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arXiv:2609.35568v1 Announce Type: new Abstract: High-performance kernels underpin efficient accelerator execution but require expert tuning and lengthy manual optimization cycles. LLM coding agents pr

hardwarearxiv-cs-lg

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Research

From Feed-Forward to Flow: Unifying Reconstruction and Generation Is Easier Than You Think

DGX agent

arXiv:2609.32761v1 Announce Type: new Abstract: Reconstruct where the images provide evidence, and generate where they do not: recent success of spatial world models such as Atlas (World Labs Team, 20

researcharxiv-cs-cv

29 Sept 2026

From Grey-Box to Green-Box: When can Physics-Informed Machine Learning Reduce Carbon Footprints in Structural Health Monitoring?

arXiv:2609.33387v1 Announce Type: new Abstract: Machine learning plays an increasingly vital role in engineering, but the corresponding increase in compute time is not without environmental cost. Phys

From HL to H+L-1 Parameters: A Hankel-Toeplitz Forecaster for Long-Term Time Series Forecasting

arXiv:2609.33984v1 Announce Type: new Abstract: Linear forecasters have shown competitive accuracy against Transformer-based models in long-term time series forecasting. We study how classical station

Tutorials

From internal representations to model improvement through prediction errors

arXiv:2609.35449v1 Announce Type: new Abstract: With limited annotation budgets, choosing which images to label determines how much a model improves. Data-selection methods that use features from a se

tutorialsarxiv-cs-cv

From Knowing to Abstaining: Bridging the Representation-Action Gap in Vision-Language Models

arXiv:2609.32653v1 Announce Type: cross Abstract: The ability of vision-language models (VLMs) to abstain from unanswerable questions is as important as their ability to answer answerable ones accurat

From Language to Task Maps: Compiling Semantic Relations While Preserving Task-Relevant Freedom

arXiv:2609.34412v1 Announce Type: new Abstract: Natural-language manipulation instructions specify qualitative relations, whereas continuous controllers require state-evaluable task quantities, differ

researcharxiv-cs-ro

From One-Shot Generation to Incremental Music Composition: Adapting a General-Purpose Instruction LLM for Persistent Symbolic Editing

arXiv:2609.34994v1 Announce Type: cross Abstract: Most music-generation systems are still framed and evaluated primarily as producers of complete outputs, whereas composition often proceeds through su

from our blog post on how we made Claude faster: https://claude.dev/blog/how-we-made-claude-ai-faster/

Claude.ai achieved roughly a three‑fold speed increase in just two weeks by implementing targeted engineering optimisations. The blog post on claude.dev explains the key changes—such as streamlined co

model-releasesthariq--x

From PDF to Evidence: Structure-Aware Retrieval for Clinical Practice Guidelines

arXiv:2609.33447v1 Announce Type: cross Abstract: Guideline documents are published as unstructured PDFs whose evidence is locked in visual structures---tables, flowcharts, and graded recommendations-

From Perception to Integration: Revisiting the Internal Dynamics of Reasoning in Vision-Language Models

arXiv:2609.34809v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer simple visual questions, but often struggle when one question requires several visual judgments. We study this

From Phase Transition to Systemic Failure: A Decoupled Analytics Framework for GNN Robustness

arXiv:2609.31656v1 Announce Type: new Abstract: Data quality is a major bottleneck for the reliable deployment of graph neural networks (GNNs) in real-world graph mining tasks. Among various sources o

From Pixel Generation to Topological Inference: Structural Dual Super-Resolution for Trustworthy Cross-Physical-Domain Trabecular Morphology Learning

arXiv:2609.34716v1 Announce Type: new Abstract: Clinical CT and UHRCT cannot resolve individual trabeculae, whereas synchrotron radiation microCT (SR{mu}CT) provides 3.2{mu}m high-resolution reference

From Pixel to Poses: Object-centric Tool Manipulation Learning from Human Demonstrations

arXiv:2609.35375v1 Announce Type: new Abstract: Scaling up robotic manipulation is primarily bottlenecked by the scarcity of real-world robot data. While recent approaches leverage human video demonst

Local Ai

From Preference to Reciprocity: Decentralized Matching with Empirically Grounded LLM-agent Based Modeling

arXiv:2609.34679v1 Announce Type: new Abstract: Bipartite matching is a fundamental problem in game theory and market design. Classical approaches such as Gale--Shapley assume complete preferences and

local-aiarxiv-cs-lg

From Scores to Samples: Elastic Forcing for Autoregressive Video Generation

arXiv:2609.35491v1 Announce Type: new Abstract: Few-step autoregressive video generation commonly relies on Distribution Matching Distillation (DMD), requiring a bidirectional diffusion teacher and an

From Soft Targets to Reward Signals: How Assignment and Reward Objectives Interact

arXiv:2609.34850v1 Announce Type: cross Abstract: Soft preference targets specify supervision strength, and reward objectives convert that strength into learned reward signals. A central design questi

From Static to Dynamic: On-Policy Distillation from Image to Video Diffusion Models

arXiv:2609.34371v1 Announce Type: new Abstract: On-policy distillation (OPD) specializes pretrained video diffusion models through teacher supervision along the student's own generation trajectory. Al

From UNI2-h to ConvNeXt-T: Lightweight Nuclei Instance Segmentation via Knowledge Distillation

arXiv:2609.35203v1 Announce Type: new Abstract: Nuclei instance segmentation is a core task in digital pathology, yet high-accuracy models rely on large vision transformer (ViT) encoders whose inferen

From World Models to World Action Models: Rethinking Next-State Prediction

arXiv:2609.34414v1 Announce Type: new Abstract: Predicting the next state is a core paradigm of World Models for modeling physical dynamics, emphasizing prediction fidelity. As World Models evolve int

Frontier Learning: Training LLM Reasoners at the Edge of Capability

arXiv:2609.35426v1 Announce Type: new Abstract: Reinforcement Learning-based post-training of Large Language Models (LLM) has been successfully applied to improve their reasoning capabilities. Existin

safetyarxiv-cs-lg

Agents

Frozen Judges, Moving Agents: Version-Dependent LLM-Judge Error and the Limits of Judge-Assisted Agent Evaluation

arXiv:2609.34198v1 Announce Type: new Abstract: Language-model judges compare agent upgrades with their predecessors, but a fixed judge can make version-dependent mistakes. We analyze 35 public coding

agentsarxiv-cs-lg

FSS-UBrain: Multi-region Few-Shot Brain Tumor MRI Segmentation

arXiv:2609.32273v1 Announce Type: new Abstract: Accurate delineation of whole tumor (WT), tumor core (TC), and enhancing tumor (ET) from multimodal magnetic resonance imaging remains challenging under

Functional Autoencoders for Amplitude-Phase Representation Learning

arXiv:2609.34207v1 Announce Type: cross Abstract: Functional data are intrinsically infinite-dimensional, and often exhibit phase variation, where corresponding events occur at different times across

safetyarxiv-cs-lg

Applications

Functional Hand Type Prior for 3D Hand Pose Estimation and Action Recognition from Egocentric View Monocular Videos

arXiv:2609.34149v1 Announce Type: new Abstract: Current methods for egocentric view action recognition often face challenges in perceiving dynamic hand movements relying solely on geometrical or physi

applicationsarxiv-cs-cv

Tutorials

FUND: Density Flow for Sampling Unnormalised Distributions

arXiv:2609.32296v1 Announce Type: new Abstract: Efficient sampling from Boltzmann distributions is central to modelling complex physical systems. Markov Chain Monte Carlo (MCMC) methods suffer from cr

tutorialsarxiv-cs-lg

Applications

FurE: Efficient Instance-Specific 3D Fur Reconstruction without Animal-Fur Datasets

arXiv:2609.35770v1 Announce Type: new Abstract: Realistic and editable animal fur reconstruction from multi-view images is challenging due to fine-scale detail, self-occlusion and obfuscation, and, un

applicationsarxiv-cs-cv

FuseAlign: Forced Alignment in the Wild

arXiv:2609.33650v1 Announce Type: new Abstract: Word-level forced alignment estimates when each transcript word occurs in an audio recording. It underpins text-based media editing, subtitling, speech-

FUSION: a skill-based research agent for publicly obtainable nuclear-physics codes

arXiv:2609.04742v1 Announce Type: cross Abstract: Running an unfamiliar nuclear-physics code is rarely difficult because of the physics alone. One must find and build the program, learn its input conv

Fusion Under Component Failure: Negative Results and Failure Modes in Ensemble AI-Generated Image Detection

arXiv:2609.31749v1 Announce Type: new Abstract: We built an ordinary stacking ensemble for AI-generated image detection -- three open detectors producing five scores, fused by a gradient-boosted meta-

Future Information-Directed Sampling for Bayesian Nonstationary Bandits

arXiv:2609.33981v1 Announce Type: new Abstract: Exploration--exploitation is a central trade-off in bandit learning. While classical algorithms such as upper confidence bound methods and Thompson Samp

safetyarxiv-cs-lg

Local Ai

FutureDuet: Decoupling Observation Access from Future Supervision in World Action Models

arXiv:2609.34362v1 Announce Type: new Abstract: World Action Models (WAMs) augment robot action generation with future visual supervision. Existing WAMs commonly fuse main and wrist observations into

local-aiarxiv-cs-ro

Local Ai

FutureRay: Control-Aligned Future Range for Agile Quadruped Navigation

arXiv:2609.32158v1 Announce Type: new Abstract: Moving obstacles can block a previously clear route while a quadruped robot executes a motion command. We investigate whether predicting changing cleara

local-aiarxiv-cs-ro

Fwiw I am certain you can build a DeepSeek/Zhipu/Minmax etc level AI lab in the UK Not easy ofc, great teams there

model-releasesemad-mostaque--x

Fwiw I am certain you can build a DeepSeek/Zhipu/Minmax etc level AI lab in the UK Not easy ofc, great teams there 🚨 WATCH: Andy Burnham says he will create a 'global code' for AI so Britain can 'capt

Fysiverse-3D-SimReady Technical Report: Agentic Physical Simulation for Pragmatic 3D World Reconstruction

arXiv:2609.31715v1 Announce Type: new Abstract: Agentic recognition requires visual perception to move beyond static scene understanding and produce structured scene representations that support the p

G^3-LoRA: Organizing Reward-Weighted Video Data with Gradient-Guided Grouped LoRA

arXiv:2609.35189v1 Announce Type: new Abstract: Post-training foundation video models on heterogeneous reward-weighted data usually assume that all data categories induce compatible updates. This assu

GAE: General Action Expert for Real-Time Humanoid Teleoperation

arXiv:2609.34233v1 Announce Type: new Abstract: Humanoid avatars extend human physical presence beyond the body, enabling people to participate in social, service, and labor activities through remotel

Agents

Game-Theoretic Control with Constrained Potential Surgery

arXiv:2609.31901v1 Announce Type: new Abstract: Constrained general-sum dynamic games are a popular formulation for highly interactive multi-agent planning problems. In recent years, Generalized Nash

agentsarxiv-cs-ro

Gauge-Equivariant Attention for Rotation-Stable 360^irc Scene Understanding

arXiv:2609.31755v1 Announce Type: new Abstract: Panoramic 360^irc scene understanding increasingly relies on icosphere transformers, but a state-of-the-art spherical model loses more than half of its

GAUGE: Group-Wise View-Inconsistency Rectification for Feed-Forward 4D Tracking

arXiv:2609.32596v1 Announce Type: new Abstract: Feed-forward models regress dense 3D point trajectories directly from monocular video, yet the residual after global alignment is substantial and lacks

GAUGE: Planner-Conditioned Active Calibration of Opaque Quadruped Velocity Interfaces

arXiv:2609.32154v1 Announce Type: new Abstract: In this paper, we present a Goal-Aware Uncertainty-Guided Exploration (GAUGE) framework for planner-conditioned active calibration of opaque quadruped v

researcharxiv-cs-ro

Gaussian Image Steganography via Parameter-Domain Keyed Embeddings

arXiv:2609.32131v1 Announce Type: new Abstract: 2D Gaussian-based image representation is becoming increasingly popular, and our work proposes a new approach to steganography by embedding information

Gaussian Neural Networks

arXiv:2609.34825v1 Announce Type: new Abstract: Gaussian neural networks (GaNNs) are proposed as a novel regularization mechanism for neural networks. From a Bayesian perspective standard regularizati

Gaussian Splatting-based Volumetric Video Compression with Sparse 4D Anchors

arXiv:2609.33969v1 Announce Type: new Abstract: Immersive video communication requires photorealistic, render-efficient, and compact dynamic scene representations. 3D Gaussian Splatting (3DGS) offers

Gaze Prompts: Temporally Dense Human Attention for Vision-Language-Action Fine-Tuning

arXiv:2609.34550v1 Announce Type: new Abstract: Vision-Language-Action (VLA) fine-tuning pairs images with actions at every step, yet typically provides only a task-level language instruction, leaving

Industry

General Intuition, which trains AI agents in spatial reasoning via gameplay footage, raised 220M at a 6.2B valuation, for $650M+ in total funding (Dean Takahashi/GamesBeat)

Dean Takahashi / GamesBeat: General Intuition, which trains AI agents in spatial reasoning via gameplay footage, raised 220M at a 6.2B valuation, for 650M+ in total funding — General Intuition has rai

industrytechmeme

Generalization Analysis of Online Stochastic Gradient Descent for Overparameterized Two-Layer Neural Networks

arXiv:2407.07670v2 Announce Type: replace-cross Abstract: We investigate the generalization performance of online stochastic gradient descent (SGD) for overparameterized two-layer neural networks unde

Generative AI-Based Data Augmentation for Oral Lesion Classification: The PhotoMOCI Dataset and Benchmark

arXiv:2609.35226v1 Announce Type: new Abstract: Early detection of oral cancer via photographic imaging presents a promising avenue for large-scale oral cavity screening. However, the development of r