Search: “models”

Couchbase Inc. is trying to solve one of the hardest problems in enterprise artificial intelligence today: turning brittle, chat-style pilots into production-grade agents capable of remembering, reaso

agentssiliconangle

Safety

CRAFT: Counterfactual Credit Assignment from Free Sibling Rollouts for Self-Distilled Agentic Reinforcement Learning

DGX agent

arXiv:2606.29476v1 Announce Type: cross Abstract: Self-distilled agentic reinforcement learning augments trajectory-level reward with a token-level distillation loss, using as its teacher the same pol

safetyarxiv-cs-ai

30 Jun 2026

Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policies

arXiv:2606.29898v1 Announce Type: cross Abstract: Real-world evaluation is the gold standard for robot policies because it tests them against the physical conditions and deployment challenges they are

Data-Efficient Multimodal Alignment for Histopathology-based Molecular Prediction

arXiv:2606.29949v1 Announce Type: cross Abstract: H&E-stained whole-slide images offer cohort-scale availability and rich spatial context but lack molecular specificity, whereas bulk RNA-seq provides

Dead-Direction Conditioners: Gauge-Equivariant Preconditioning for Deep Networks

arXiv:2606.29176v1 Announce Type: new Abstract: A deep network's loss is invariant to continuous symmetries of its parameters: the logit shift, the ReLU rescaling, the LayerNorm scale, the per-head at

Depth Exploration for LLM Decoding

arXiv:2606.29223v1 Announce Type: new Abstract: Autoregressive LLM decoding evaluates every generated token through the full layer stack, even though many tokens become predictable at intermediate dep

DivAS: Interactive 3D Segmentation by Depth-Weighted Voxel Aggregation

arXiv:2601.04860v2 Announce Type: replace Abstract: Interactive 3D segmentation of a reconstructed scene should not require a representation-specific optimization loop. We observe that the recipe for

DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks

arXiv:2503.09679v2 Announce Type: replace-cross Abstract: Meta-learning represents a strong class of approaches for solving few-shot learning tasks. Nonetheless, recent research suggests that simply p

Dual-Flow Reinforcement Learning with State-Aware Exploration

arXiv:2606.29820v1 Announce Type: cross Abstract: In complex continuous-control reinforcement learning tasks, multimodal optimal actions often coincide with uncertain, multimodal return distributions,

Efficient RGB-T Object Detection via Sparse Cross-Modality Fusion

arXiv:2606.30215v1 Announce Type: cross Abstract: RGB-T detectors leverage the complementary strengths of visible and thermal infrared modalities, achieving robust performance under challenging condit

Industry

Emad Mostaque on PostAGI: 'Right now, not a single institution is on your side. The companies won't look out for you, and the governments wo…

Emad Mostaque on PostAGI: 'Right now, not a single institution is on your side. The companies won't look out for you, and the governments won't either. Most of the AI debate just runs between those tw

industryemad-mostaque--x

Enhancing Layer Interaction Using Key-Correlated Layer Attention

arXiv:2606.28405v1 Announce Type: new Abstract: Recent advances in network architecture design have introduced layer attention to enhance inter-layer interactions. In such frameworks, each layer queri

EPIC-EuroParl-UdS: Information-Theoretic Perspectives on Translation and Interpreting

arXiv:2603.09785v3 Announce Type: replace Abstract: This paper introduces an updated and combined version of the bidirectional English-German EPIC-UdS (spoken) and EuroParl-UdS (written) corpora conta

safetyarxiv-cs-cl

EvLIR: Learning Illumination Residuals from Ordered Events for Low-Light Image Enhancement

arXiv:2606.29430v1 Announce Type: new Abstract: Low-light image enhancement is severely ill-posed when the input frame contains missing structure, saturated noise, and weak local contrast. Event camer

Industry

Excited to be working with MIXI in Japan as we continue to grow our partnership.

industrycristobal-valenzuela--x

Excited to be working with MIXI in Japan as we continue to grow our partnership. Today, we're announcing a strategic partnership with MIXI, one of Japan's largest gaming, sports and entertainment comp

FalconTrack: Photorealistic Auto-Labeled Perception and Physics-Aware Vision-Based Aerial Tracking

arXiv:2606.29783v1 Announce Type: cross Abstract: Vision-based aerial tracking is critical in GPS-denied environments. Reliable perception for tracking depends on large-scale labeled data, yet most ph

Hardware

Featuring the man of the moment @dylan522p @shaunmmaguire in today's Training Data episode. Nobody is a more trusted industry insider to the…

Featuring the man of the moment @dylan522p @shaunmmaguire in today's Training Data episode. Nobody is a more trusted industry insider to the biggest infrastructure build-out in history. The story of h

hardwaresonya-huang--x

FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images

arXiv:2606.30347v1 Announce Type: cross Abstract: We present FFAvatar, a Transformer-based 3D Gaussian framework for fast construction of high-quality and animatable 4D head avatars from one or more r

First-Order Temporal Logic Tensor Networks

arXiv:2606.29972v1 Announce Type: new Abstract: Most of the existing neuro-symbolic AI methods focus on the scenario of static knowledge where objects do not change according to a temporal dimension.

Fisher-Routed Mixture of Experts for Federated Class-Incremental Learning

arXiv:2606.28835v1 Announce Type: cross Abstract: Federated Learning (FL) emerged as a promising distributed machine learning paradigm. However, extending FL to the class incremental learning scenario

FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management

arXiv:2412.02831v2 Announce Type: replace-cross Abstract: The increasing accessibility of radiometric thermal imaging sensors for unmanned aerial vehicles (UAVs) offers significant potential for advan

Applications

FlexTab: A Flexible Encoder-Decoder Architecture for In-Context Learning Across Diverse Tabular Tasks

arXiv:2606.30336v1 Announce Type: new Abstract: We introduce FlexTab, a flexible encoder-decoder architecture for in-context learning on tabular data that pairs a single, task-agnostic encoder with a

applicationsarxiv-cs-lg

For even higher speeds, reach out for a custom deployment! We’ve hit 446 tok/s on Artificial Analysis. Learn more → https://fireworks.ai/blo…

Fireworks AI announced achieving 446 tokens per second throughput speeds as measured by Artificial Analysis benchmarks, positioning this as their standard performance metric. The company offers custom

tutorialsfireworks-ai--x

Industry

Ford CEO Jim Farley in new interview on Chinese EV competition: 'There's no real competition from Tesla, GM or Ford with what we've seen fro…

Ford CEO Jim Farley in new interview on Chinese EV competition: 'There's no real competition from Tesla, GM or Ford with what we've seen from China. They are completely dominating the EV landscape glo

industryelon-musk--x

Fourier Neural Operators with Least-Squares Readout Refit for Learning Random Obstacle-to-Solution Maps

arXiv:2606.29436v1 Announce Type: cross Abstract: We study operator learning for random obstacle-to-solution maps arising from elliptic variational inequalities with finite-band self-affine random obs

tutorialsarxiv-cs-lg

Frames2Residual: Spatiotemporal Decoupling for Self-Supervised Video Denoising

arXiv:2603.10417v2 Announce Type: replace Abstract: Self-supervised video denoising methods typically extend image-based frameworks into the temporal dimension, yet they often struggle to integrate in

From Local Windows to Adaptive Candidates via Individualized Exploratory: Rethinking Attention for Image Super-Resolution

arXiv:2601.08341v2 Announce Type: replace Abstract: Single Image Super-Resolution (SISR) is a fundamental computer vision task that aims to reconstruct a high-resolution (HR) image from a low-resoluti

From Phase to Phenomenon: Self-Supervised Learning of Subsurface Scattering with Minimal Phase-shift Inputs

arXiv:2606.29461v1 Announce Type: new Abstract: We propose a self-supervised pretraining framework for learning sub-surface scattering (SSS) light transport representations from minimal input. Our met

GarmentZoom: Generating Zoomable Images from Garment Listings

arXiv:2606.29535v1 Announce Type: new Abstract: Online product listings for garments often include an overview photo and a close-up to show garment details. However, each photo focuses on either field

safetyarxiv-cs-cv

Golden Hour Divide: Trauma Care Accessibility and Resource Vulnerability in Sri Lanka

arXiv:2606.29889v1 Announce Type: new Abstract: Timely intensive care dictates survival, yet emergency infrastructure remains unevenly distributed across Sri Lanka. While pre-hospital services have ex

safetyarxiv-cs-lg

Graph-GSReg: Leveraging 3D Scene Graphs for Gaussian Splatting Registration

arXiv:2606.29782v1 Announce Type: new Abstract: Merging multiple 3D Gaussian Splatting (3DGS) scenes into a single unified Gaussian representation is essential for large-scale 3D mapping and long-term

Harvesting AI Computation at the Edge via Generic Approximation

arXiv:2606.29518v1 Announce Type: cross Abstract: With the widespread adoption of AI in various IoT scenarios such as smart sensing and processing, AI chips have become a common component at the edge.

HASTE: A Framework for Training-Free, Dynamic, and Steerable Compression of Pre-Trained Convolutional Neural Networks

arXiv:2606.30516v1 Announce Type: new Abstract: Deploying large convolutional neural networks (CNNs) on resource-constrained devices is challenging due to their high computational cost. While dynamic

Heads, Not Backbones: Output Heads Dominate Architectures on Fat-Tailed Returns

arXiv:2606.30037v1 Announce Type: new Abstract: In a deep forecasting pipeline for fat-tailed financial returns at short horizons, which matters more - the backbone architecture or the output head? We

Hierarchical Policy Learning via Spectral Decomposition

arXiv:2606.29570v1 Announce Type: new Abstract: In this paper, we identify a semantic decomposition in robot action sequences, separating task-level motion intent from execution-level refinements. By

safetyarxiv-cs-ro

Hierarchical Reinforcement Learning in StarCraft Micromanagement with Influence Maps and Cluster-based Scripts

arXiv:2606.30092v1 Announce Type: new Abstract: Real-time strategy (RTS) games present significant AI challenges, characterized by expansive state-action spaces arising from multi-unit coordination in

HiReFF: High-Resolution Feedforward Human Reconstruction from Uncalibrated Sparse-View Video

arXiv:2606.29333v1 Announce Type: new Abstract: Uncalibrated volumetric video streaming for human reconstruction is essential for holographic communication and AR/VR, yet remains challenging due to th

HJ-SafeDMP: Hamilton-Jacobi Reachability-Guided Dynamic Movement Primitives for Provably Safe Robot Motion

arXiv:2606.28995v1 Announce Type: new Abstract: Robots deployed in safety-critical environments must execute motions that are simultaneously robust to disturbances and provably safe from collisions. D

safetyarxiv-cs-ro

How Anthropomorphic Language Impacts Public Perceptions of AI

arXiv:2606.29121v1 Announce Type: cross Abstract: Public discourse about artificial intelligence (AI) often uses anthropomorphic language: language that attributes human capabilities and characteristi

Hyper-Network Neural Functional Maps for Unsupervised Robust 3D Shape Matching

arXiv:2606.30131v1 Announce Type: cross Abstract: Functional maps are the cornerstone of recent non-rigid 3D shape matching methods due to their efficiency and performance. However, existing methods s

Local Ai

ImprovEvolve: Basin-Hopping Meets LLM-Guided Evolutionary Search

arXiv:2602.10233v2 Announce Type: replace-cross Abstract: LLM-guided evolutionary computation, most notably AlphaEvolve, has been remarkably successful in discovering novel mathematical constructions

local-aiarxiv-cs-ai

IMU-HOI: A Symbiotic Framework for Coherent Human-Object Interaction and Motion Capture via Contact-Conscious Inertial Fusion

arXiv:2606.28604v1 Announce Type: new Abstract: Capturing full-body human motion with object interactions is crucial for AR/VR and robotics applications, yet it remains challenging for conventional vi

Information Dynamics of Language Communication

arXiv:2606.30096v1 Announce Type: new Abstract: Quantifying how meaning propagates through communicative exchanges remains underdeveloped in computational linguistics. Here we introduce an information

researcharxiv-cs-cl

Informational Frustration in Neural Manifolds: Shannon Bottlenecks and the Limits of Learnability

arXiv:2606.30512v1 Announce Type: cross Abstract: Why overparameterised deep networks generalise so remarkably well remains one of the most stubborn open questions in machine learning theory. Classica

tutorialsarxiv-cs-ai

Inoculation Adapters: Improved Selective Generalization of Capabilities with Fewer Surprising Backdoors

arXiv:2606.30252v1 Announce Type: new Abstract: Inoculation prompting is a selective generalization technique used against Emergent Misalignment. We introduce inoculation adapters (IA), which similarl

tutorialsarxiv-cs-ai

Agents

Is Lying an Emergent Behaviour in LLMs? Evidence from Gaslighting AI agents in a Sustainability Game

arXiv:2606.28456v1 Announce Type: cross Abstract: LLMs agents are increasingly used in multi-agent settings, yet their behaviour in sustainability games remains largely unexplored. This work investiga

agentsarxiv-cs-ai

Joint 3D Gravity and Magnetic Inversion via Rectified Flow and Ginzburg-Landau Guidance

arXiv:2603.06829v2 Announce Type: replace Abstract: Subsurface ore detection is of paramount importance given the rising depletion of shallow mineral resources in recent years. It is crucial to explor

JOPP-3D: Joint Open Vocabulary Semantic Segmentation on Point Clouds and Panoramas

arXiv:2603.06168v3 Announce Type: replace Abstract: Semantic segmentation across visual modalities such as 3D point clouds and panoramic images remains a challenging task, primarily due to the scarcit