Search: “inference”

Learning Robust Visuomotor Policies via Dynamics Alignment

arXiv:2510.27114v2 Announce Type: replace-cross Abstract: Generative BC policies model expert action distributions well, but they do not explicitly reason about what scene a candidate action would pro

Learning to Assist: Collaborative VLAs for Implicit Human-Robot Collaboration

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DGX agent

arXiv:2606.12475v2 Announce Type: replace Abstract: Human-robot collaboration (HRC) combines the complementary strengths of humans and robots to improve task efficiency. However, many existing collabo

safetyarxiv-cs-ro

14 Oct 2026

Tutorials

LeHami: Symplectic Latent Dynamics for World Models

arXiv:2610.15267v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPAs) learn world models directly in latent space, but unconstrained autoregressive predictors may contract t

tutorialsarxiv-cs-lg

LensErase: A Foundation Model for Erase Anything

arXiv:2610.18072v1 Announce Type: new Abstract: We introduce LensErase, a general-purpose mask-based Erase Anything foundation model designed to cover a broad spectrum of real-world erase scenarios. L

applicationsarxiv-cs-cv

Less is More: Label-Guided Efficient Summarization of Procedural and Instructional Videos

arXiv:2601.12243v3 Announce Type: replace Abstract: Video summarization transforms long videos into concise representations that are easier to document and analyze, especially in high-stakes domains s

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Listen Before Act: Audio-Conditioned Robot Manipulation with ListenVLA

model-releasesarxiv-cs-ro

arXiv:2610.16313v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced robotic manipulation by connecting visual perception and language instructions to action generation. H

LLM2R: From Large Language Models to 3D Reassemblers

arXiv:2610.18604v1 Announce Type: new Abstract: 3D part assembly aims to reconstruct a complete shape from a set of unassembled parts by predicting a rigid SE(3) transformation for each part. Because

Locomotion with Online Awareness of Dynamics for Precision Footholds

arXiv:2610.17930v1 Announce Type: new Abstract: Unknown payloads alter robot dynamics and make precise contact execution difficult when foothold margins are small. We present LOAD, a perceptive locomo

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Look Before You Move: Agent-Interface-Aligned Supervision for Open-World Mobile Manipulation

arXiv:2610.15572v1 Announce Type: new Abstract: Open-world mobile manipulation requires a robot to find an object, approach it, and move it to a target receptacle from a language instruction. Training

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LoRAtorio: An intrinsic approach to LoRA Skill Composition

arXiv:2508.11624v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has become a widely adopted technique in text-to-image diffusion models, enabling the personalisation of visual concepts

Measure Neural Mappings

arXiv:2610.17384v1 Announce Type: new Abstract: We introduce and define measure neural mappings (MNMs), which combine measure-dependent neural transport with ensemble consistency for learning operator

Agents

MemAct: Streaming Spatial Understanding with Memory and Active Exploration

arXiv:2610.17640v1 Announce Type: new Abstract: Spatial understanding is essential for embodied agents navigating and interacting with the physical world. As observations arrive incrementally, agents

agentsarxiv-cs-cv

Meta-Video: Efficient Standardized Evaluation for Video Understanding

model-releasesarxiv-cs-cv

arXiv:2610.18535v1 Announce Type: new Abstract: Video understanding benchmarks are the primary yardstick for measuring progress in video-language modeling, and a growing body of work relies on them to

microsoft/UserRepGen-4B

https://preview.redd.it/gwb4of5vmivh1.png?width=2400&format=png&auto=webp&s=853f4cf25b4140ccf8b151b4124547788a544b33 UserRepGen-4B is a fine-tuned Qwen3.5-4B language model that generates a structured

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MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs

arXiv:2508.21044v2 Announce Type: replace Abstract: Video Large Language Models (VLLMs) excel in video understanding, but their excessive visual tokens pose a significant computational challenge for r

applicationsarxiv-cs-cv

MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision

arXiv:2610.17856v1 Announce Type: new Abstract: Time-series analysis is increasingly studied in multimodal settings, yet most benchmarks pair temporal signals with text or with visualizations derived

Tutorials

MORE: Learning Motion-Oriented Registers for Driving World Models and Planning

arXiv:2610.14871v1 Announce Type: new Abstract: By predicting future states, latent world models provide rich self-supervision for end-to-end driving, but often inherit dense features from pretrained

tutorialsarxiv-cs-cv

Multics: Generative Multi-Player World Model with Hierarchical Communication

arXiv:2610.17201v1 Announce Type: new Abstract: Multi-player interactive world models aim to simulate shared environments from multiple players' perspectives, but achieving robust generation while sca

local-aiarxiv-cs-cv

Neural Evidence and Behavioural Welfare Economics: When Can Neuroeconomics Inform Policy?

arXiv:2511.19548v2 Announce Type: replace Abstract: Neuroeconomics appears to offer welfare economics an evidential supplement, since neural data may help distinguish choices that express genuine pref

Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation

arXiv:2610.14162v1 Announce Type: cross Abstract: Diffusion language models (DLMs) offer parallel sampling for faster generation than autoregressive models, an increasingly important advantage as infe

NoduleFlow: Automatic 3D Lung Nodule Detection and Segmentation

arXiv:2610.16548v1 Announce Type: new Abstract: Low dose Computed Tomography (CT) is the standard imaging modality for lung cancer screening. On CT scans, lung cancer typically manifests as pulmonary

local-aiarxiv-cs-cv

Omni-Modal LLMs Know More Than They Say

arXiv:2610.16135v1 Announce Type: cross Abstract: Omni-modal large language models (Omni-LLMs) extend LLMs to process heterogeneous modalities (e.g., vision, audio, and IMU signals) alongside language

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On Generalizing Preference-based Reinforcement Learning to Multi-Objective Problems

arXiv:2607.11432v2 Announce Type: replace Abstract: We study reinforcement learning (RL) from pairwise human-generated trajectory comparisons. We generalize preference-based RL by formalizing a novel

One-Way Coupling via Patchwise Adaptive Normalization in Transformer Surrogates

arXiv:2610.14687v1 Announce Type: new Abstract: Many physical systems exhibit one-way coupling: exogenous fields such as medium density or obstacle geometry influence the dynamics without being affect

Online LLM Personalization from Pairwise Preferences Across Users

arXiv:2610.17203v1 Announce Type: new Abstract: Large language models can answer the same question in different styles, but users' preferred styles are hidden and vary across users and questions. We s

Only What You've Signed up For: Secure Workflows with Constrained Diffusion Agents

arXiv:2610.15177v1 Announce Type: new Abstract: As agentic AI systems take on increasingly complex and consequential tasks, securing them against prompt injection becomes critical. Existing defenses o

P-BFM: Perceptive Behavioral Foundation Models for Humanoid Control via Unsupervised Reinforcement Learning

arXiv:2610.15833v1 Announce Type: new Abstract: Behavioral foundation models (BFMs) provide humanoids with reusable repertoires of whole-body behaviors; in real-world humanoid control, the same behavi

local-aiarxiv-cs-ro

PanoLAM: Large Avatar Model for Gaussian Full-Head Synthesis from One-shot Unposed Image

arXiv:2509.07552v3 Announce Type: replace Abstract: We present a feed-forward framework for static Gaussian full-head reconstruction and novel-view rendering from a single unposed image. Unlike previo

PerturbBridge: Direct Phenotypic Supervision for Cellular Perturbation Generation

arXiv:2610.17066v1 Announce Type: new Abstract: Virtual cell models should capture phenotypes induced by specific perturbations. However, image-based models are typically trained and evaluated to matc

Pessimistic Latent Task-aware Optimization for Robust Offline Meta-Reinforcement Learning

arXiv:2610.15428v1 Announce Type: new Abstract: Context-based offline meta-reinforcement learning (COMRL) has advanced almost entirely through better task representations, which separate task identity

Physical SLAM: Physics-aware Simultaneous Localisation and Mapping

model-releasesarxiv-cs-ro

arXiv:2610.17260v1 Announce Type: new Abstract: To reconstruct a predictive 4D representation of the physical world from monocular video captured by a moving camera, we jointly reconstruct dynamic Gau

Physics-informed random neural architectures on compact boundaryless multiply connected manifolds for random-operator models in machine learning and uncertainty quantification

arXiv:2610.14844v1 Announce Type: cross Abstract: We introduce stochastic physics-informed neural networks (SPINNs) for stochastic boundary-value problems (SBVPs) with random operators. The method enf

PINT: A Unified Model with Shared Predictive Intent for Robot Manipulation

arXiv:2610.16355v1 Announce Type: new Abstract: Generalist robot manipulation can benefit from pretrained vision-language models (VLMs) for semantic reasoning and video generation models (VGMs) for wo

applicationsarxiv-cs-ro

PixARG: Pixel-Asynchronous Retrieval-Augmented Diffusion for Fast and Realistic Image Generation

arXiv:2610.14713v1 Announce Type: new Abstract: While diffusion models achieve impressive image generation capabilities, they suffer from high computational costs, implausible artifacts, and limited a

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Agents

Pixels or Code? Benchmarking Instruction-Guided Visual Artifact Operation

arXiv:2610.16444v1 Announce Type: new Abstract: Visual artifacts such as charts, technical diagrams, webpages, and document pages underpin scientific, commercial, and engineering workflows. Editing th

agentsarxiv-cs-cv

Tutorials

PixSearch: Region-Grounded Retrieval for Knowledgeable Large Multimodal Models

arXiv:2601.19060v2 Announce Type: replace Abstract: Multimodal Retrieval-Augmented Generation (MM-RAG) augments visual question answering (VQA) with external knowledge, but many systems rely on modula

tutorialsarxiv-cs-cv

PLAYGROUND: Progressive Layout Generation with Render-Grounded Planning

model-releasesarxiv-cs-cv

arXiv:2610.18865v1 Announce Type: new Abstract: Generating editable graphic designs requires arranging visual and textual elements into a coherent composition while preserving their content and editab

Plume Segmentation from MethaneSAT with Cross-Sensor Transfer Learning and Physics-Informed Postprocessing

arXiv:2605.24273v2 Announce Type: replace Abstract: Automated detection and masking of individual methane plumes from satellite imagery is important for operational emission attribution and quantifica

Posterior-Averaged Bellman Flow Matching for Distributional Critics

arXiv:2610.17788v1 Announce Type: new Abstract: Distributional critics model the full return distribution, providing richer signals for exploration and risk-sensitive control. Recent work has shown th

PreSO: Privileged Representation Isolation for On-Policy Self-Distillation

arXiv:2610.14001v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) uses a self-teacher conditioned on privileged information to turn the sparse outcome signal of reinforcement learning

PRISM: Calibrating Black-Box Judges with Counterfactual Probes

arXiv:2610.18389v1 Announce Type: new Abstract: Large language models are increasingly used as judges to reduce reliance on costly human evaluation, yet their scores can systematically disagree with h

local-aiarxiv-cs-lg

PRISM: Precision Forcing for Generalist Vision-Language-Action Policies

arXiv:2610.14704v1 Announce Type: new Abstract: Coupling a pretrained vision-language model (VLM) with a diffusion or flow-matching action expert has become the mainstream vision-language-action (VLA)

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Probabilistic Simulation of Gas-Liquid Interfaces with Coupled Flow Matching on Spherical Harmonics

arXiv:2610.16327v1 Announce Type: new Abstract: Bubbly flows involve strongly coupled bubble motion, deformation, and hydrodynamic interactions, making high-fidelity simulation computationally expensi

Prospective Forcing: Learning to Look Ahead for Autoregressive Long Video Diffusion

arXiv:2610.14654v1 Announce Type: new Abstract: Autoregressive video generators synthesize long videos through chunk-wise rollouts, yet they are typically trained to predict only the immediate future.

ProTok: Unified Protein Tokenization via Modular Multi-Codebook Quantization

arXiv:2610.18481v1 Announce Type: new Abstract: Protein sequence, structure, and functional annotations each capture complementary aspects of protein biology, yet existing tokenizers encode each modal

PVD-ONet: A Multi-scale Neural Operator Method for Singularly Perturbed Boundary Layer Problems

arXiv:2507.21437v3 Announce Type: replace Abstract: Physics-informed neural networks and physics-informed DeepONet excel at solving partial differential equations but often struggle with singularly pe

QASA: Quality-Guided K-Adaptive Slot Attention for Unsupervised Object-Centric Learning

arXiv:2601.12936v2 Announce Type: replace Abstract: Slot Attention, an approach that binds different objects in a scene to a set of 'slots', has become a leading method in unsupervised object-centric

applicationsarxiv-cs-cv

QK-Edit: Revisiting Attention-based Injection in MM-DiT for Image and Video Editing

arXiv:2610.17829v1 Announce Type: new Abstract: Multimodal Diffusion Transformers (MM-DiTs) have recently emerged as a powerful framework for unified text-vision synthesis, surpassing traditional U-Ne