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Enterprise-grade PostgreSQL with AlloyDB Omni RPM Orchestrator is generally available

model-releasesgoogle-cloud-ai

We are thrilled to announce the general availability of the AlloyDB Omni Red Hat RPM orchestrator, that brings production-ready security, resiliency, and low-downtime operations to PostgreSQL workload

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Safety

Entropy-Regularized Rank-Masked Policy Optimization for Test-Time Reinforcement Learning in Code Generation

DGX agent

arXiv:2609.09135v1 Announce Type: new Abstract: Existing methods for test-time reinforcement learning (TTRL) derive rewards from answer-level self-voting on unlabeled test-time tasks with canonical an

safetyarxiv-cs-lg

9 Sept 2026

EntropyPrune: Matrix Entropy Guided Visual Token Pruning for Multimodal Large Language Models

arXiv:2602.17196v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) incur substantial inference cost due to the processing of hundreds of visual tokens per image. Although tok

Environments as Scaffold: Enriching Feedback to Bootstrap Self-Evolving Agents in Long-Horizon Tasks

arXiv:2609.08404v1 Announce Type: new Abstract: Large Language Models demonstrate remarkable proficiency in static reasoning, yet training them as autonomous agents through Reinforcement Learning (RL)

safetyarxiv-cs-lg

Applications

EquiGQNet: Fast Grasp Quality Evaluation via Shared Equivariant Point Cloud Encoding

arXiv:2609.07145v1 Announce Type: new Abstract: Planning six-degree-of-freedom (6-DoF) grasps for unseen objects in cluttered tabletop scenes from a single-view depth image requires accurate and effic

applicationsarxiv-cs-ro

Equivariance Breaks the Learning Rate

arXiv:2609.08381v1 Announce Type: new Abstract: Equivariant networks are commonly trained with Adam, yet recent work reports that matrix-structured optimizers such as Muon can perform better on these

Agents

Estimating Semantic Ambiguity via Gaussian Context Distributions for VLM-Driven Traversability Analysis

arXiv:2609.08583v1 Announce Type: new Abstract: Autonomous navigation in unstructured environments requires robust scene understanding, yet Vision-Language Models (VLMs) often suffer from semantic amb

agentsarxiv-cs-ro

Hardware

EStream: Fast and Memory-Efficient MoE Prefill through Expert Virtualization on Mobile NPUs

arXiv:2609.06551v1 Announce Type: cross Abstract: Mobile vendors and application developers increasingly deploy LLMs on smartphones for diverse prefill-only services. Yet current systems rely mainly o

hardwarearxiv-cs-lg

Agents

Euno raises $23M to build the AI-native context brain for autonomous agents

Israeli artificial intelligence startup Euno says it’s trying to build an AI-native “context brain” for autonomous agents after raising 23 million in an early-stage funding today. The Series A round w

agentssiliconangle

Evaluating Vision-Language Models for Image Quality Assessment using Psychophysical Data

arXiv:2603.24578v2 Announce Type: replace Abstract: Psychophysical experiments remain the most reliable approach for perceptual image quality assessment (IQA), yet their cost and limited scalability m

Evaluation of Contextual Understanding in Large Language Models

arXiv:2609.09004v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate impressive performance across diverse NLP tasks, yet their ability to exhibit genuine contextual understandin

Evaluation Principles for MRI-MRA Registration in Trigeminal Neuralgia: An ROI-Centered Neurovascular Benchmark

arXiv:2609.08805v1 Announce Type: new Abstract: Preoperative evaluation of trigeminal neuralgia (TN) often requires joint interpretation of structural MRI, which depicts the trigeminal nerve and surro

Event-Based De-Snowing for Autonomous Driving

arXiv:2507.20901v2 Announce Type: replace Abstract: Adverse weather conditions, particularly heavy snowfall, pose significant challenges to both human drivers and autonomous vehicles. Traditional imag

Eventually Optimal and Scalable Multi-Agent Planning for Block Cave Mining

arXiv:2609.07109v1 Announce Type: new Abstract: Automation in underground mining has the potential to significantly enhance safety, operational efficiency, and sustainability. However, effectively coo

safetyarxiv-cs-ro

Evolution of Multimodal Question Answering: From Modality-Adaptive Extraction to Unified Language Representation

arXiv:2609.08896v1 Announce Type: cross Abstract: The rapid growth of multimodal data has intensified the need for question answering (QA) systems capable of reasoning across heterogeneous sources suc

EvoNav-Bench: Benchmarking Lifelong Navigation in Evolving Environments

model-releasesarxiv-cs-ro

arXiv:2609.08292v1 Announce Type: new Abstract: Lifelong navigation (LN) requires an embodied agent to solve a sequence of navigation subtasks in the same environment. Since solving each subtask from

Exact Record Omission in Delta Attention: A Transport Criterion, Its Cost, and a Replay Certificate

arXiv:2609.06872v1 Announce Type: new Abstract: When a user asks an assistant to forget a record, the test is whether the memory now matches the state it would hold if the record had never been stored

Hardware

Exclusive: Compute Exchange adds GPU inventory manager to simplify AI infrastructure purchases

The Compute Exchange Inc., a startup that matches buyers and sellers of graphics processing units, is launching a GPU inventory management capability intended to give enterprise buyers a consolidated

hardwaresiliconangle

Applications

Explainable Temporal Attention-based Defect Detection For Fillet Joints in Real-Time Gas Metal Arc Welding Based on Multi-modal Data

arXiv:2609.07893v1 Announce Type: cross Abstract: Deep learning is an efficient technique to monitor the real time welding process, reducing post-welding repairs and production delays. This paper leve

applicationsarxiv-cs-lg

Exploring a side question without losing the original conversation

I shared ThoughtDAG here a while ago. I've now recorded how I use it: select a phrase in an answer, explore it on a branch, and connect the parts I want in the next question. I'm the developer. Though

model-releasesr-ollama

extbf{PLATO}: Preintegration Learning from Accurate Trajectory Observations for Neural Inertial Odometry

model-releasesarxiv-cs-ro

arXiv:2609.06450v1 Announce Type: new Abstract: Neural inertial odometry has demonstrated strong potential for motion estimation in challenging environments, yet inertial-only preintegration remains s

FaceLinkGen: A Re-evaluation of Identity Leakage in Privacy-Preserving Face Recognition and Face Anonymization Systems Using Simple Distillation

arXiv:2602.02914v3 Announce Type: replace Abstract: Privacy-preserving face recognition (PPFR) hides facial appearance while retaining machine recognition, whereas perception-preserving face de-identi

Facial Age Estimation for Age Fraud Detection in National ID Systems

arXiv:2609.05638v1 Announce Type: new Abstract: Identity fraud during biometric enrollment and updates remains a major challenge for large-scale national identity systems. A common fraud vector is mis

FACT: A Forensic Agent with Compiled Tool-Use Trajectories for AI-Generated Image Detection

arXiv:2609.05876v1 Announce Type: new Abstract: AI-generated image detection is increasingly open-world: new image generators produce highly realistic images that make visual artifacts harder to ident

Hardware

FALCON-S: Fixed-wing ground-effect Aerodynamics Simulator and Flight Control Learning Suite

arXiv:2609.06046v1 Announce Type: cross Abstract: We present a modular, high-fidelity simulation framework for the development and benchmarking of flight control strategies in fixed-wing aerial robots

hardwarearxiv-cs-lg

FANS: Federated Adaptive Network Search Learning for Heterogeneous Devices

arXiv:2609.06106v1 Announce Type: new Abstract: Heterogeneous Federated Learning (HFL) aims to train models across devices with diverse resource budgets while preserving data privacy. Existing HFL met

Fast PAC Global Optimization via Restarted Langevin: Exploration, Exploitation, and Degenerate Cooling

arXiv:2609.06196v1 Announce Type: cross Abstract: We study the computational effort required for global optimization of a smooth, possibly nonconvex objective Gamma:R^doR. An algorithm satisfies the (

Feature Superposition in Neural Networks: From Theory to Practice

arXiv:2609.06862v1 Announce Type: new Abstract: Superposition refers to neural networks representing more features than they have dimensions. It offers a possible explanation for polysemantic neurons

Federated Binary Gating with Server-Side Vision-Language Inference for Surveillance Anomaly Classification

arXiv:2609.07403v1 Announce Type: new Abstract: Privacy-sensitive surveillance systems could benefit from large vision-language models (VLMs), but such models typically require centralized access to r

FedGenSC: Federated Generative Semantic Communication with Channel-Aware Adaptation

arXiv:2609.08593v1 Announce Type: cross Abstract: Integrating generative adversarial networks (GANs) into federated semantic communication (SemCom) is a natural progression, as generative priors can r

FedRAW: Preserving Rare-Label Influence in Asynchronous Federated Learning

arXiv:2609.07192v1 Announce Type: new Abstract: Asynchronous federated learning improves scalability by updating the global model from a server-side buffer of client updates as they arrive, rather tha

safetyarxiv-cs-lg

FedSubMuon: Communication-Efficient Federated LLM Fine-Tuning via Structured Subspace Muon

arXiv:2609.06073v1 Announce Type: new Abstract: Federated fine-tuning adapts large language models (LLMs) to decentralized client data, but its scalability in cross-device training is often limited by

Feedback Control for Multi-Objective Graph Self-Supervision

arXiv:2602.05036v2 Announce Type: replace Abstract: Can multi-task self-supervised learning on graphs be coordinated without the usual tug-of-war between objectives? Graph self-supervised learning (SS

Applications

Fewer yet critical: Reducing Redundant Token Dependencies for Transformer-based Time Series Forecasting

arXiv:2503.06867v2 Announce Type: replace-cross Abstract: Time series forecasting (TSF) is important in real-world applications. Recently, Transformer-based methods have achieved strong performance by

applicationsarxiv-cs-lg

FigEx2: Visual-Conditioned Panel Detection and Captioning for Scientific Compound Figures

arXiv:2601.08026v5 Announce Type: replace Abstract: Scientific compound figures combine multiple labeled panels into a single image, and downstream pretraining and retrieval require panel-aligned visu

FILT3R: Latent State Adaptive Kalman Filter for Streaming 3D Reconstruction

arXiv:2603.18493v2 Announce Type: replace Abstract: Streaming 3D reconstruction maintains a persistent latent state that is updated online from incoming frames, enabling constant-memory inference. A k

Fine-grained Distributed Backdoor Attacks in Federated Learning

arXiv:2609.07147v1 Announce Type: new Abstract: Federated learning, as a privacy-preserving distributed machine learning paradigm, faces significant threats from backdoor attacks. Compared to centrali

Fine-Grained Instruction-Guided Graph Reasoning for Vision-and-Language Navigation

arXiv:2503.11006v3 Announce Type: replace Abstract: Vision and Language Navigation (VLN) requires an embodied agent to traverse complex environments by following natural language instructions, demandi

Fine-Grained Visual Preprocessing and Dual-Stream Temporal Modeling for Multimodal Sentiment Analysis on Social Media

arXiv:2609.07010v1 Announce Type: new Abstract: Multimodal sentiment analysis often remains text-dominant due to raw-video noise and insufficient temporal modeling. Using CH-SIMS v2.0S, this study pro

FineHOI: Part-Aware Dense Representations for Zero-Shot Human-Object Interaction Detection

arXiv:2609.05959v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection aims to localize humans and objects in images and classify their interactions. Zero-shot HOI focuses on recogni

FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute

arXiv:2609.08848v1 Announce Type: new Abstract: We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for gam

Fitting and Learning Basis-Restricted Propositional Formulas

arXiv:2609.08961v1 Announce Type: cross Abstract: For a finite set O of Boolean functions, we consider the class of propositional formulas built using the functions in O as connectives. We determine,

Fixed-Dimensional Latent Flow for Generating Variable-Size 3D Molecules

arXiv:2609.08333v1 Announce Type: cross Abstract: In molecular discovery, molecule size is coupled to composition, structure, and other target properties. Yet most 3D generators require molecule size

safetyarxiv-cs-lg

Flexible Motion Generation from Language and Style References

arXiv:2609.08032v1 Announce Type: new Abstract: We introduce FlexMoGen, a novel framework for flexible human motion synthesis conditioned on both natural language descriptions and motion style referen

Flexible Spectral-Normalized Neural Gaussian Process for Dynamic Aperture Prediction

arXiv:2609.08620v1 Announce Type: cross Abstract: We address the challenge of scalable uncertainty quantification in large-scale scientific applications, where complex state-of-the-art machine learnin

Flow-Matching Guided Deep Unfolding for Hyperspectral Image Reconstruction

arXiv:2510.01912v2 Announce Type: replace Abstract: Reconstructing a three-dimensional hyperspectral cube from a two-dimensional compressed measurement is a severely ill-posed inverse problem. Existin

Flow3D-OPD: Multi-Teacher On-Policy Distillation for 3D Geometry Generation with Flow-Matching Diffusion Transformer

arXiv:2609.07137v1 Announce Type: new Abstract: Recent image-to-3D generation models built on flow-matching diffusion Transformers (DiT) can produce high-fidelity meshes, yet their post-training strat

FMMO: Detecting the Divergence Between Local Attribution and Global Drift

arXiv:2609.06173v1 Announce Type: new Abstract: Post-deployment drift poses a critical risk to algorithmic accountability, particularly when ground truth labels are delayed and performance degradation