlenecked by the quadratic cost of full attention. Existing efficient alternatives often rely ei

FUNCanon: Learning Pose-Aware Action Primitives via Functional Object Canonicalization for Generalizable Robotic Manipulation

arXiv:2509.19102v2 Announce Type: replace-cross Abstract: General-purpose robotic skills from end-to-end demonstrations often leads to task-specific policies that fail to generalize beyond the trainin

safetyarxiv-cs-ai

Generation Navigator: A State-Aware Agentic Framework for Image Generation

arXiv:2605.17969v1 Announce Type: new Abstract: Despite rapid advances in text-to-image generation, faithfully realizing user intent remains challenging, often requiring manual multi-turn trial and er

safetyarxiv-cs-cv

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis

arXiv:2507.21035v3 Announce Type: replace Abstract: Gene expression analysis holds the key to many biomedical discoveries, yet extracting insights from raw transcriptomic data remains formidable due t

Geometry-Editable and Appearance-Preserving Object Compositon

arXiv:2505.20914v2 Announce Type: replace Abstract: General object composition (GOC) aims to seamlessly integrate a target object into a background scene with desired geometric properties, while simul

Geospatial-Reasoning-Driven Vocabulary-Agnostic Remote Sensing Semantic Segmentation

arXiv:2602.08206v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation has become an important direction in remote sensing, as it enables recognition beyond predefined land-cover ca

GeoWorld-VLM: Geometry from World Models for Vision-Language Models

arXiv:2605.16713v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) achieve strong semantic recognition, yet remain brittle on elementary spatial relations such as left of, on, behi

safetyarxiv-cs-ai

Local Ai

Global Prior Meets Local Consistency: Dual-Memory Augmented Vision-Language-Action Model for Efficient Robotic Manipulation

arXiv:2602.20200v2 Announce Type: replace-cross Abstract: Hierarchical Vision-Language-Action (VLA) models have rapidly become a dominant paradigm for robotic manipulation. It typically comprising a V

local-aiarxiv-cs-ai

GRaD-Nav++: Vision-Language Model Enabled Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics

model-releasesarxiv-cs-ro

arXiv:2506.14009v2 Announce Type: replace Abstract: Autonomous drones capable of interpreting and executing high-level language instructions in unstructured environments remain a long-standing goal. Y

GRAFT: Decoupling Ranking and Calibration for Survival Analysis

arXiv:2602.07884v2 Announce Type: replace-cross Abstract: Survival analysis is complicated by censored data, high-dimensional features, and non-linear interactions. Classical models offer interpretabi

Graph Embedding in the Graph Fractional Fourier Transform Domain

arXiv:2508.02383v2 Announce Type: replace Abstract: Spectral graph embedding plays a critical role in graph representation learning by generating low-dimensional vector representations from graph spec

Graph Hierarchical Recurrence for Long-Range Generalization

arXiv:2605.18387v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) and Graph Transformers (GTs) are now a fundamental paradigm for graph learning, combining the representation-learning cap

GraViti: Graph-Level Variational Autoencoders with Relaxed Permutation Invariance

arXiv:2605.16668v1 Announce Type: cross Abstract: We introduce GraViti, a transformer-based graph-level variational autoencoder that maps entire graphs to compact latent vectors. This design produces

HAD: Hallucination-Aware Diffusion Priors for 3D Reconstruction

arXiv:2605.16873v1 Announce Type: new Abstract: Diffusion priors have recently demonstrated strong capability in enhancing the quality of sparse-view 3D reconstruction by augmenting training views at

Helpful to a Fault: Measuring Illicit Assistance in Multi-Turn, Multilingual LLM Agents

arXiv:2602.16346v3 Announce Type: replace Abstract: LLM-based agents execute real-world workflows via tools and memory. These affordances enable ill-intended adversaries to also use these agents to ca

safetyarxiv-cs-cl

How Off-Policy Can GRPO Be? Mu-GRPO for Efficient LLM Reinforcement Learning

arXiv:2605.17570v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has been a key driver of recent progress in reinforcement learning with verifiable rewards (RLVR) for large

safetyarxiv-cs-cl

HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL

arXiv:2605.17792v1 Announce Type: new Abstract: Calibrating distributed hydrologic models is a critical bottleneck across operational water resources management - streamflow prediction, reservoir oper

Applications

Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions

arXiv:2605.16527v1 Announce Type: cross Abstract: Hypergraphs model higher-order relations that drive real-world decisions, from drug prescriptions to recommendations. A central structural signal in s

applicationsarxiv-cs-ai

Local Ai

IdGlow: Dynamic Identity Modulation for Multi-Subject Generation

arXiv:2603.00607v2 Announce Type: replace-cross Abstract: Multi-subject image generation requires seamlessly harmonizing multiple reference identities within a coherent scene. However, existing method

local-aiarxiv-cs-ai

Implicit Hierarchical GRPO: Decoupling Tool Invocation from Execution for Tool-Integrated Mathematical Reasoning

arXiv:2605.18500v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly leveraged tool invocation to enhance their reasoning capabilities. However, existing approaches typically

safetyarxiv-cs-cl

Improving MLLM Training Efficiency via Stage-Aware Sparsity

arXiv:2509.18150v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated outstanding performance across a variety of domains. However, training MLLMs is oft

safetyarxiv-cs-ai

Applications

Isolating Nonlinear Independent Sources in fMRI with eta-TCVAE Models

arXiv:2605.16708v1 Announce Type: new Abstract: Learning meaningful latent representations from nonlinear fMRI data remains a fundamental challenge in neuroimaging analysis. Traditional independent co

applicationsarxiv-cs-lg

KairosHope: A Next-Generation Time-Series Foundation Model for Specialized Classification via Dual-Memory Architecture

arXiv:2605.18657v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) have demonstrated notable success in general-purpose forecasting tasks; however, their adaptation to specialized

Kelvin v1.0: A Neural Pre-Encoder for H.264: A standards-compliant learned preprocessor with -27.62% BD-VMAF on UVG

model-releasesarxiv-cs-cv

arXiv:2605.16376v1 Announce Type: cross Abstract: Kelvin is a lightweight learned pre-encoder that sits in front of an unmodified libx264 encoder. It applies content-adaptive pixel adjustments, bounde

KISS - Knowledge Infrastructure for Scientific Simulation: A Scaffolding for Agentic Earth Science

arXiv:2605.17856v1 Announce Type: new Abstract: Process-based simulation models encode decades of scientific understanding across the Earth sciences, yet the communities most exposed to climate risk a

KVCapsule: Efficient Sequential KV Cache Compression for Vision-Language Models with Asymmetric Redundancy

arXiv:2605.16439v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have emerged as a critical and fast-growing extension of Large Language Models (LLMs) that enable multimodal reasoning t

Hardware

KVDrive: A Holistic Multi-Tier KV Cache Management System for Long-Context LLM Inference

arXiv:2605.18071v1 Announce Type: new Abstract: Supporting long-context LLMs is challenging due to the substantial memory demands of the key-value (KV) cache. Existing offloading systems store the ful

hardwarearxiv-cs-cl

Agents

LARGER: Lexically Anchored Repository Graph Exploration and Retrieval

arXiv:2605.16352v1 Announce Type: cross Abstract: Repository-level coding agents must first localize the files and symbols relevant to a task; failures at this stage can cascade across downstream obje

agentsarxiv-cs-ai

Agents

LASAR: Towards Spatio-temporal Reasoning with Latent Cognitive Map

arXiv:2605.16899v1 Announce Type: new Abstract: A fundamental challenge in embodied AI is verifying if agents build internal models of spatial structure or merely learn to mimic task-specific expert t

agentsarxiv-cs-cv

Agents

Latent Action Reparameterization for Efficient Agent Inference

arXiv:2605.18597v1 Announce Type: new Abstract: Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inf

agentsarxiv-cs-ai

Tutorials

Learning from Historical Activations in Graph Neural Networks

arXiv:2601.01123v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have demonstrated remarkable success in various domains such as social networks, molecular chemistry, and more. A

tutorialsarxiv-cs-ai