Search: “benchmark”

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

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Disco-LoRA: Disentangled Composition of Content, Style, and Motion for Multi-concept Video Customization

DGX agent

arXiv:2606.26668v1 Announce Type: cross Abstract: Video customization based on Text-to-Video (T2V) models aims to learn specific features from reference data to generate controllable videos. While sig

model-releasesarxiv-cs-ai

26 Jun 2026

Tutorials

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

arXiv:2508.02753v5 Announce Type: replace-cross Abstract: Time Series Forecasting (TSF) faces persistent challenges in modeling intricate temporal dependencies across different scales. Despite recent

tutorialsarxiv-cs-ai

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

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

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

Applications

Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting

arXiv:2601.16632v4 Announce Type: replace-cross Abstract: Time series forecasting has witnessed significant progress with deep learning. While prevailing approaches enhance forecasting performance by

applicationsarxiv-cs-ai

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

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation

arXiv:2606.27268v1 Announce Type: cross Abstract: Recently, a few works have made early attempts to study test-time scaling for embodied tasks. However, two major challenges remain unsolved: (1) reaso

safetyarxiv-cs-ai

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

Event-Aware Instructed Assistant for Referring Video Segmentation

arXiv:2606.26994v1 Announce Type: cross Abstract: Existing referring video segmentation methods often treat a video as a single event consisting of multiple images, overlooking the fact that a video t

researcharxiv-cs-ai

EvoEmbedding: Evolvable Representations for Long-Context Retrieval and Agentic Memory

arXiv:2606.21649v2 Announce Type: replace Abstract: Existing embedding models are inherently static: they encode text segments in isolation, ignoring their surrounding context and temporal order. This

agentsarxiv-cs-cl

extsc{DiARC}: Distinguishing Positive and Negative Samples Helps Improving ARC-like Reasoning Ability of Large Language Models

arXiv:2606.26530v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC;~itealp{chollet2019measure}) contains tasks that require summarizing patterns from limited grid samples and

From Weights to Features: SAE-Guided Activation Regularization for LLM Continual Learning

model-releasesarxiv-cs-cl

arXiv:2606.26629v1 Announce Type: cross Abstract: Weight-space regularization methods such as Elastic Weight Consolidation (EWC) are the standard approach to catastrophic forgetting in continual learn

fTNN: a tensor neural network for fractional PDEs

arXiv:2606.27140v1 Announce Type: new Abstract: We develop the fTNN, a deterministic tensor neural network subspace method for problems involving the fractional Laplacian on bounded domains, taking th

researcharxiv-cs-lg

GAVEL: Grounded Caption Error Verification and Localization

model-releasesarxiv-cs-cl

arXiv:2606.26923v1 Announce Type: new Abstract: Vision-language models (VLMs) often produce hallucinated or inconsistent outputs, where text and images are not properly aligned. Addressing this issue

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models

arXiv:2606.26287v1 Announce Type: new Abstract: With the increase in model parameters and training data, the instruction following and generalization capabilities of Large VisionLanguage Models (LVLMs

Tutorials

Generating a Paracosm for Training-Free Zero-Shot Composed Image Retrieval

arXiv:2602.00813v5 Announce Type: replace Abstract: Composed Image Retrieval (CIR) is the task of retrieving a target image from a database using a multimodal query, which consists of a reference imag

tutorialsarxiv-cs-cv

Applications

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

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

Applications

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

HOB: A Holistically Optimized Bidding Strategy under Heterogeneous Bidding Environments

arXiv:2510.15238v2 Announce Type: replace-cross Abstract: Optimizing a single advertising campaign across heterogeneous channels is a central challenge in industrial autobidding. Auction mechanisms va

Hybrid privacy-aware semantic search: SVD-truncated document geometry and CKKS-encrypted query reranking under a restricted threat model

arXiv:2606.26373v1 Announce Type: cross Abstract: Dense embeddings power semantic search and retrieval-augmented generation, but embedding-inversion attacks can reconstruct source text from a vector:

HyperDFlash: MHC-Aligned Block Speculative Decoding with Gated Residual Reduction

model-releasesarxiv-cs-cl

arXiv:2606.26744v1 Announce Type: cross Abstract: We present HyperDFlash, a block-parallel speculative decoding framework tailored to the novel multi-hyper-connection (MHC) architecture proposed by De

Implementation of reinforcement learning in chemical reaction networks: application to phototaxis as curiosity-driven exploration

arXiv:2606.26168v1 Announce Type: new Abstract: Living systems navigate environments using noisy and incomplete sensory signals. In unicellular algae, phototaxis is often modeled as a mechanistic run-

In-Context Model Predictive Generation: Open-Vocabulary Motion Synthesis from Language Models to Physics

arXiv:2606.26981v1 Announce Type: cross Abstract: Synthesizing human motion from textual descriptions is essential for immersive digital applications, yet existing methods face a persistent trade-off

safetyarxiv-cs-ai

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

Inherited Circuits, Learned Semantics: How Fine-Tuning Creates Evasion Vulnerabilities Invisible to Standard Evaluation

arXiv:2606.27091v1 Announce Type: cross Abstract: LLMs fine-tuned for security classification are usually evaluated on held-out examples from the same distribution as their training data. We show that

Knowledge-augmented Agentic AI for Mental Health Medication Information Seeking

arXiv:2606.26205v1 Announce Type: new Abstract: Patients increasingly seek medication information online, yet safety knowledge for psychiatric drugs is split between regulatory adverse-event records,

safetyarxiv-cs-ai

Learning from the Self-future: On-policy Self-distillation for dLLMs

arXiv:2606.18195v2 Announce Type: replace Abstract: On-policy self-distillation (OPSD) has proven effective for post-training large language models (LLMs), yet its application to diffusion LLMs (dLLMs

safetyarxiv-cs-cl

Learning Long-Range Dependencies with Temporal Predictive Coding

arXiv:2602.18131v2 Announce Type: replace Abstract: Temporal Predictive Coding provides a layer-local, parallelisable mechanism for learning in recurrent systems, making it an attractive candidate for

Learning Robust Penetration Testing Policies under Partial Observability: A systematic evaluation

arXiv:2509.20008v2 Announce Type: replace Abstract: Penetration testing, the simulation of cyberattacks to identify security vulnerabilities, presents a sequential decision-making problem well-suited

safetyarxiv-cs-lg

Learning to Select Maximum Clique Algorithms: From Traditional Machine Learning to a Dual-Channel Hybrid Neural Architecture

arXiv:2508.08005v4 Announce Type: replace-cross Abstract: The Maximum Clique Problem (MCP) is an NP-hard problem with wide-ranging applications in fields such as bioinformatics, network science, and s

Limited Reference, Reliable Generation: A Two-Component Framework for Tabular Data Generation in Low-Data Regimes

arXiv:2509.09960v2 Announce Type: replace-cross Abstract: Synthetic tabular data generation is increasingly essential in machine learning, supporting downstream applications when real-world, high-qual

LiMoDE: Rethinking Lifelong Robot Manipulation from a Mixture-of-Dynamic-Experts Perspective

arXiv:2606.26183v1 Announce Type: cross Abstract: Building a generalist robot that can leverage prior knowledge for continuous task adaptation remains a significant challenge. Previous works alleviate

LiveEdit: Towards Real-Time Diffusion-Based Streaming Video Editing

arXiv:2606.26740v1 Announce Type: new Abstract: Streaming video editing has made rapid progress, yet practical deployment is still limited by two core issues: maintaining stable backgrounds and non-ed

LogicIR: Logic Gate Networks for Image Restoration

arXiv:2606.26609v1 Announce Type: new Abstract: Image restoration aims to reconstruct high-quality images from degraded low-quality inputs. As the computational demands of image restoration models con

Look-Before-Move: Narrative-Grounded World Visual Attention in Dynamic 3D Story Worlds

arXiv:2606.26964v1 Announce Type: new Abstract: As embodied AI and world models increasingly operate in dynamic 3D environments, visual perception must move beyond passively interpreting given observa

Mask to Concept: Auto-Promptable SAM3 via Efficient Test-Time Concept Embedding Search for Few-Shot Annotation

arXiv:2606.26711v1 Announce Type: new Abstract: Transforming foundation segmentation models from human-prompted tools into auto-promptable annotators is critical for scalable medical data annotation.

MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

arXiv:2604.01958v2 Announce Type: replace Abstract: Infrared and visible video fusion combines the object saliency from infrared images with the texture details from visible images to produce semantic

Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data

arXiv:2606.26498v1 Announce Type: cross Abstract: This paper addresses model-free continuous-time mean-field control in a setting where the population dynamics evolve continuously according to an unkn

MedPruner: Training-Free Hierarchical Token Pruning for Efficient 3D Medical Image Understanding in Vision-Language Models

arXiv:2603.11625v2 Announce Type: replace-cross Abstract: While specialized Medical Vision-Language Models (VLMs) have achieved remarkable success in interpreting 2D and 3D medical modalities, their d

researcharxiv-cs-ai

MIRROR: Novelty-Constrained Memory-Guided MCTS Red-Teaming for Agentic RAG

arXiv:2606.26793v1 Announce Type: cross Abstract: Multimodal agentic retrieval-augmented generation (RAG) systems expand the attack surface beyond prompt injection to include text poisoning, image inj

agentsarxiv-cs-ai

Mitigating Hallucinations via Inter-Layer Consistency Aggregation in Large Vision-Language Models

arXiv:2505.12343v2 Announce Type: replace-cross Abstract: Despite the impressive capabilities of Large Vision-Language Models (LVLMs), they remain susceptible to hallucinations, where generated conten

researcharxiv-cs-ai

Multilingual Reasoning Cascades Need More Context

arXiv:2606.27306v1 Announce Type: new Abstract: Translation cascades for reasoning translate the query from another language to English, reason in English, and translate the answer back to the origina

researcharxiv-cs-cl

NebulaExp-8B: An Empirical Post-Training Pipeline via Full-Scale Ablation Research

arXiv:2606.26671v1 Announce Type: new Abstract: Post-training alignment determines the reasoning and human preference following capabilities of large language models, yet most existing works withhold

NeuraDock Visual Cognitive Load Agent Tutorial: A Quality-Gated Open-Source EEG Workflow for Alpha Dynamics and Real-Time Applications

arXiv:2606.26518v1 Announce Type: new Abstract: This tutorial paper provides a step-by-step, reproducible walkthrough of NeuraDock Agent, an open-source EEG agent focused on Alpha dynamics and visual

agentsarxiv-cs-ai

Tutorials

Neural Voxel Dynamics: Learning Implicit 3D Physics via Volumetric Feature Advection

arXiv:2606.26410v1 Announce Type: new Abstract: We present a self-supervised framework for learning implicit 3D physical dynamics directly from video-derived supervisory signals. While current generat

tutorialsarxiv-cs-cv