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From Zipf's Law to Neural Scaling through Heaps' Law and Hilberg's Hypothesis

arXiv:2512.13491v3 Announce Type: replace-cross Abstract: We inspect the deductive connection between the neural scaling law and Zipf's law -- two statements discussed in machine learning and quantita

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FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors for Contact-Rich Manipulation

DGX agent

arXiv:2606.13102v2 Announce Type: replace Abstract: Despite the success of vision-based generalist robotic policies, existing tactile-based policies remain tied to fixed embodiments and sensor setups.

safetyarxiv-cs-ro

23 Jun 2026

Tutorials

Full-Body Golf Swing Kinematic Reconstruction From a Smartwatch IMU

arXiv:2606.22876v1 Announce Type: new Abstract: Quantitative measurement of the golf swing is critical for evaluating technique and enabling individualized feedback. However, existing methods are impr

tutorialsarxiv-cs-cv

Full Nonlinear Nonholonomic Dynamics and Motion Analysis of a 3-DoF Underactuated Spherical Rolling Robot

arXiv:2606.22169v1 Announce Type: new Abstract: This paper presents a full nonlinear constrained dynamic model of MonoRollBot, a novel 3-DoF spherical rolling robot driven by a single motor, a lead-sc

researcharxiv-cs-ro

Fursee: Hybrid YOLO-DINOv3 Framework for Fursuit Identity Retrieval and Clustering

arXiv:2606.22872v1 Announce Type: new Abstract: Global furry conventions produce massive fursuit photographs, while manual sorting brings heavy labor costs and calls for automatic identity retrieval a

Applications

Fusing Backdoors, Machine Learning, and Optimization for Large-Scale Parametric Mixed-Integer Programs

arXiv:2606.21440v1 Announce Type: new Abstract: Large-scale optimization problems are often solved repeatedly under similar structural conditions, leading to substantial computational overhead. This o

applicationsarxiv-cs-lg

G-MASt3R-SfM: Graph-based View Pruning and Multi-stage Optimization for Robust SfM

arXiv:2606.22856v1 Announce Type: new Abstract: Structure from Motion (SfM) is essential for multi-view 3D reconstruction, however, its accuracy heavily relies on the accuracy of image matching. While

GAC: Stabilizing Asynchronous RL Training for LLMs via Gradient Alignment Control

arXiv:2603.01501v2 Announce Type: replace Abstract: Asynchronous execution is essential for scaling reinforcement learning (RL) to modern large model workloads, including large language models and AI

safetyarxiv-cs-lg

Tutorials

Gain Tuning Is Not What You Need: Reward Gain Adaptation for Constrained Locomotion Learning

arXiv:2510.10759v2 Announce Type: replace Abstract: Existing robot locomotion learning techniques rely heavily on the offline selection of proper reward weighting gains and cannot guarantee constraint

tutorialsarxiv-cs-ro

Applications

GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulation

arXiv:2411.18276v3 Announce Type: replace Abstract: Effectively manipulating articulated objects in household scenarios is a crucial step toward achieving general embodied artificial intelligence. Mai

applicationsarxiv-cs-ro

GARIP: A Running-Average Moving Reference for Last-Iterate Self-Play in Two-Player Zero-Sum Games

arXiv:2606.22688v1 Announce Type: cross Abstract: Self-play with naive gradient ascent cycles in two-player zero-sum games: the last iterate orbits the equilibrium. Modern methods restore last-iterate

safetyarxiv-cs-lg

Gated MLPs as Symmetry-Broken Rank-1 Bilinear Attention

arXiv:2606.22172v1 Announce Type: new Abstract: We show that the conventional gated MLP can be viewed as a rank-1 approximation to a bilinear attention mechanism with two distinct factors correspondin

Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems

arXiv:2505.00909v3 Announce Type: replace Abstract: In this paper, we propose a Gaussian Process (GP)-based policy iteration framework for addressing both forward and inverse problems in Hamilton--Jac

safetyarxiv-cs-lg

Tutorials

Gen2Balance: Generative Balancing for Long-Tailed Video Action Recognition

arXiv:2606.22416v1 Announce Type: new Abstract: We address the problem of training on long-tailed data for video action recognition. We propose to augment the training set using a text-to-video genera

tutorialsarxiv-cs-cv

Generalized nonparametric regression in reproducing kernel Hilbert spaces: Consistency and rates of convergence

arXiv:2606.22993v1 Announce Type: cross Abstract: We develop a comprehensive theory for regularized M-estimation in reproducing kernel Hilbert spaces. Under mild conditions on the loss we establish ex

Generating Fearful Images: Investigating Potential Emotional Biases in Image-Generation Models

arXiv:2411.05985v3 Announce Type: replace-cross Abstract: This paper examines potential biases and inconsistencies in the emotions evoked by images produced by generative artificial intelligence (AI)

Generative Modeling via Kernelized Stochastic Interpolants

arXiv:2602.20070v3 Announce Type: replace Abstract: We develop a kernel method for generative modeling within the stochastic interpolant framework, replacing neural network training with linear system

Generative Relightable Avatars

arXiv:2606.22718v1 Announce Type: new Abstract: We present Generative Relightable Avatars (GRA), a person-specific method for photorealistic free-view rendering and environment-map relighting of full-

Applications

Generative Robust Optimisation

arXiv:2606.22536v1 Announce Type: new Abstract: Classical uncertainty sets for robust optimisation impose fixed geometric shapes that cannot represent the complex dependencies present in real-world da

applicationsarxiv-cs-lg

Hardware

Genesis Workbench: A blueprint for industry AI in life sciences, powered by Databricks and NVIDIA

Genesis Workbench is a collaborative framework developed by Databricks and NVIDIA designed to accelerate AI adoption in the life sciences industry by providing integrated tools and best practices. The

hardwaredatabricks

GenTrack: A New Generation of Multi-Object Tracking

arXiv:2510.24399v3 Announce Type: replace Abstract: This paper introduces a novel multi-object tracking (MOT) method, dubbed GenTrack, whose main contributions include: first-a hybrid tracking approac

agentsarxiv-cs-cv

GeoFidelity-Bench: Evaluating Segment-Level Geographic Fidelity in Text-to-Image Street-View Generation

arXiv:2606.23669v1 Announce Type: new Abstract: Text-to-image models can generate visually plausible city streets, but whether their outputs correspond to a requested road segment rather than a generi

GeoFlow-SLAM++: A Robust Multi-Camera Visual-Inertial SLAM System with Relocalization

arXiv:2606.22051v1 Announce Type: new Abstract: Monocular and RGB-D visual-inertial SLAM systems remain susceptible to limited field of view, sensor-specific failure modes, and unreliable cross-sessio

researcharxiv-cs-ro

Geometric and Information Compression of Representations in Deep Learning

arXiv:2606.21593v1 Announce Type: new Abstract: Deep neural networks transform input data into latent representations that support a wide range of downstream tasks. These representations can be charac

Geometric Entropy: When Trajectory Diversity Helps and Hurts in Imitation Learning

arXiv:2606.20871v1 Announce Type: new Abstract: We study how trajectory-shape diversity in demonstrations affects imitation learning (IL) performance across models, tasks, and data scales. We introduc

safetyarxiv-cs-ro

Geometric Reconstruction of Extrinsic Contact Trajectories using Tactile Sensing and Proprioception for Tool Manipulation

arXiv:2606.22251v1 Announce Type: new Abstract: Tactile sensing enables robots to perceive rich contact information at the grasp, supporting tasks such as object recognition, in-hand pose estimation,

researcharxiv-cs-ro

GEOPHYS: The Geometry of Physical Plausibility

arXiv:2606.20707v1 Announce Type: new Abstract: While humans can identify physically implausible events within milliseconds, machine learning approaches addressing the same problem are extremely slow

GeoRouteNet: Geometry-Enhanced Non-Autoregressive Neural Solver for the Traveling Salesman Problem

arXiv:2606.22776v1 Announce Type: new Abstract: The traveling salesman problem (TSP) is a canonical NP-hard combinatorial optimization benchmark that tests the representational capacity and generaliza

GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer

arXiv:2512.20399v3 Announce Type: replace Abstract: We present GeoTransolver, a multiscale geometry-aware physics attention transformer for Computer Aided Engineering (CAE). GeoTransolver extends the

GIM-ENDO: A Multimodal Endoscopic Image and Video Dataset for Gastric Intestinal Metaplasia Morphology and Pathology

arXiv:2606.20919v1 Announce Type: new Abstract: Gastric intestinal metaplasia (GIM) is a precursor lesion to gastric dysplasia and adenocarcinoma whose early detection is crucial for intervening in th

GitOfThoughts: Version-Controlled Reasoning and Agent Memory You Can Replay, Diff, and Merge

arXiv:2606.14470v2 Announce Type: replace-cross Abstract: Large language model reasoning leaves no trace once it is done. The steps of a chain of thought disappear when the context window closes, a pr

GLM 5.2 is already top 10 on OpenRouter this week, sitting right next to Opus 4.8. it's also been really strong in Deep Agents across long-h…

GLM 5.2 is already top 10 on OpenRouter this week, sitting right next to Opus 4.8. it's also been really strong in Deep Agents across long-horizon coding, big context, tool use, and verifying work bef

agentsharrison-chase--x

GLM-5.2 is available in Perplexity's Agent API. Just tested it, and it's powerful when paired with the Search SDK inside a sandbox. - Spin u…

GLM-5.2 is available in Perplexity's Agent API. Just tested it, and it's powerful when paired with the Search SDK inside a sandbox. - Spin up a sandbox environment - Call the web search tool (people s

agentszhipu-ai--x

GO: The Great Outdoors Multimodal Dataset

arXiv:2501.19274v2 Announce Type: replace Abstract: The Great Outdoors (GO) dataset is a multi-modal annotated data resource aimed at advancing ground robotics research in unstructured environments. E

agentsarxiv-cs-ro

Go-with-the-Track: Video Compositing and Motion Control with Point Tracking

arXiv:2606.20891v1 Announce Type: new Abstract: Filmmaking demands precise motion control and reference image compositing -- capabilities that existing methods treat separately. Point-track-conditione

Gold Points Sniper: Self-guided Visual Reasoning in VLM for Fine-grained Action Understanding

arXiv:2606.22409v1 Announce Type: new Abstract: Robots operating in everyday environments must understand fine-grained human actions, intentions, and contextual cues from broad views where people occu

Good-Enough LLM Obfuscation (GELO)

arXiv:2603.05035v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly served on shared accelerators where an adversary with read access to device memory can observe K

Industry

Google Home will soon get better at recognizing you

A new update for Google Home could make it less likely your smart home cameras mistake you for someone else, just because you're facing away from the camera. Starting June 23rd, Google's expanding its

industrythe-verge-ai

Industry

Google plans a 12-week incubator, picking 10 to 20 AI startups from its 'Xoogler' alumni and providing up to 350K in cloud credits and 100K in direct funding (Guinevere Grant/Bloomberg)

Guinevere Grant / Bloomberg: Google plans a 12-week incubator, picking 10 to 20 AI startups from its “Xoogler” alumni and providing up to 350K in cloud credits and 100K in direct funding — Alphabet In

industrytechmeme

GRADE: Graph Representation of LLM Agent Dependency and Execution

arXiv:2606.22741v1 Announce Type: new Abstract: Can one graph represent every kind of LLM agent's run? A trace records what each step did, never what it relied on, the state it read, and the results i

agentsarxiv-cs-lg

Gradient-Descent Steps to Success over Mean Accuracy: A Paradigm Shift for ML

arXiv:2606.22053v1 Announce Type: new Abstract: Traditional evaluation of machine learning (ML) models typically focuses on achieving the maximum possible accuracy irrespective of the computational co

Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions

arXiv:2602.04548v2 Announce Type: replace Abstract: We develop a general mathematical framework to analyze scaling regimes and derive explicit analytic solutions for gradient flow (GF) in large learni

Gradient-Free Warm-Start Library Recovery: an Amortized-Regret Separation

arXiv:2606.21253v1 Announce Type: new Abstract: Continual learning that is gradient-free, local, online, and append-only is attractive for edge and streaming deployment, but its value is usually argue

agentsarxiv-cs-lg

Gradual Capacity Growth for Sparse Network Discovery

arXiv:2509.25665v2 Announce Type: replace Abstract: Sparse neural network methods typically assume that the target sparsity (or density) is fixed in advance, even though the relationship between netwo

GRAG: Generic Response-Augmented Generation Framework for Personalized Conversational Systems

arXiv:2606.21097v1 Announce Type: cross Abstract: Deploying highly capable personalized conversational agents in resource-constrained or privacy-sensitive environments remains a significant challenge.

GRAIN: Group Aggregation via Min-Norm Objective

arXiv:2606.22917v1 Announce Type: new Abstract: Learning instability is a long-standing problem across machine learning, but it is especially acute in the overparameterized regime that defines modern

Graph Alignment via Dual-Pass Spectral Encoding and Latent Space Communication

arXiv:2509.09597v3 Announce Type: replace-cross Abstract: Graph alignment, the problem of identifying corresponding nodes across multiple graphs, is fundamental to numerous applications. Most existing

safetyarxiv-cs-cv

Graph-of-Differences: Anatomy-Structured Difference Alignment for Medical Image Re-Identification

arXiv:2606.21368v1 Announce Type: new Abstract: Medical image re-identification (MedReID) enables longitudinal patient linkage but remains vulnerable to shortcut learning and often produces decisions

safetyarxiv-cs-cv