Search: “framework”

RoadBench: Benchmarking MLLMs on Fine-Grained Spatial Understanding and Reasoning under Urban Road Scenarios

arXiv:2511.18011v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have demonstrated powerful capabilities in general spatial understanding and reasoning. However, their fine

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Robust 3D Alignment of Generative Reconstructions via Partial Monocular Observations

DGX agent

arXiv:2607.00498v1 Announce Type: new Abstract: Aligning generative 3D reconstructions with partial monocular observations is a critical but under-explored challenge in computer vision. This task is i

model-releasesarxiv-cs-cv

2 Jul 2026

Robust Operational Space Control with Conformal Disturbance Bounds for Safe Redundant Manipulation

arXiv:2607.00424v1 Announce Type: new Abstract: Redundant robotic manipulators operating in constrained and human-interactive environments require accurate task-space tracking together with rigorous s

safetyarxiv-cs-ro

Rosetta: Composable Native Multimodal Pretraining

arXiv:2607.00293v1 Announce Type: cross Abstract: Achieving true artificial general intelligence requires foundation models capable of integrating new modalities without forgetting prior knowledge. Ho

researcharxiv-cs-cl

SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport

model-releasesarxiv-cs-lg

arXiv:2607.00377v1 Announce Type: new Abstract: Self-supervised Continual Graph Learning (CGL) aims to successively learn from a graph sequence with different tasks without label supervision - a parad

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction

arXiv:2607.00008v1 Announce Type: cross Abstract: Extracting structured data from unstructured text using large language models (LLMs) becomes challenging when target schemas are large and complex. In

applicationsarxiv-cs-ai

Search-Based Spatiotemporal and Multi-Robot Motion Planning on Graphs of Space-Time Convex Sets

arXiv:2607.00444v1 Announce Type: cross Abstract: Spatiotemporal motion planning, especially in multi-robot settings, requires robots to reason about collision-free regions that change over time, whic

Segmenting, Fast and Slow: Real-Time Open-Vocabulary Video Instance Segmentation with Dual-Path Processing

arXiv:2607.00124v1 Announce Type: new Abstract: Object-centric models inspired by DETR have become the dominant paradigm for open-vocabulary video instance segmentation (OV-VIS). While recent efforts

local-aiarxiv-cs-cv

Selective Expert Guidance for Effective and Diverse Exploration in Reinforcement Learning of LLMs

arXiv:2510.04140v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a widely adopted technique for enhancing the reasoning ability of Large Language Mo

safetyarxiv-cs-ai

Selective Test-Time Debiasing for CLIP via Reward Gating

arXiv:2607.00423v1 Announce Type: new Abstract: Vision language models (VLMs) demonstrate strong zero-shot performance, but often perpetuate social stereotypes in person-centric queries, yielding skew

safetyarxiv-cs-cl

Semi-Bandit Learning for Monotone Stochastic Optimization

arXiv:2312.15427v3 Announce Type: replace Abstract: Stochastic optimization is a widely used approach for optimization under uncertainty, where uncertain input parameters are modeled by random variabl

safetyarxiv-cs-lg

Hardware

SNAP-FM: Sparse Nonlinear Accelerated Projection for Physics-Constrained Generative Modeling

arXiv:2607.00095v1 Announce Type: cross Abstract: Generative models have emerged as scalable surrogates for physical simulation, yet they offer no guarantee that their outputs respect the conservation

hardwarearxiv-cs-ai

SoK: Attack and Defense Landscape of Mobile On-device AI Systems

arXiv:2607.00362v1 Announce Type: cross Abstract: Mobile on-device AI (MoAI) systems that integrate locally deployed AI models with conventional mobile software components are emerging as a key paradi

local-aiarxiv-cs-ai

Solution space path planning for supporting en-route air traffic control

arXiv:2607.00064v1 Announce Type: new Abstract: As technology advances, many path-planning algorithms have been proposed for Air Traffic Management, yet their operational adoption in tactical control

Spectral and Trajectory Regularization for Diffusion Transformer Super-Resolution

arXiv:2603.06275v2 Announce Type: replace Abstract: Diffusion transformer (DiT) architectures show great potential for real-world image super-resolution (Real-ISR). However, their computationally expe

Spectral Geometry and Bosonic-Bloch Probes: Explorations in Quantum Learning

arXiv:2607.00063v1 Announce Type: cross Abstract: This paper studies how spectral geometry emerges in quantum learning models and how it can be diagnosed with physically grounded probes. In graph-regu

Spotted: Location-informed Reidentification of Hyenas and Leopards in Camera Trap Surveys

arXiv:2607.00804v1 Announce Type: new Abstract: Animal re-identification (ReID) in camera-trap surveys remains challenging due to low image quality, strong variation in illumination and viewpoint, and

researcharxiv-cs-cv

StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting

arXiv:2607.00197v1 Announce Type: new Abstract: Long-horizon multivariate time series forecasting (LTSF) remains challenging due to non-stationarity, regime shifts, and error accumulation. The Variabi

local-aiarxiv-cs-lg

Stateful Token Reduction for Long-Video Hybrid VLMs

arXiv:2603.00198v2 Announce Type: replace-cross Abstract: Token reduction accelerates long-video vision--language models (VLMs), but existing methods target Transformers, where reduction is treated as

Stitched Embeddings: A Unified Latent Space for 3D Garments and 2D Patterns

arXiv:2607.00829v1 Announce Type: new Abstract: While garments are essential for realistic digital humans, their topological variety makes them much harder to model than parametric bodies. Traditional

applicationsarxiv-cs-cv

SuperFlex: Deformable Superquadrics for Point Cloud Decomposition

arXiv:2607.01015v1 Announce Type: new Abstract: Superquadrics have proven to provide a compact, geometrically meaningful representation for 3D objects. However, existing methods suffer from limited re

applicationsarxiv-cs-cv

TCMA: Text-Conditioned Multi-granularity Alignment for Drone Cross-Modal Text-Video Retrieval

arXiv:2510.10180v2 Announce Type: replace Abstract: Unmanned aerial vehicles (UAVs) have become powerful platforms for real-time, high-resolution data collection, producing massive volumes of aerial v

TerraBench: Can Agents Reason Over Heterogeneous Earth-System Data?

arXiv:2606.13148v2 Announce Type: replace Abstract: Climate and environmental decision-making increasingly requires reasoning across heterogeneous inputs, including gridded physical data, satellite im

TetraSDF: Analytic Isosurface Extraction with Multi-resolution Tetrahedral Grid

arXiv:2511.16273v2 Announce Type: replace Abstract: Extracting an explicit surface that exactly matches the zero-level set of a neural signed distance function (SDF) remains challenging. Sampling-base

safetyarxiv-cs-cv

This is a very bold letter from Maria Ressa and Bengio! It is historic to see the chairs of the UN Independent International Scientific Pane…

Maria Ressa and Yann Bengio, prominent figures in technology and AI governance, co-authored a significant letter addressing concerns related to the UN Independent International Scientific Panel on AI.

safetygary-marcus--x

Towards High-Resolution Visual Perception via Hierarchical Entity Exploration

arXiv:2607.00816v1 Announce Type: new Abstract: High-resolution (HR) image perception remains a key challenge in multimodal large language models (MLLMs), as fine-grained details are often lost when t

Towards Memory-Efficient Autoregressive Video Generation via Instance-Specific Parametric Absorption

arXiv:2607.00712v1 Announce Type: new Abstract: Autoregressive (AR) streaming models have emerged as a powerful paradigm for long video generation. However, the linearly growing Key-Value (KV) cache p

local-aiarxiv-cs-cv

Towards Metric-Agnostic Trajectory Forecasting

arXiv:2607.01133v1 Announce Type: new Abstract: Accurate trajectory forecasting of surrounding traffic participants is a core capability for autonomous driving, enabling vehicles to anticipate behavio

Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization

arXiv:2607.00817v1 Announce Type: new Abstract: Text-to-image diffusion models achieve impressive visual quality, yet demographic bias remains a challenge, as neutral prompts consistently produce ster

safetyarxiv-cs-cv

Trust the Prior (or Not): Uncertainty-Aware Abdominal Aortic Aneurysm Segmentation

arXiv:2607.00201v1 Announce Type: new Abstract: Robust segmentation of intraluminal thrombus is critical for risk assessment in Abdominal Aortic Aneurysm, yet it remains challenging due to heterogeneo

researcharxiv-cs-cv

Understanding Why Language Models Hallucinate: Testing Reasoning Against Priors

arXiv:2607.00447v1 Announce Type: new Abstract: Large language models often produce hallucinated answers that violate prompt-level constraints. A key diagnostic question is whether these failures refl

safetyarxiv-cs-cl

Universal Image Immunization against Diffusion-based Image Editing via Semantic Injection

arXiv:2602.14679v2 Announce Type: replace Abstract: Diffusion model advances have enabled powerful text-guided image editing, but also raise ethical and legal risks such as deepfakes and unauthorized

applicationsarxiv-cs-cv

Unleashing More Actions via Action Compositional Training for VLA Models

arXiv:2607.00351v1 Announce Type: new Abstract: Vision-Language-Action models excel at robotic manipulation, driven by the scale and diversity of demonstration data. However, standard training paradig

safetyarxiv-cs-ro

Validating Causal Abstraction Metrics on Simulated Complex Systems

arXiv:2607.00267v1 Announce Type: cross Abstract: A central goal of science is to produce valid explanations of complex systems: high-level causal accounts that faithfully reflect the behavior of lowe

Agents

VLM-AR3L: Vision-Language Models for Absolute and Relative Rewards in Reinforcement Learning

arXiv:2607.00483v1 Announce Type: new Abstract: Designing effective reward functions remains a major challenge in reinforcement learning (RL), particularly in open-ended environments where task goals

agentsarxiv-cs-ro

Wake up for Touch! Mask-isolated Tactile Alignment Learning in MLLMs

arXiv:2607.00302v1 Announce Type: new Abstract: Touch supplies the physical grounding needed to perceive intrinsic material properties, such as friction and compliance, that vision alone often cannot

When Classic Cache Policies Fail: Learning-Augmented Replacement for Semantic Retrieval Buffers

arXiv:2607.00394v1 Announce Type: cross Abstract: LLM agents increasingly rely on retrieval buffers to store and reuse past experience, yet the cache management policies governing these buffers remain

researcharxiv-cs-cl

XSkill: Continual Learning from Experience and Skills in Multimodal Agents

arXiv:2603.12056v3 Announce Type: replace Abstract: Multimodal agents can now tackle complex reasoning tasks with diverse tools, yet they still suffer from inefficient tool use and inflexible orchestr

Zero-Shot Distracted Driver Detection via Vision Language Models with Double Decoupling

arXiv:2601.08467v2 Announce Type: replace Abstract: Distracted driving is a major cause of traffic collisions, calling for robust and scalable detection methods. Vision-language models (VLMs) enable s

safetyarxiv-cs-cv

3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance

arXiv:2606.31329v1 Announce Type: cross Abstract: Hierarchical Vision-Language-Action (VLA) models decouple high-level planning from low-level control to improve generalization in robot manipulation.

safetyarxiv-cs-ai

A Scalable Whole-body Motion Transfer via Implicit Kinodynamic Motion Retargeting

arXiv:2509.15443v2 Announce Type: replace-cross Abstract: Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abun

safetyarxiv-cs-ai

A Semantic-Layer-Mediated Agent for Natural Language to SQL over Heterogeneous Enterprise Databases

model-releasesarxiv-cs-cl

arXiv:2606.31041v1 Announce Type: new Abstract: Natural language-to-SQL (NL2SQL) over real-world enterprise databases remains significantly more challenging than on academic benchmarks. Enterprise sch

Absorption-Feature-Guided Distance-Decoupled Estimation and Band Selection for LWIR Hyperspectral Passive Ranging

arXiv:2606.31824v1 Announce Type: new Abstract: Long-wave infrared (LWIR) hyperspectral observations contain distance-dependent atmospheric absorption signatures, providing a physical basis for long-r

Agentic RAG-VLM: Affordance-Aware Retrieval-Augmented Generation with Self-Reflective Planning for Robotic Grasping

arXiv:2606.31200v1 Announce Type: new Abstract: Generalizable robotic grasping in cluttered environments is essential for deploying manipulators in unstructured human spaces, yet existing VLM-based me

Hardware

AgRefactor: Self-Evolving Agentic Workflow for HLS Compatibility and Performance

arXiv:2606.30949v1 Announce Type: new Abstract: High-Level Synthesis (HLS) provides a fast path from concepts to silicon, but converting real-world software into synthesizable HLS code remains challen

hardwarearxiv-cs-ai

AI Transparency: Governance Compliance or Stakeholder Requirements?

arXiv:2606.30652v1 Announce Type: cross Abstract: Transparency is increasingly mandated for public-sector AI systems, with organisations required to publish statements describing their AI use and over

AION: Aerial Indoor Object-Goal Navigation Using Dual-Policy Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2601.15614v3 Announce Type: replace Abstract: Object-Goal Navigation (ObjectNav) requires an agent to autonomously explore an unknown environment and navigate toward target objects specified by

ALM2Vec: Learning Audio Embeddings for Universal Audio Retrieval with Large Audio-Language Models

arXiv:2606.30682v1 Announce Type: cross Abstract: Recent advances in language--audio retrieval have been largely driven by contrastive dual-encoder architectures that align audio and text in a shared