Search: “framework”

arXiv:2509.19707v2 Announce Type: replace-cross Abstract: Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and application

tutorialsarxiv-cs-lg

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Tutorials

Diffusion Graph Posterior Sampling for Nonlinear Inverse Problems with Application to Electrical Impedance Tomography

DGX agent

arXiv:2605.19621v1 Announce Type: cross Abstract: Deep generative models have emerged as state-of-the-art for solving inverse problems, but applying them to inverse problems for PDEs, like electrical

tutorialsarxiv-cs-lg

20 May 2026

Directed Acyclic Graph Convolutional Networks

arXiv:2506.12218v2 Announce Type: replace-cross Abstract: Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architec

safetyarxiv-cs-lg

Distribution-Free Uncertainty Quantification for Continuous AI Agent Evaluation

arXiv:2605.19779v1 Announce Type: new Abstract: We adapt split conformal prediction and adaptive conformal inference (ACI) to continuous AI agent evaluation, providing distribution-free coverage guara

DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model

arXiv:2602.23622v2 Announce Type: replace-cross Abstract: Significant progress has been made in the field of Instruction-based Image Editing Models (IIEMs). However, while these models demonstrate pla

Domain-Adaptive Communication-Rate Optimization for Sim-to-Real Humanoid-Robot Wireless XR Teleoperation

arXiv:2605.19293v1 Announce Type: cross Abstract: Wireless extended reality (XR) teleoperation provides embodied interaction capability for collecting humanoid robot demonstrations, but the large-scal

safetyarxiv-cs-lg

Don't Let Bandit Feedback Pull Continual LLM-Recommender Updates Off Target

arXiv:2605.18899v1 Announce Type: cross Abstract: Generative LLM-based recommenders (LLM-Rec) require continual post-deployment updates, yet deployment logs provide only policy-shaped contextual bandi

safetyarxiv-cs-ai

Tutorials

DOTRAG: Retrieval-Time Reasoning Along Paths

arXiv:2605.18760v1 Announce Type: cross Abstract: Graph Retrieval-Augmented Generation (GraphRAG) is dominated by a retrieve-then-reason paradigm, where context is retrieved using heuristics and then

tutorialsarxiv-cs-ai

Local Ai

Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding

arXiv:2605.20104v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates large language model inference by leveraging a draft-then-verify paradigm. To maximize the acceptance rate, rece

local-aiarxiv-cs-ai

Dr.LLM: Dynamic Layer Routing in LLMs

arXiv:2510.12773v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) process every token through all layers of a transformer stack, causing wasted computation on simple queries and i

Local Ai

Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection

arXiv:2605.19122v1 Announce Type: cross Abstract: Tensor-valued data arise naturally in neuroimaging, genomics, climate science, and spatiotemporal networks, where multilinear dependencies across mode

local-aiarxiv-cs-lg

DualView: Adaptive Local-Global Fusion for Multi-Hop Document Reranking

arXiv:2605.18767v1 Announce Type: cross Abstract: Multi-hop question answering requires aggregating information from multiple documents, a critical capability for knowledge-intensive applications. A f

Dynamic Model Merging Made Slim

arXiv:2605.18904v1 Announce Type: cross Abstract: Model merging enables the reuse of fine-tuned models without joint training or access to original data. Dynamic merging further improves flexibility b

DynaTok: Temporally Adaptive and Positional Bias-Aware Token Compression for Video-LLMs

arXiv:2605.19322v1 Announce Type: new Abstract: Recent advances in Video Large Language Models (Video-LLMs) have greatly expanded multimodal reasoning capabilities. However, the massive number of visu

safetyarxiv-cs-cv

DynaTrain: Fast Online Parallelism Switching for Elastic LLM Training

model-releasesarxiv-cs-lg

arXiv:2605.18815v1 Announce Type: new Abstract: Modern large language model (LLM) training is inherently dynamic: resource fluctuations, RLHF phase shifts, and cluster elasticity continually reshape t

Efficient Elicitation of Collective Disagreements

arXiv:2605.19521v1 Announce Type: new Abstract: We analyze the structure of the disagreement among a population of voters over a set of alternatives. Surveys typically ask either for pairwise comparis

Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention

arXiv:2605.19726v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) enable globally coherent, bidirectional, and controllable text generation, offering advantages over traditional autoreg

EgoCoT-Bench: Benchmarking Grounded and Verifiable Operation-Centric Chain of Thought Reasoning for MLLMs

arXiv:2605.19559v1 Announce Type: cross Abstract: The rapid development of Multimodal Large Language Models (MLLMs) has led to growing interest in egocentric video understanding, specifically the abil

Embedding by Elicitation: Dynamic Representations for Bayesian Optimization of System Prompts

arXiv:2605.19093v1 Announce Type: new Abstract: System prompts are a central control mechanism in modern AI systems, shaping behavior across conversations, tasks, and user populations. Yet they are di

EMO-BOOST: Emotion-Augmented Audio-Visual Features for Improved Generalization in Deepfake Detection

arXiv:2605.19630v1 Announce Type: new Abstract: With every advancement in generative AI models, forensics is under increasing pressure. The constant emergence of new generation techniques makes it imp

EnsemHalDet: Robust VLM Hallucination Detection via Ensemble of Internal State Detectors

arXiv:2604.02784v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) excel at multimodal tasks, but they remain vulnerable to hallucinations that are factually incorrect or unground

researcharxiv-cs-cl

EpiDiffVO: Geometry-Aware Epipolar Diffusion for Robust Visual Odometry

arXiv:2605.19556v1 Announce Type: new Abstract: Estimating relative pose from image pairs fundamentally requires only a minimal subset of geometrically consistent correspondences. However, most learni

EUPHORIA: Efficient Universal Planning via Hybrid Optimization for Robust Industrial Robotic Assembly

arXiv:2605.18872v1 Announce Type: cross Abstract: Robotic assembly in architectural construction faces a persistent bottleneck: existing planners are either highly specialized, requiring prohibitive r

EVA-0: Test-Time Model Evolution with Only Two Forward Passes per Sample

arXiv:2605.18867v1 Announce Type: cross Abstract: Test-time model evolution offers a promising way for deployed models to improve from unlabeled test-time experience, yet most existing methods depend

EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.19506v1 Announce Type: new Abstract: First-person dynamic spatial reasoning requires models to track continuous motion and precise geometric structure, but the quadratic attention cost of T

EviTrack: Selection over Sampling for Delayed Disambiguation

arXiv:2605.19283v1 Announce Type: cross Abstract: Sequential prediction is challenging in regimes of delayed disambiguation, where early observations are ambiguous and multiple latent explanations rem

Exposing Functional Fusion: A New Class of Strategic Backdoor in Dynamic Prompt Architectures

model-releasesarxiv-cs-cv

arXiv:2605.19478v1 Announce Type: cross Abstract: Existing ViT backdoor attacks based on backbone-overwriting full-tuning are computationally expensive and inflict performance degradation. This has fo

Eyes on VLM: Benchmarking Gaze Following and Social Gaze Prediction in Vision Language Models

arXiv:2605.19859v1 Announce Type: new Abstract: Vision-language models (VLMs) have rapidly evolved into general-purpose multimodal reasoners with strong zero-shot generalization. In this context, VLMs

Factor Augmented High-Dimensional SGD

arXiv:2605.19291v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is a fundamental optimization algorithm widely used in modern machine learning. In this paper, we propose Factor-Aug

researcharxiv-cs-lg

Agents

FAGER: Factually Grounded Evaluation and Refinement of Text-to-Image Models

arXiv:2605.19111v1 Announce Type: cross Abstract: Existing text-to-image (T2I) evaluation metrics mainly assess whether generated images align with information explicitly stated in the prompt, but oft

agentsarxiv-cs-ai

Fast-BEV++: Fast by Algorithm, Deployable by Design

model-releasesarxiv-cs-cv

arXiv:2512.08237v3 Announce Type: replace Abstract: The advancement of vision-only Bird's-Eye-View (BEV) perception, a core paradigm for cost-effective autonomous driving, is hindered by the long-stan

Feature-Space Smoothing: Certified Robustness of Deep Representations

arXiv:2601.16200v3 Announce Type: replace-cross Abstract: Modern deep learning models exhibit strong capabilities across diverse applications, yet remain vulnerable to malicious inputs that induce err

safetyarxiv-cs-cv

Applications

Feed-Forward Gaussian Splatting from Sparse Aerial Views

arXiv:2605.19949v1 Announce Type: new Abstract: Reconstructing large-scale urban scenes from sparse aerial views is a crucial yet challenging task. Due to biased top-down and shallow-oblique camera po

applicationsarxiv-cs-cv

FGSVQA: Frequency-Guided Short-form Video Quality Assessment

arXiv:2605.20016v1 Announce Type: cross Abstract: Short-form video poses new challenges to the quality assessment of user-generated content (UGC) due to its complex generation pipeline, rapid content

FineBench: Benchmarking and Enhancing Vision-Language Models for Fine-grained Human Activity Understanding

arXiv:2605.19846v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities in general video understanding, yet they often struggle with the fine-grained

Fingerprinting LLMs via Prompt Injection

arXiv:2509.25448v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are often modified after release through post-processing such as post-training or quantization, which makes it ch

researcharxiv-cs-cl

FlexDraft: Flexible Speculative Decoding via Attention Tuning and Bonus-Guided Calibration

arXiv:2605.20022v1 Announce Type: new Abstract: Speculative decoding accelerates memory-bound LLM inference without quality degradation by using a fast drafter to propose multiple candidate tokens and

researcharxiv-cs-cl

FlowErase-RL: Rethinking Concept Erasure as Reward Optimization in Flow Matching Models

arXiv:2605.19739v1 Announce Type: new Abstract: Recent advances in flow matching models have significantly improved text-to-image generation quality, but also introduce growing safety risks due to the

safetyarxiv-cs-cv

Formal Skill: Programmable Runtime Skills for Efficient and Accurate LLM Agents

arXiv:2605.19604v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly act inside real workspaces, where tools and skills determine whether model reasoning becomes reliable act

safetyarxiv-cs-ai

Tutorials

FreeOrbit4D: Training-Free Arbitrary Camera Redirection for Monocular Videos via Foreground-Complete 4D Reconstruction

arXiv:2601.18993v2 Announce Type: replace-cross Abstract: Camera redirection aims to replay a dynamic scene from a single monocular video under a user-specified camera trajectory. However, large-angle

tutorialsarxiv-cs-ai

From Division to Decision: Leveraging Temporal Cell-Stage Segmentation for Embryo Transferability Prediction

arXiv:2605.18923v1 Announce Type: cross Abstract: Accurate selection of bovine embryos is a challenging task, as current practice relies on a single expert assessment on the seventh day after insemina

From SGD to Muon: Adaptive Optimization via Schatten-p Norms

arXiv:2605.19781v1 Announce Type: new Abstract: Modern optimizers, like Muon, impose matrix-wise geometry constraints on their updates. These matrix-wise constraints can be unified under Linear Minimi

From Sparsity to Simplicity: Enabling Simpler Sequential Replacements via Sparse Attention Distillation

arXiv:2605.18865v1 Announce Type: cross Abstract: Self-attention serves as the core foundation of large-scale transformer pretraining, but its quadratic token interaction cost makes inference expensiv

Hardware

GEM: GPU-Variability-Aware Expert to GPU Mapping for MoE Systems

arXiv:2605.19945v1 Announce Type: cross Abstract: Mixture-of-Expert (MoE) models enable efficient inference by employing smaller experts and activating only a subset of them per token. MoE serving eng

hardwarearxiv-cs-ai

GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks

arXiv:2605.18873v1 Announce Type: cross Abstract: Training and evaluating false data injection attack (FDIA) detectors for power systems is constrained by data scarcity. Operational grid measurements

Generative Auto-Bidding with Unified Modeling and Exploration

arXiv:2605.19457v1 Announce Type: new Abstract: Automated bidding is central to modern digital advertising. Early rule-based methods lacked adaptability, while subsequent Reinforcement Learning approa

safetyarxiv-cs-ai

Generative Recursive Reasoning

arXiv:2605.19376v1 Announce Type: new Abstract: How should future neural reasoning systems implement extended computation? Recursive Reasoning Models (RRMs) offer a promising alternative to autoregres

GLUT: 3D Gaussian Lookup Table for Continuous Color Transformation

arXiv:2605.19889v1 Announce Type: cross Abstract: 3D Lookup Tables (3D LUTs) are widely used for color mapping, but their grid-based representation requires discretizing the RGB space, leading to a ca