Search: “framework”

Geometric Similarity in VLM Low-Level Vision Representations

arXiv:2610.00848v1 Announce Type: cross Abstract: Vision-language models (VLMs) have emerged as powerful candidates for universal vision backbones, with representative architectures including autoregr

Gestalt: Large Multimodal Interplay Model

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2610.00576v1 Announce Type: new Abstract: In this paper, we propose Gestalt, a new paradigm of large multimodal model built around multimodal interplay. Despite rapid advances, large multimodal

safetyarxiv-cs-cv

2 Oct 2026

GIFTBench: Diagnosing Generalization in Image Forgery Localization and Informing Model Design

model-releasesarxiv-cs-cv

arXiv:2610.01778v1 Announce Type: new Abstract: Reliable evaluation of image forgery localization (IFL) requires assessing models under diverse distribution changes, yet existing benchmarks often cove

GlassGuard: Verified Glass Plane Mapping for Robot Navigation

arXiv:2610.02110v1 Announce Type: new Abstract: Transparent and specular surfaces pose a serious challenge to LiDAR-based SLAM and navigation because laser returns may pass through glass, leaving coll

applicationsarxiv-cs-ro

Gradient-Aligned Pair Selection for Personalized Preference Optimization

arXiv:2610.00061v1 Announce Type: new Abstract: Personalizing large language models (LLMs) requires aligning generation behavior with user-specific preferences rather than aggregate quality. While Dir

Harnessing Vision-Language Models for Perceptual Quality Assessment and Autonomous Content Adjustment in Augmented Reality

model-releasesarxiv-cs-cv

arXiv:2610.00677v1 Announce Type: new Abstract: Advancements in augmented reality (AR) continue to foster innovative solutions, facilitating novel methodologies within educational systems, healthcare

HHR: Hierarchical Hash Retrieval for Efficient LLM Generation

arXiv:2610.01230v1 Announce Type: new Abstract: Efficient long-context inference is essential for large language models (LLMs), yet it poses a severe computational bottleneck. Hash-based retrieval off

Higher-Order Molecular Grammars for Generative and Foundation Models in Chemistry

arXiv:2610.02186v1 Announce Type: cross Abstract: Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly

Higher-Order Positional Encodings for Graph Representation Learning

arXiv:2610.01903v1 Announce Type: new Abstract: Many real-world systems exhibit higher-order interactions among groups of entities that cannot be captured by pairwise relationships alone. Graph Transf

applicationsarxiv-cs-lg

HiPhy: Hierarchical Alignment for Physically-Plausible Multi-Principle Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.02197v1 Announce Type: new Abstract: Video generation models have achieved remarkable visual fidelity and have strong potential to become general-purpose world simulators. Despite this prog

How Much Can Language Models Gain from Test-Time Computation?

model-releasesarxiv-cs-lg

arXiv:2610.01110v1 Announce Type: new Abstract: How much can test-time computation improve a language model, and at what cost? Test-time scaling is widely proposed as a substitute for larger models, b

HumanoidTTT: Test-Time Capability Reuse for Efficient Humanoid Control

arXiv:2610.00198v1 Announce Type: new Abstract: Recent advances in motion generation and whole-body tracking have enabled humanoid robots to execute increasingly diverse motions, yet the same motion c

researcharxiv-cs-ro

iADD: Improving Alignment and Diversity in Diffusion Policy Optimization

arXiv:2610.01789v1 Announce Type: cross Abstract: Reinforcement learning based post training of diffusion models, such as Denoising Diffusion Policy Optimization (DDPO), optimizes a reverse diffusion

Improving Math Reasoning through Value-guided Informative Search

arXiv:2610.01080v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has substantially improved the mathematical reasoning capabilities of large language models. Recen

Incident-Arena: Getting agents to the last nine of reliability

arXiv:2610.00648v1 Announce Type: new Abstract: AI coding agents are ubiquitous in engineering workflows amongst industry and academia. Yet, despite their use in app coding, relatively less attention

Increasing Width Allows Greedy Layer-wise Training to Rival End-to-End Backpropagation in Self-Supervised Learning

arXiv:2610.00753v1 Announce Type: cross Abstract: End-to-end backpropagation has been the dominant mode of training in deep learning, allowing for the coordination of parameter updates across layers o

IndoorBEV: A Lightweight Real-Time LiDAR BEV Perception System for Indoor Mobile Robots

arXiv:2610.00355v1 Announce Type: new Abstract: Efficient indoor LiDAR perception is challenging because mobile robots must understand cluttered three-dimensional environments under strict latency and

local-aiarxiv-cs-ro

Is Success All You Need? Investigating the Impact of Input Perturbations on VLA Behaviour in Tabletop Manipulation Tasks

model-releasesarxiv-cs-ro

arXiv:2610.01351v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have achieved high task success rates on robot manipulation task benchmarks. More recently, there has been an emphas

iSEE: Object Permanence Through Self-Supervision

arXiv:2610.01201v1 Announce Type: new Abstract: Object permanence, keeping track of an object's identity and position while it is occluded, is central to video representations that track, predict and

local-aiarxiv-cs-cv

ITC-MoE: Importance-guided Token-aware Compression for MoE Diffusion Language Models

arXiv:2610.01296v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) Diffusion Language Models (DLMs) offer flexible parallel decoding and increased model capacity, but their large number of exper

Iterative Policy Refinement through Semantic Rollout Analysis

arXiv:2610.01652v1 Announce Type: cross Abstract: Structured policies improve efficiency, robustness, and interpretability in imitation learning by introducing task-specific inductive bias, but existi

Kernelized Activation Steering

arXiv:2610.01062v1 Announce Type: new Abstract: Activation steering provides a simple, training-free mechanism for controlling attributes of generative models such as sentiment, style, and helpfulness

Kinematic MeanFlow: One-Step Action Generation Policy for Robotic Foundation Models

arXiv:2610.00864v1 Announce Type: cross Abstract: In this paper, we study how to achieve one-step action generation in Robotic Foundation Models (RFMs), aiming to overcome the high inference latency o

Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models

arXiv:2603.16065v3 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has shown strong potential for improving robotic manipulation policies, yet its practical use remains bottlenecked

Latent-Foresight: End-to-End Learning Predictable Representations for Latent World Models

arXiv:2610.01942v1 Announce Type: new Abstract: Predicting the future evolution of a scene is a fundamental capability for world modeling. Recent work has shown that operating in the feature space of

researcharxiv-cs-cv

Latent JEPA: Abstract Future Prediction for Latent Reasoning in Chemistry

arXiv:2610.01947v1 Announce Type: new Abstract: Large language models offer a promising foundation for chemical reasoning, bringing together chemical knowledge and multistep problem solving. Chemical

Tutorials

Learning to Ask: Information Acquisition for SLM-LLM Collaboration, under a budget

arXiv:2610.01236v1 Announce Type: new Abstract: Collaboration between a small language model (SLM) and a large language model (LLM) offers an opportunity to combine the efficiency of smaller models wi

tutorialsarxiv-cs-ai

Learning to Sell: Reinforcement Learning for Strategic Large Language Model Agents in Multi-Product Markets

arXiv:2609.33289v2 Announce Type: replace Abstract: Autonomous large language model (LLM) agents operating in multi-product markets must make sequential decisions under information asymmetry and resou

LENS-GRF: Permutation-Invariant Lesion Evidence Network with Gated Residual Fusion for Acne Severity Grading and Multi-Rater Clinical Oracle Analysis

arXiv:2610.00294v1 Announce Type: cross Abstract: Automated acne severity grading requires both whole-face context and fine-grained lesion evidence. We propose LENS-GRF (Lesion Evidence Network with S

researcharxiv-cs-ai

Agents

LiteReality-Agent: An Agentic System for Interactable 3D Indoor Scene Reconstruction

arXiv:2610.01863v1 Announce Type: new Abstract: We present LiteReality-Agent, an agentic system for reconstructing real indoor environments as realistic, articulated, and simulation-ready 3D scenes fr

agentsarxiv-cs-cv

LLM-Assisted Discovery of Typed Semantic Links for Ontology Network Construction

arXiv:2610.01393v1 Announce Type: cross Abstract: Constructing typed, justified semantic links between ontologies is essential for enabling interoperability across heterogeneous and interdisciplinary

researcharxiv-cs-ai

Local Support Learning

arXiv:2610.02126v1 Announce Type: cross Abstract: We explore catastrophic forgetting in the context of large pre-trained models. By considering forgetting as a geometric problem in the input space of

MaPa: Text-driven Photorealistic Material Painting for 3D Shapes

arXiv:2404.17569v4 Announce Type: replace Abstract: This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to gene

researcharxiv-cs-cv

Mapping the RAG Landscape: A Four Axis Taxonomy of Efficiency, Defense, Interactivity, and Reasoning

arXiv:2610.01936v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable fluency across many tasks but remain limited by their static, parameter bound knowledge and th

MedVL-SAM2: A unified 3D medical vision-language model for multimodal reasoning and prompt-driven segmentation

arXiv:2601.09879v2 Announce Type: replace-cross Abstract: Recent progress in medical vision-language models (VLMs) has achieved strong performance on image-level text-centric tasks such as report gene

MEGA: Object-Level Mesh Extraction from 3D Gaussian Splatting via Spatial Visual Distillation

arXiv:2610.01707v1 Announce Type: new Abstract: Mesh extraction from 3D Gaussian Splatting (3DGS) aims to endow 3D Gaussians with accurate geometric structures, enabling explicit and precise 3D occupa

researcharxiv-cs-cv

Mem++: Non-Destructive Memory for Long-Term Organizational LLM Agents

arXiv:2610.02002v1 Announce Type: cross Abstract: Large Language Model (LLM) agents now take part in organizational work, where many authors record decisions across documents over months. Because a re

MiLoop: Selective Memory Propagation for Neural Combinatorial Optimization

arXiv:2610.01685v1 Announce Type: new Abstract: Constructive neural combinatorial optimization (NCO) has emerged as a promising paradigm that learns to construct solutions to combinatorial optimizatio

safetyarxiv-cs-lg

Model Merging via Data-Free Covariance Estimation

arXiv:2604.01329v2 Announce Type: replace Abstract: Model merging provides a way of cheaply combining individual models to produce a model that inherits each individual's capabilities. While some merg

Modeling The Object Representations Underlying Human Physical Reasoning

arXiv:2602.12486v2 Announce Type: replace-cross Abstract: Humans appear to represent objects when reasoning about physics with coarse, volumetric 'bodies' that smooth concavities, trading fine visual

MoLE: Mixture of Latent Experts for Complementary Visual Reasoning

arXiv:2610.01917v1 Announce Type: cross Abstract: Latent visual reasoning equips vision--language models with continuous intermediate states that can process visual evidence without explicit textual r

researcharxiv-cs-ai

MoRA: MoE Pruning via Router Bias Learning and Expert Approximation

model-releasesarxiv-cs-lg

arXiv:2610.00367v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable parameter scaling with limited per-token computation by activating only a small subset of experts for each token,

MOVE: Multimodal Open-world Verification and Expansion for Graph Learning

arXiv:2610.00268v1 Announce Type: new Abstract: Multimodal graph learning faces a fundamental challenge: new classes may emerge after deployment, while models are trained with a fixed label space. Exi

Multi-Jurisdictional Legal Identity Assurance for Capability Gating: A Design-Science Proposal for Tiered, Reusable Identity Assurance of Natural, Juridical, and Machine Entities

arXiv:2610.00287v1 Announce Type: cross Abstract: Identity assurance is the cost a digital system pays for dishonesty and uncertainty: it exists to make acts attributable when not everyone can be trus

applicationsarxiv-cs-ai

Multi-Task Anti-Causal Learning for Reconstructing Urban Events from Residents' Reports

arXiv:2603.11546v2 Announce Type: replace Abstract: Many real-world machine learning tasks are anti-causal: they require inferring latent causes from observed effects. In practice, we often face multi

applicationsarxiv-cs-lg

MVDG: Efficient Multi-view 3D Disambiguation on Unconstrained Real-World Images

arXiv:2610.01098v1 Announce Type: new Abstract: Illusory matches between distinct yet visually similar 3D surfaces--doppelgangers--remain a fundamental obstacle for large-scale, in-the-wild 3D reconst

local-aiarxiv-cs-cv

Neither Black nor White: Balancing Semantic and Collaborative Signals with Graph-Informed Semantic IDs (GrIS)

arXiv:2610.01533v1 Announce Type: new Abstract: Existing work on Semantic IDs (SIDs) for generative recommendation treats SID construction as a representation learning problem: encode items into a qua

applicationsarxiv-cs-ai

NextMe-800: Anticipating Personal Behavior from Months of Egocentric Video

arXiv:2610.01461v1 Announce Type: new Abstract: We often plan ambitiously yet act habitually and wonder, in retrospect, whether we would have planned differently had we known what we would actually do