Search: “inference”

Aura: Consistent Multi-Subject Video Generation via VLM-Grounded Semantic Alignment

arXiv:2607.04311v1 Announce Type: new Abstract: Subject-driven and multi-element video generation are central to controllable video synthesis, but existing methods still struggle to preserve identity

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Research

Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation

DGX agent

arXiv:2607.02968v1 Announce Type: new Abstract: Massive Activations (MAs) have been widely observed in Transformer-based models, yet their structure and functional roles in Diffusion Transformers (DiT

researcharxiv-cs-cv

7 Jul 2026

BanglaMemeEvidence: A Multimodal Benchmark Dataset for Explanatory Evidence Detection in Bengali Memes

arXiv:2607.03981v1 Announce Type: cross Abstract: Memes have become influential communication tools on social media, combining viral visuals with concise messaging to convey impactful ideas. While sub

Bayesian Invariance Modeling of Multi-Environment Data

arXiv:2506.22675v4 Announce Type: replace-cross Abstract: Invariant prediction [Peters et al., 2016] analyzes feature/outcome data from multiple environments to identify invariant features - those wit

researcharxiv-cs-lg

Beyond Independent Labels: Schwartz-Geometry Decoding for Human Value Detection

arXiv:2607.05052v1 Announce Type: cross Abstract: Human value detection is commonly formulated as sentence-level multi-label classification over the 19 refined Schwartz values, typically predicted as

Beyond Isolated Objects: Relationship-aware Open Vocabulary Scene Understanding via 3D Scene Graph Analysis

arXiv:2607.05348v1 Announce Type: new Abstract: Open-vocabulary 3D scene understanding aims to segment 3D scenes beyond predefined categories by transferring semantic knowledge from vision-language mo

Beyond Scene Priors: Fine-Grained Traffic Scene Reasoning with Benchmarking and Query-Guided Small-Object Focus

arXiv:2607.04149v1 Announce Type: new Abstract: In safety-critical traffic scenarios, answering complex questions relies on minute, localized visual cues. However, standard Multimodal Large Language M

BoRP: Bootstrapped Regression Probing for Scalable and Human-Aligned LLM Evaluation

arXiv:2601.18253v2 Announce Type: replace-cross Abstract: Accurate evaluation of user satisfaction is critical for iterative development of conversational AI. However, for open-ended assistants, tradi

BrainNormalizer: Anatomy-Informed Pseudo-Healthy Brain Reconstruction from Tumor MRI via Edge-Guided ControlNet

arXiv:2511.12853v2 Announce Type: replace-cross Abstract: Brain tumors induce complex structural deformations that obscure the patient' s original neuroanatomy, making it difficult to distinguish tumo

CDST: Color Disentangled Style Transfer for Universal Style Reference Customization

arXiv:2506.13770v2 Announce Type: replace Abstract: We introduce Color Disentangled Style Transfer (CDST), a novel and efficient two-stream style transfer training paradigm which completely isolates c

City landscape in sight: A crowdsourced framework for unlocking urban-scale window view perceptions from real estate imagery

arXiv:2606.15198v2 Announce Type: replace Abstract: City landscapes viewed through home windows influence quality of life, yet perceptions of actual window views at the urban scale remain understudied

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving

arXiv:2607.02841v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-m

CoACT: Action-Preserving Observation Compression for Coding Agents

arXiv:2607.02911v1 Announce Type: cross Abstract: LLM-based coding agents solve software-engineering tasks through iterative interactions with development environments, where returned observations acc

agentsarxiv-cs-ai

CogRad: A Cognitively-Inspired Multi-Agent Framework for Radiology Report Generation

arXiv:2607.03853v1 Announce Type: new Abstract: Automated radiology report generation (RRG) can ease radiologist workload, yet most existing systems produce a report in a single forward pass, with no

agentsarxiv-cs-cv

Tutorials

CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion

arXiv:2607.05046v1 Announce Type: new Abstract: Evaluating generative AI models is a routine, but resource-intensive, process that is conducted over and over again during the course of model developme

tutorialsarxiv-cs-lg

Cortex: A Bidirectionally Aligned Embodied Agent Framework for Long-horizon Manipulation

arXiv:2607.05377v1 Announce Type: cross Abstract: While recent Vision-Language-Action (VLA) models show promise toward generalist manipulation policies, they struggle with long-horizon tasks due to th

agentsarxiv-cs-ai

Coverage-Controlled Preference Mining from Noisy Claim Verification for Evidence-Grounded Generation

arXiv:2603.10494v2 Announce Type: replace Abstract: Evidence-grounded generation produces summaries whose claims should be supported by supplied evidence, but claim-level verifiers provide noisy feedb

safetyarxiv-cs-cl

Criterion-Conditional In-Context Learning: Evaluating Criterion-Shift Adaptation in Vision-Language Models

arXiv:2607.02575v1 Announce Type: cross Abstract: Vision-language models can perform new tasks without parameter updates through in-context learning (ICL), whose core mechanism is utilizing the suppor

CritiqueDriveVLM: From Verifier-Guided Reinforcement Learning to Latent Thought Distillation for Autonomous Driving

arXiv:2607.04179v1 Announce Type: cross Abstract: End-to-end Vision-Language Models (VLMs) show immense potential in autonomous driving. However, standard Supervised Fine-Tuning (SFT) often suffers fr

DeGenseGS: Geometrically and Semantically Decoupled Surgical Scene Understanding in 4D Gaussian Splatting

arXiv:2607.04761v1 Announce Type: new Abstract: Real-time, text-promptable 4D reconstruction is indispensable for autonomous surgical interaction. Severe misalignment between semantic meaning and phys

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)

arXiv:2607.04223v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reduces but does not eliminate hallucination, and existing detectors return a single answer-level score that does

researcharxiv-cs-ai

DiCE-CIR: Direct Composition Learning for Efficient Zero-Shot Composed Image Retrieval

arXiv:2607.04665v1 Announce Type: new Abstract: Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image from a multimodal query consisting of a reference image and an edit text des

DistillH-Mamba: A Hypergraph-Mamba-Based Knowledge Distillation Model for Efficient Impact Fall Detection

arXiv:2607.03156v1 Announce Type: new Abstract: Falls among the elderly represent a significant public health concern due to their prevalence, consequences, and societal burden. While deep learning ha

Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval

arXiv:2607.04605v1 Announce Type: cross Abstract: Multi-vector vision-language retrieval preserves fine-grained visual evidence through maximum-similarity late interaction, but dense image-side tokens

researcharxiv-cs-ai

Don't Commit Alone: Joint Token Commitment in Diffusion Large Language Models

arXiv:2607.04469v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) commit multiple tokens per denoising step by decoding each selected position independently from the shared conte

researcharxiv-cs-cl

dOPSD: On-Policy Self-Distillation for Diffusion Language Models

arXiv:2607.04428v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising a masked sequence, offering a parallel alternative to autoregressive mo

DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation

arXiv:2607.04927v1 Announce Type: cross Abstract: World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense super

Efficient bias mitigation in T2I diffusion models using Concept Graphs

arXiv:2607.03397v1 Announce Type: new Abstract: Text-to-Image diffusion models often propagate harmful bias inherited from the training data. Existing bias mitigation techniques typically intervene on

Efficient Flow Matching for Sparse-View CT Reconstruction

arXiv:2603.00205v2 Announce Type: replace-cross Abstract: Generative models, particularly Diffusion Models (DM), have shown strong potential for Computed Tomography (CT) reconstruction serving as expr

researcharxiv-cs-ai

EVAS: Efficient Multimodal Temporal Forgery Localization via Audio-Visual Synergy and Steered Boundary Calibration

arXiv:2607.04472v1 Announce Type: new Abstract: The rapid proliferation of artificial intelligence-generated content necessitates reliable multimodal forensics. Beyond video-level binary classificatio

FDR-Occ: Factorized Dense Routing for Full-Spectrum 3D Occupancy Prediction

arXiv:2607.03822v1 Announce Type: new Abstract: Vision-based 3D occupancy prediction fundamentally relies on the 2D-to-3D view transformation. Current paradigms predominantly utilize explicit physical

local-aiarxiv-cs-cv

FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture

arXiv:2607.04085v1 Announce Type: cross Abstract: Routing-prediction federated learning has emerged as a new paradigm that reframes inter-client heterogeneity as a resource for system-level intelligen

local-aiarxiv-cs-ai

Applications

Fine-Grained Computation Offload for Off-the-Shelf Servers in Tens of Lines

arXiv:2607.02630v1 Announce Type: cross Abstract: Hardware accelerators now sit on the critical path of online serving. GPUs, FPGAs, and increasingly remote services such as hardware security modules,

applicationsarxiv-cs-ai

FOI-O: An NZ-first ontology and verification methods package for Freedom of Information process modelling

arXiv:2607.02947v1 Announce Type: cross Abstract: Public official-information request records contain process signals. They can support research, workflow review, and human-supervised agent help. Yet

agentsarxiv-cs-cl

Forethought: Verifiable Reasoning from Neurosymbolic Primitive Programming

arXiv:2607.04096v1 Announce Type: new Abstract: Current agentic workflows usually involve decomposing user requests into sequences of tool calls with correctly resolved parameters, the results of whic

Fortifying Fully Convolutional Generative Adversarial Networks for Image Super-Resolution Using Divergence Measures

arXiv:2404.06294v2 Announce Type: replace-cross Abstract: Super-Resolution (SR) is a time-hallowed image processing problem that aims to improve the quality of a Low-Resolution (LR) sample up to the s

FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion

arXiv:2607.04125v1 Announce Type: new Abstract: Small object detection in Unmanned Aerial Vehicle (UAV) imagery remains challenging under adverse conditions, including complex weather, low illuminatio

Applications

From Geometric Labels to Semantic Understanding of Indoor Building Components Using Multimodal Large Language Models

arXiv:2607.03661v1 Announce Type: new Abstract: Point cloud-based understanding has become an important enabler for facility operation and maintenance involving indoor building components. However, ex

applicationsarxiv-cs-cv

Gemma 4 Technical Report

arXiv:2607.02770v1 Announce Type: cross Abstract: We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute effi

GenShin: Guiding Rational Liposome Design by Ranking Liposomal Protein Corona through a Docking-Pose-Free GNN

arXiv:2504.13853v2 Announce Type: replace-cross Abstract: Rational design of lipid nanoparticles (LNPs) for tissue-specific delivery critically depends on predicting the composition of the protein cor

Geometry-Aware Bayesian Quantification via Compositional Data Analysis

arXiv:2607.04977v1 Announce Type: new Abstract: Accurately estimating the unknown target label distribution is the critical first step for adapting to label shift. This task, widely known as quantific

researcharxiv-cs-lg

Geometry-aware Depth-guided Representation Learning for Structure-preserving Low-light Image Enhancement

arXiv:2607.05005v1 Announce Type: new Abstract: Low-light degradation reduces image visibility and weakens structural cues that are important for visual representation and scene understanding. Existin

GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Text

arXiv:2312.15320v3 Announce Type: replace-cross Abstract: Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests, and genetic

Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection

arXiv:2607.03817v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) show strong few-shot generalization, but industrial anomaly detection remains difficult because defects are small, input

local-aiarxiv-cs-cv

Tutorials

GMODiff: One-Step Gain Map Refinement with Diffusion Priors for HDR Reconstruction

arXiv:2512.16357v3 Announce Type: replace Abstract: Pre-trained Latent Diffusion Models (LDMs) have recently shown strong perceptual priors for low-level vision tasks, making them a promising directio

tutorialsarxiv-cs-cv

Governed MCP: Kernel-Level Tool Governance for AI Agents via Logit-Based Safety Primitives

arXiv:2604.16870v2 Announce Type: replace-cross Abstract: AI agents increasingly call external tools (file system, network, APIs) through the Model Context Protocol (MCP). These tool calls are the age

Graph Neural Networks are Heuristics

arXiv:2601.13465v4 Announce Type: replace Abstract: Graph neural networks are usually treated as auxiliaries for combinatorial optimization: they imitate algorithms, guide search, or supply scores to

local-aiarxiv-cs-ai

GUSH3R: Everyone Everywhere All at Once as Gaussians

arXiv:2607.05243v1 Announce Type: new Abstract: Reconstructing dynamic human-scene environments from monocular videos is a challenging problem that requires jointly modeling scene geometry, camera mot