Search: “framework”

Debias in Text, Believe Your Eyes: Text-Anchored Cross-Modal Transfer for Visual Counter-Commonsense Reasoning

arXiv:2608.06938v1 Announce Type: cross Abstract: The visual reasoning ability of multimodal large language models (MLLMs) is crucial for downstream applications, particularly counter-commonsense reas

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Model Releases

Deep Evidential Regression for Sparse Forest Height Estimation from Multimodal Satellite Imagery

DGX agent

arXiv:2608.06406v1 Announce Type: new Abstract: Accurate estimation of forest height from satellite imagery is essential for applications such as carbon accounting, biodiversity monitoring, and ecosys

model-releasesarxiv-cs-cv

10 Aug 2026

Tutorials

Defining Energy Indicators for Impact Identification on Aerospace Composites: A Structured Feature Selection Approach Guided by Domain Knowledge

arXiv:2511.01592v2 Announce Type: replace Abstract: Energy estimation is critical to impact identification on aerospace composites, where low-velocity impacts can induce internal damage that is undete

tutorialsarxiv-cs-lg

Density-aware Hierarchical Clustering Based on Element-Categorized Connection Subgraphs

arXiv:2608.06990v1 Announce Type: cross Abstract: Clustering is a fundamental data mining technique for pattern recognition through unsupervised learning. Among various clustering methods, hierarchica

DiDPO: Diff-in-Diff Policy Optimization for Coding Agent Training

arXiv:2608.07147v1 Announce Type: new Abstract: Reinforcement learning with Verifiable Reward (RLVR) has emerged as a powerful paradigm for training coding agents, where the execution feedback from co

DocMemo: Dynamic Evidence Discovery via Probabilistic Memory-Guided Retrieval for Multi-Modal Document Understanding

arXiv:2608.07067v1 Announce Type: new Abstract: Long-document understanding requires locating sparse and heterogeneous evidence across hundreds of pages, yet existing systems remain limited by static

Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models?

arXiv:2608.07006v1 Announce Type: new Abstract: Visual retrieval-augmented generation (RAG) commonly expands the retrieved evidence set to improve answer-page coverage, implicitly assuming that all av

researcharxiv-cs-cl

ED-CSP: Crystal Structure Prediction from Electron Diffraction

arXiv:2608.06448v1 Announce Type: cross Abstract: Recovering a periodic 3D crystal structure from sparse, unindexed electron diffraction (ED) observations is a challenging generative inverse problem.

EliSeg: Verified Target Construction for Report-Grounded Abnormality Segmentation

arXiv:2608.07299v1 Announce Type: cross Abstract: Radiology reports describe clinical observations but do not specify executable segmentation targets. They may contain present, negated, prior,uncertai

ELMZip: Onboard Satellite Image Compression via Extreme Learning Machines for Efficient Downlink

arXiv:2608.06942v1 Announce Type: cross Abstract: The acquisition of multispectral imagery via small satellites (e.g., CubeSats) presents significant data downlink challenges due to high data volumes

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization

arXiv:2608.07248v1 Announce Type: cross Abstract: We prove that mirror descent converges to a KKT point for the nonconvex problem without excluding boundary limits. The result holds under verifiable c

researcharxiv-cs-lg

FinRank: An Evidence-Grounded Benchmark for Financial Question Answering and Retrieval over SEC Filings

arXiv:2608.07400v1 Announce Type: new Abstract: Financial question answering is typically evaluated by answer correctness, yet in SEC filings a plausible and even numerically correct answer can be gro

Flow-Corrected Shape Optimization: Taming Manifold Drift in High-Dimensional 3D Models

arXiv:2608.07199v1 Announce Type: new Abstract: Optimizing 3D shapes within the latent spaces of deep generative models is fundamental to computer assisted engineering, yet remains prone to a critical

Fluid-DiT: Graph-Free Diffusion Transformers for Fluid Flow Simulations Learning

arXiv:2608.07161v1 Announce Type: cross Abstract: Simulating complex fluid flows requires capturing full equilibrium distributions rather than just mean trajectories, yet high-fidelity solvers remain

From Cheap Fakes to Pure Synthesis: Addressing the New Era of T2V Fake News Videos

arXiv:2608.06732v1 Announce Type: new Abstract: Recent text-to-video (T2V) generation models enable fake news videos to be synthesized from scratch, shifting the threat beyond cheap fakes assembled fr

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning

arXiv:2608.06894v1 Announce Type: new Abstract: Neural operators have become a central tool for solving partial differential equations (PDEs), with spectral operators offering efficient global mixing

Game-Theoretic Inverse Reinforcement Learning for Modeling Competitive Human Driving: A Cut-in Prediction Study

model-releasesarxiv-cs-lg

arXiv:2608.06445v1 Announce Type: cross Abstract: Capturing the strategic decision-making inherent in competitive human driving is critical for autonomous vehicle safety and traffic simulation. This s

GeoDistill-Refine: Silhouette-First Geometry Distillation for Annotation-Free Spacecraft Segmentation

arXiv:2608.07405v1 Announce Type: cross Abstract: Foundation segmentation models can provide supervision for spacecraft imagery without manual training masks, but their predictions vary with textual p

Agents

Harnessing the Synergy between LLM Agents and Knowledge Graphs for Urban Socioeconomic Prediction

arXiv:2411.00028v3 Announce Type: replace-cross Abstract: Socioeconomic prediction aims to leverage various urban data to predict the socioeconomic indicators of regions such as population and commerc

agentsarxiv-cs-ai

HazeSpikeMamba: Coupling Spiking-Inspired and State-Space Features for Self-Supervised Real-World Dehazing

arXiv:2608.06886v1 Announce Type: new Abstract: Dehazing networks are commonly trained on synthetic hazy-clear pairs, but their performance often drops on real photographs. Synthetic haze generated us

local-aiarxiv-cs-cv

HFS: Holistic Query-Aware Frame Selection for Efficient Video Understanding

arXiv:2512.11534v2 Announce Type: replace-cross Abstract: Key frame selection is essentially a set-level optimization problem: the quality of the selected subset depends on the interactions among fram

researcharxiv-cs-cl

High-dimensional ridgeless least squares interpolation under spiked covariance structures

arXiv:2608.07281v1 Announce Type: cross Abstract: This paper investigates the asymptotic behavior of the out-of-sample prediction risk of the high-dimensional ridgeless least-squares estimator when th

safetyarxiv-cs-lg

HNR-DAC: Hard-Negative Reranking and Distribution-Aligned Classification for Scientific Claim Verification

arXiv:2608.07204v1 Announce Type: new Abstract: Scientific claim verification over a cited paper requires predicting the claim--paper relation and identifying the paragraphs that justify that predicti

researcharxiv-cs-cl

Human-AI Perceptual Alignment by Playing Hues and Cues

arXiv:2608.07141v1 Announce Type: new Abstract: Evaluating the perceptual alignment between Contrastive Vision-Language Models (CVLMs) and humans is typically constrained by traditional benchmarks tha

local-aiarxiv-cs-cv

I Seek You in Videos: Identity-Conditioned Queries for Person-Centric Video Reasoning

arXiv:2608.07417v1 Announce Type: cross Abstract: Real-world video reasoning often involves multimodal, multi-source inputs, whereas existing video reasoning tasks typically assume a simplified video-

Identity as Presence: Towards Appearance and Voice Personalized Joint Audio-Video Generation

arXiv:2603.17889v4 Announce Type: replace Abstract: Recent advances in video synthesis have enabled realistic integration of real individuals, driving demand for identity-aware generation. While emerg

safetyarxiv-cs-cv

Implicit Neural Speckle Denoising

arXiv:2608.06574v1 Announce Type: cross Abstract: Speckle fundamentally limits coherent imaging by introducing multiplicative, spatially correlated noise that obscures scene structure. Removing speckl

Tutorials

InstanceSplat: Instance-Aware Feed-Forward 3D Gaussian Splatting for Scene Understanding

arXiv:2608.07144v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) enables efficient and generalizable 3D reconstruction, but current feed-forward 3DGS methods for scene underst

tutorialsarxiv-cs-cv

Agents

Joint Optimization of Reasoning and Dual-Memory for Self-Learning Diagnostic Agent

arXiv:2604.07269v2 Announce Type: replace Abstract: Clinical expertise improves not only by acquiring medical knowledge, but by accumulating experience that yields reusable diagnostic patterns. Recent

agentsarxiv-cs-cl

KnifeHunter: Structured Local Representation Learning for Fine-Grained Knife Image Retrieval in Law Enforcement

arXiv:2608.07057v1 Announce Type: new Abstract: Knife-enabled violence presents a major public safety challenge, and law enforcement agencies require scalable tools for catalogue-level knife identific

safetyarxiv-cs-cv

KReF: Training-Free Retrieval for Long-Term Time-Series Forecasting and Predictive Uncertainty

arXiv:2608.06748v1 Announce Type: cross Abstract: Probabilistic long-term time-series forecasting commonly relies on trained models. Training-free conformal methods typically construct intervals aroun

Latent Fact-Checking: Detecting Misinformation through Activation Engineering

model-releasesarxiv-cs-cl

arXiv:2608.06417v1 Announce Type: cross Abstract: The proliferation of misinformation online has driven demand for scalable detection systems. While most existing approaches rely on surface-level ling

M2-SMap: Memory-Efficient Semantic Mapping with Hierarchical Multi-Model Representation

arXiv:2608.07074v1 Announce Type: new Abstract: Dense point cloud maps, as a typically used mapping representation, are difficult to deploy on resource-constrained robots because their memory consumpt

local-aiarxiv-cs-ro

MaskFlow: Precise, Consistent and Seamless Regional Image Editing

arXiv:2608.06929v1 Announce Type: cross Abstract: Regional image editing has attracted considerable attention for its spatial controllability. Although instruction-based and mask-reference-based editi

MAUPITI: On-Device Prototype-Based Learning on a Smart Infrared Sensor

arXiv:2608.07192v1 Announce Type: new Abstract: Low-resolution infrared (IR) array sensors represent an interesting solution for privacy-preserving human sensing in embedded systems. In this letter, w

local-aiarxiv-cs-lg

MemPrism: Task-Conditioned Relational Memory Views for Long-Horizon Agents

arXiv:2608.06745v1 Announce Type: new Abstract: Long-horizon agents rely on memory to reuse experiences, yet existing memory systems often assume that evidence can be directly consumed through a fixed

MirrorWorld: Taming Video Diffusion Models for Mirror Reflection Generation

model-releasesarxiv-cs-cv

arXiv:2608.07463v1 Announce Type: new Abstract: Recent advances in video diffusion models (VDMs) have enabled high-fidelity video synthesis. However, generating mirror reflections remains challenging

Modular TTT: Rethinking Test-Time Training as Composable Modules

model-releasesarxiv-cs-cl

arXiv:2608.07110v1 Announce Type: cross Abstract: Test-time training (TTT) views sequence modeling as an online learning problem in which fast weights are updated by an internal learning rule. Despite

Multi Codec Discrete Diffusion Model for Text Guided Speech Inpainting and Editing

model-releasesarxiv-cs-cl

arXiv:2608.06424v1 Announce Type: cross Abstract: Speech recordings often contain missing, corrupted, or incorrect regions that must be reconstructed or modified without re-synthesizing the entire utt

Multiple Hypothesis Flow Estimation for Video Frame Interpolation under Matching Ambiguity

model-releasesarxiv-cs-cv

arXiv:2608.07120v1 Announce Type: new Abstract: Many flow-based video frame interpolation (VFI) methods synthesize an intermediate frame by estimating optical flow fields, warping the two input frames

Tutorials

Omni-modal decomposition autoencoders learn full-stack wearable disentangled representations

arXiv:2608.07385v1 Announce Type: cross Abstract: Learning disentangled representations is a key requirement for developing versatile, general-purpose, and sustainable models in multi-modal wearable c

tutorialsarxiv-cs-ai

Panoramic Multimodal Semantic Occupancy Prediction for Quadruped Robots

model-releasesarxiv-cs-cv

arXiv:2603.13108v2 Announce Type: replace-cross Abstract: Panoramic imagery provides holistic 360{eg} visual coverage for environmental perception in quadruped robots. However, existing occupancy pred

PCAE: Learning Ordered Representations in Latent Space for Intrinsic Dimension Estimation via Principal Component Autoencoder

arXiv:2601.19179v2 Announce Type: replace Abstract: Autoencoders have long been considered a nonlinear extension of Principal Component Analysis (PCA). Prior studies have demonstrated that linear auto

researcharxiv-cs-lg

People Are Not Just Their Countries. Disentangling Social Determinants of LLM Value Alignment Across Europe

arXiv:2608.07367v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly used as a primary source of information and advice, understanding their alignment to humans in terms of

Progress-Certified Reversible Simplex Supervision of Goal-Reaching Reinforcement Learning

arXiv:2601.19499v2 Announce Type: replace Abstract: Task completion is difficult to certify when state aggregation, model mismatch, and disturbances invalidate nominal RL transitions. We present a rev

safetyarxiv-cs-ro

Prune Once: Retraining-Free Task-Agnostic Pruning for Vision-Language Models

arXiv:2608.06901v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved remarkable generalization across diverse multimodal tasks through large-scale pre-training, yet their rapidl

Quantum Generative Diffusion Model: A Fully Quantum-Mechanical Model for Generating Quantum State Ensemble

arXiv:2401.07039v5 Announce Type: replace-cross Abstract: Mixed quantum states are the native description of many physically important quantum systems, making their generation a fundamental task in qu

researcharxiv-cs-lg

Applications

Recent advances in weakly supervised learning: New supervision paradigms, assumption relaxations, and practical solutions

arXiv:2608.06896v1 Announce Type: new Abstract: Deep learning has achieved great success in recent years thanks to the availability of high-quality, well-annotated training data. However, this require

applicationsarxiv-cs-lg