Search: “inference”

One Scene, Two Depths: Probing Geometric Ambiguity in Monocular Foundation Models

arXiv:2606.29600v1 Announce Type: cross Abstract: A faithful 3D world representation should account for layered geometry, where a single camera ray may contain multiple visible and geometrically valid

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Model Releases

OSWorld2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks

DGX agent

arXiv:2606.29537v1 Announce Type: new Abstract: Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to

model-releasesarxiv-cs-ai

30 Jun 2026

RadarTwin: Scene-Specific mmWave Radar Simulation and Learning for Mobile Indoor Perception

arXiv:2606.28396v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar perception is limited by data scarcity: models trained on existing radar datasets fail to generalize to new objects, envi

RainODE: Continuous-Time Precipitation Forecasting with Latent Neural ODEs

arXiv:2606.29855v1 Announce Type: new Abstract: In precipitation forecasting, not only accuracy but also temporal resolution is critical. However, increasing temporal resolution is constrained by obse

Tools

Ray Data 2.56: Improving Reliability for AI Data Pipelines

Ray Data 2.56 introduces reliability improvements for AI data pipelines, likely including enhancements to data processing, fault tolerance, and stability features within the Ray distributed computing

toolsanyscale-ray

Applications

Real-time Rendering-based Surgical Instrument Tracking via Evolutionary Optimization

arXiv:2603.11404v3 Announce Type: replace-cross Abstract: Accurate and efficient tracking of surgical instruments is fundamental for Robot-Assisted Minimally Invasive Surgery. Although vision-based ro

applicationsarxiv-cs-cv

Real-Time Underwater Image Enhancement via Frequency-Guided Dual-Path Attention

arXiv:2606.30314v1 Announce Type: new Abstract: Real-time underwater image enhancement (UIE) is crucial for mobile underwater photography and autonomous robotic systems, where practical deployment typ

agentsarxiv-cs-cv

RefAlign: Representation Alignment for Reference-to-Video Generation

model-releasesarxiv-cs-cv

arXiv:2603.25743v2 Announce Type: replace Abstract: Reference-to-video (R2V) generation is a controllable video synthesis paradigm that constrains the generation process using both text prompts and re

REPAIR-Bench: A Benchmark for Robot Error Perception And Interaction Recovery

model-releasesarxiv-cs-ro

arXiv:2606.29937v1 Announce Type: new Abstract: Understanding how users perceive and respond to robot failures is essential for building robust and trustworthy robot systems. Prior work, however, (i)

RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources

arXiv:2606.29538v1 Announce Type: cross Abstract: Skills are a useful abstraction for software agents, turning human and agent experience into reusable procedural knowledge. Yet existing skill librari

agentsarxiv-cs-ai

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation

arXiv:2602.09305v2 Announce Type: replace Abstract: Large Language Models (LLMs) demonstrate transformative potential, yet their reasoning remains inconsistent and unreliable. Reinforcement learning (

safetyarxiv-cs-lg

Scene-aware Prediction of Diverse Human Movement Goals

arXiv:2606.29942v1 Announce Type: new Abstract: Anticipation of human behaviours facilitates autonomous systems in proactive planning. Human behaviour could be stochastic due to varying goals. Human g

agentsarxiv-cs-cv

See Only When Needed: Context-Aware Attention Intervention for Mitigating Hallucinations in LVLMs

arXiv:2606.29847v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) excel at multimodal tasks but remain prone to object hallucinations. Prior training-free remedies often uniformly s

Seeing Touch from Motion: A Unified Modality-Aware Visuo-Tactile Policy with Tactile Motion Correlation

arXiv:2606.29941v1 Announce Type: cross Abstract: Visuo-Tactile policies leveraging optical tactile sensors have shown great promise in contact-rich manipulation. These sensors achieve high spatial re

safetyarxiv-cs-cv

Self-Supervised Theorem Discovery in a Formal Axiomatic System

arXiv:2606.28747v1 Announce Type: new Abstract: Recent artificial intelligence (AI) systems have shown remarkable progress in mathematical reasoning. Many existing approaches, including large language

SkelEM: Training-Signal Decoupling of Skeleton and Diffusion for Self-supervised Axial Super-Resolution in Volume Microscopy

model-releasesarxiv-cs-cv

arXiv:2606.30012v1 Announce Type: new Abstract: Volume microscopy, including electron and light microscopy, suffers from severe anisotropic resolution due to physical axial sectioning. Existing self-s

SonoCLIP: Mask-Guided Region-Aware Vision-Language Pretraining for Fetal Ultrasound Analysis

arXiv:2606.29586v1 Announce Type: cross Abstract: Vision-language foundation models have shown strong potential in medical image analysis. Although foundation models for ultrasound imaging have recent

local-aiarxiv-cs-ai

Hardware

Spanning the Visual Analogy Space with a Weight Basis of LoRAs

arXiv:2602.15727v2 Announce Type: replace-cross Abstract: Visual analogy learning enables image editing via demonstration rather than textual description, allowing users to specify complex transformat

hardwarearxiv-cs-ai

Sparse Autoencoders are Capable LLM Jailbreak Mitigators

arXiv:2602.12418v2 Announce Type: replace-cross Abstract: Jailbreak attacks remain a persistent threat to large language model safety. We propose Context-Conditioned Delta Steering (CC-Delta), an SAE-

safetyarxiv-cs-cl

StereoGS: Sparse-View 3D Gaussian Splatting via Stereo Priors

arXiv:2606.30545v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has achieved remarkable success in real-time novel view synthesis, yet it suffers from severe overfitting under sparse-view

Stochastic and Non-local Closure Modeling for Nonlinear Dynamical Systems via Latent Score-based Generative Models

arXiv:2506.20771v2 Announce Type: replace Abstract: We propose a latent score-based generative AI framework for learning stochastic, non-local closure models and constitutive laws in nonlinear dynamic

local-aiarxiv-cs-lg

Synthetic Interaction Data for Scalable Personalization in Large Language Models

arXiv:2602.12394v2 Announce Type: replace Abstract: Personalized prompting offers large opportunities for deploying large language models (LLMs) to diverse users, yet existing prompt optimization meth

agentsarxiv-cs-lg

Tutorials

T2LDM++: A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generation

arXiv:2606.30147v1 Announce Type: new Abstract: Recent progress in Text-to-Image generation benefits from large-scale Text-Image pairs. However, the scarcity of Text-LiDAR pairs often causes over-smoo

tutorialsarxiv-cs-cv

Applications

T3R: Deeper Test-Time Adaptation for Graph Neural Networks via Gradient Rotation

arXiv:2606.30011v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) deployed in real-world systems typically have fixed weights, often leading to degraded performance under distribution shi

applicationsarxiv-cs-ai

TerraDiT: Point-Conditioned Diffusion Transformer for Satellite Image Synthesis

arXiv:2603.02172v2 Announce Type: replace Abstract: We introduce TerraDiT, a diffusion transformer designed for text-to-satellite image generation with point-based control. Existing controlled satelli

safetyarxiv-cs-cv

The Complexity Ceiling Benchmark: A Multi-Domain Evaluation of Sequential Reasoning Under Depth Scaling

arXiv:2606.29278v1 Announce Type: new Abstract: We introduce the Complexity Ceiling Benchmark (CCB), a controlled evaluation of how language-model reasoning decays as the number of required sequential

The CRISTAL Method: Neurosymbolic analysis from AI-synthesized world models

arXiv:2606.29799v1 Announce Type: new Abstract: This project introduces the CRISTAL Method (Coherent Reliable Intentional Synthesis of Truthful Analysis Logic), a neurosymbolic framework for automatin

The Hidden Cost of Structured Generation in LLMs: Draft-Conditioned Constrained Decoding

arXiv:2603.03305v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to generate executable outputs, JSON objects, and API calls, where a single syntax error ca

The Voronoi Bottleneck: Capacity-Aware Dense Retrieval for Product Search

arXiv:2606.28359v1 Announce Type: cross Abstract: Dense embedding retrieval compresses all relevance information into a single inner product, imposing a fundamental geometric limit -- the Voronoi Bott

researcharxiv-cs-lg

Thrilled to announce the Wearable AI Workshop at ECCV 2026 🎉 that we're organizing with an awesome group of folks across Meta Reality Labs,…

model-releasesyann-lecun--x

Thrilled to announce the Wearable AI Workshop at ECCV 2026 🎉 that we're organizing with an awesome group of folks across Meta Reality Labs, AMI Labs, HKUST, Georgia Tech, UCF, and U. of Edinburgh. If

Hardware

TokenBudgeting: Our Conversations with Enterprises on Token Spend

TokenBudgeting examines enterprise spending patterns and cost management strategies related to AI token consumption, based on SemiAnalysis's direct conversations with corporate customers. The analysis

hardwaresemianalysis

Toward Secure and Reliable PDDL Formalization of Large Language Models with Planner-in-the-Loop Feedback

arXiv:2606.29700v1 Announce Type: new Abstract: Planning often requires symbolic specifications that are both executable and verifiable. For large language models deployed in autonomous or decision-su

Towards Continual Motion-Language Agents: LoRA Variants for Incremental Motion Understanding and Generation

arXiv:2606.30266v1 Announce Type: cross Abstract: Motion-language agents must possess the bidirectional capability to both understand human movement (motion-to-text, M2T) and generate it from natural

Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks

arXiv:2504.17421v2 Announce Type: replace-cross Abstract: Large language models (LMs) offer broad generalization capabilities but require vast amounts of data and computational resources for domain-sp

researcharxiv-cs-ai

Training Vision-Language-Action Models with Dense Embodied Chain-of-Thought Supervision

model-releasesarxiv-cs-cv

arXiv:2606.30552v1 Announce Type: cross Abstract: Cross-embodiment transfer in vision-language-action (VLA) models remains challenging because low-level state and action spaces differ fundamentally ac

Transformer Architectures as Complete Bayes Processes: A Formal Proof in the Measure-Theoretic Kernel Framework

arXiv:2606.30440v1 Announce Type: cross Abstract: We present a complete formal proof that transformer architectures, when their internal update mechanisms satisfy a Bayes joint-distribution condition,

researcharxiv-cs-ai

Transition-Aware best-of-N sampling for Longitudinal Chest X-ray Reports

arXiv:2606.28393v1 Announce Type: new Abstract: In longitudinal clinical practice, every chest X-ray is read in the context of the patients prior exam, and much of what the radiologist communicates is

Hardware

Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries

arXiv:2602.04940v2 Announce Type: replace Abstract: Deep learning has emerged as a transformative tool for the neural surrogate modeling of partial differential equations (PDEs), known as neural PDE s

hardwarearxiv-cs-lg

Two kinds of robustness are not the same: disentangling fault tolerance and low-SNR robustness in multi-domain event detection on real data

model-releasesarxiv-cs-lg

arXiv:2606.29339v1 Announce Type: cross Abstract: Reliable event detection underpins induced-seismicity monitoring for Carbon dioxide Capture and Storage (CCS) and geothermal operations, distributed a

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention

arXiv:2510.16325v3 Announce Type: replace Abstract: Ultra-high-resolution text-to-image generation is increasingly vital for applications requiring fine-grained textures and global structural fidelity

Understanding Evaluation Illusion in Diffusion Large Language Models

arXiv:2606.29228v1 Announce Type: new Abstract: Despite the capability of parallel decoding, diffusion large language models (dLLMs) require many denoising steps to maintain generation quality, motiva

researcharxiv-cs-cl

UniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation

arXiv:2603.22282v2 Announce Type: replace-cross Abstract: We present UniMotion, to our knowledge the first unified framework for simultaneous understanding and generation of human motion, natural lang

safetyarxiv-cs-ai

UniVAD v2: Unified Visual Anomaly Detection via Support-Conditioned Boundary Construction

arXiv:2606.29714v1 Announce Type: new Abstract: Unified visual anomaly detection seeks to train a single detector that can be deployed across categories, domains, and application scenarios. In the few

Vision-Language-Action Models: Experimental Insights from a Real-World UR5 Platform

arXiv:2606.30456v1 Announce Type: cross Abstract: This project investigates whether recent Vision-Language-Action (VLA) models can be transferred from controlled research benchmarks to a real-world ro

safetyarxiv-cs-cv

VisReflect: Latent Visual Reflection for Fine-Grained Perception in Long Visual Context

arXiv:2606.30288v1 Announce Type: new Abstract: Large Vision Language Models (LVLMs) have achieved remarkable success on vision-language tasks, yet fine-grained perception over high-resolution images

Walking in the Implicit: Interactive World Exploration via Neural Scene Representation

arXiv:2606.30045v1 Announce Type: new Abstract: Interactive video generation systems for camera-controlled world exploration roll out growing sequences of latent video frames, entangling state transit

Tools

We heard your feedback. You want to go faster. Introducing GLM 5.2 Fast The same model and quality as GLM 5.2 standard, now at 140 tok/s Fli…

Fireworks AI announced GLM 5.2 Fast, an optimized version of their GLM 5.2 model that maintains the same quality and capabilities as the standard version while delivering significantly faster inferenc

toolsfireworks-ai--x

We're coming out of stealth. We've built our first racks after a successful A0 tapeout, 1B+ in customer contracts, and 800m raised. Early …

We're coming out of stealth. We've built our first racks after a successful A0 tapeout, 1B+ in customer contracts, and 800m raised. Early customer tests show us achieving SOTA throughput, latency, and

researchkarpathy--x