Search: “framework”

FLOW: Feature-Level Optimal Warping for Generalized Remote Physiological Measurement

arXiv:2609.38913v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact physiological measurement but remains vulnerable to domain shifts from illumination, motion, and

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Forging LLM Authorship Fingerprints with Targeted Rewriting

DGX agent

arXiv:2609.38831v1 Announce Type: new Abstract: Model-attribution classifiers can often identify which language model produced a text, making model-specific writing patterns a signal of provenance. Ac

researcharxiv-cs-cl

1 Oct 2026

FORTE: Forecasting Occupancy for Spatiotemporal Risk-Aware Planning in Dynamic Environments

arXiv:2609.39305v1 Announce Type: new Abstract: Safe navigation in dynamic environments requires anticipating future environmental states to account for spatiotemporal risks, specifically when and whe

researcharxiv-cs-ro

Framing the Narrative: Ideological Mimicry in Large Language Models

arXiv:2609.38256v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to answer questions about politically contentious issues, yet evaluations typically treat a model's s

researcharxiv-cs-cl

From Compound Figures to Medical Multi-image Reasoning: Scaling Multimodal Large Language Models with Biomedical Literature

arXiv:2511.22232v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) are increasingly capable in medical imaging, yet most focus on single-image settings. Clinical interp

From Construction to Injection: Edit-Based Fingerprints for Large Language Models

arXiv:2509.03122v5 Announce Type: replace-cross Abstract: Reliable model fingerprints are essential for protecting large language models (LLMs) against unauthorized redistribution and commercial misus

From Core to Detail: Unsupervised Disentanglement with Entropy-Ordered Flows

arXiv:2602.06940v2 Announce Type: replace Abstract: The unsupervised discovery of features that are both semantically meaningful and stable across runs remains a central challenge in representation le

From Given to Gathered Evidence: Agentic Learning for Longitudinal Medical Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.39566v1 Announce Type: new Abstract: Foundation models can serve as clinical agents through tool-use harnesses. However, conventional medical benchmarks assess reasoning over preselected ev

From Local Whole-Body VLA Behaviors to Scene-Scale Aerial Manipulation

arXiv:2609.39670v1 Announce Type: new Abstract: Vision-language-action (VLA) models enable task-conditioned interaction, but extending them to scene-scale aerial manipulation remains challenging due t

safetyarxiv-cs-ro

Agents

From Solo to Social Learning: Characterizing Recursive Social Improvement in LLMs

arXiv:2609.38516v1 Announce Type: cross Abstract: Large language models (LLMs) can now improve themselves by revising the instructions they follow, and LLM agents are increasingly orchestrated to work

agentsarxiv-cs-ai

FrontierGS: Progressive View-Space Frontier Expansion for Sparse 3D Gaussian Splatting

arXiv:2511.16030v3 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) enables efficient, high-fidelity novel view synthesis, yet its performance degrades severely under sparse-view supervis

GateSPINE: Gated Cross-View Fusion for Lumbar Spine MRI Report Generation

arXiv:2609.40091v1 Announce Type: cross Abstract: Automated report generation can ease the burden radiolo gists face when interpreting multi-sequence MRI studies. Unlike CT, MRI examinations comprise

Gaussian Stippling: Efficient Sorting-Free 3D Gaussian Rendering through Hybrid Sampling and Spatiotemporal Reconstruction

arXiv:2609.38488v1 Announce Type: cross Abstract: Conventional 3D Gaussian Splatting (3DGS) requires depth sorting and ordered alpha blending to correctly render overlapping Gaussian primitives. Stoch

GazeFlow: From Human Gaze Behavior to Generative Egocentric Gaze Prediction

arXiv:2609.38519v1 Announce Type: new Abstract: Egocentric gaze prediction enables many downstream applications but remains challenging, as human gaze is inherently stochastic. This stochasticity is c

General Performance Guarantee for Human Torque Estimation-Based Task-Agnostic Assistive Exoskeleton Control

arXiv:2609.39558v1 Announce Type: cross Abstract: Accurate human torque estimation is crucial for enabling task-agnostic control in robotic exoskeleton systems. However, estimation errors may cause mi

Generalized Geometry Block Proximal Linearized Method for Multiblock Nonconvex and Nonsmooth Optimization

arXiv:2609.39301v1 Announce Type: cross Abstract: This paper considers a class of multiblock nonconvex and nonsmooth optimization problems arising in many applications. Existing methods construct prox

GeoNest: Learning to Select Failure-Aware Neighborhoods for the Irregular Knapsack Problem in a Circular Container

arXiv:2609.38863v1 Announce Type: cross Abstract: The two-dimensional irregular knapsack problem in a fixed circular container is an important combinatorial optimization problem for maximizing materia

Hardware

Gestalt: a meta-foundation model for astronomy

arXiv:2609.38312v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each n

hardwarearxiv-cs-lg

Graph Anomaly Detection as Finite-Horizon Control: Training-Free Scoring via Empirical Bayes

arXiv:2609.38424v1 Announce Type: new Abstract: Node-level graph anomaly detection (GAD) identifies nodes whose attributes and interactions deviate from dominant graph regularities. Existing GAD model

Graph Residual Conjugate Diffusion: SNR-Equalized Heat Flow for Graph Signals

arXiv:2609.39658v1 Announce Type: new Abstract: Diffusion models generate data by reversing a forward corruption process that typically approaches a simple Gaussian prior. Recent work has extended thi

GraphForge: Training Working Agents with Graph-Anchored Workspace Synthesis

model-releasesarxiv-cs-cl

arXiv:2609.38923v1 Announce Type: new Abstract: Working agents need to read diverse files, coordinate tools, and produce deliverables. Training such agents requires tasks built on many real files with

GraphMAS: A Systematic Benchmark of Multi-Agent Coordination for Graph Learning

model-releasesarxiv-cs-lg

arXiv:2609.39777v1 Announce Type: new Abstract: LLM-based multi-agent systems coordinate specialized reasoning through aggregation, interaction, and adaptive control, yet their potential for graph lea

GraphToxin: Reconstructing Full Unlearned Graphs from Graph Unlearning

arXiv:2511.10936v3 Announce Type: replace-cross Abstract: Graph unlearning (GU) has emerged as a promising solution to comply with 'the right to be forgotten' regulations by enabling the removal of se

Local Ai

GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking

arXiv:2609.39116v1 Announce Type: new Abstract: Prior-free 6D object pose tracking seeks to recover the trajectory of an unseen object from a single RGB video without object-specific CAD models, posed

local-aiarxiv-cs-cv

HARDE: Optimizing Agent Harnesses for Runtime Risk Detection and Execution Control

arXiv:2609.38291v1 Announce Type: cross Abstract: Large language model (LLM) agents are vulnerable to safety risks such as injected malicious instructions or misleading information, motivating runtime

safetyarxiv-cs-cl

Here the World in Stereo: Learning Dynamic Spatial Correspondence for Immersive Joint Video-Audio Generation

arXiv:2609.38748v1 Announce Type: new Abstract: Recent joint video-audio generation models have achieved strong semantic correspondence and temporal synchronization. However, applications such as AR/V

Tutorials

Hermes: Learning Contextual Reasoning Unlocks Test-Time Scaling

arXiv:2609.38332v1 Announce Type: cross Abstract: Test-time scaling improves model performance by allocating additional compute during inference. Using this compute effectively across multiple context

tutorialsarxiv-cs-ai

How Accurate Is Accurate Enough?

arXiv:2609.38785v1 Announce Type: new Abstract: How accurate must a numerical approximation be within a learning system? Primitive error alone cannot answer this question: errors of the same magnitude

Hyperbolic Prototype Routing for Rehearsal-Free Class-Incremental Learning

model-releasesarxiv-cs-lg

arXiv:2609.39550v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) aims to continually learn new classes while preserving prior knowledge. Parameter-efficient fine-tuning with pre-traine

Hyperspectral Image Models: Technical Report

model-releasesarxiv-cs-cv

arXiv:2609.39871v1 Announce Type: new Abstract: Hyperspectral remote sensing has advanced across diverse deep learning paradigms, including spectral spatial CNNs, Vision Transformers, Mamba, graph neu

Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting

arXiv:2512.19735v4 Announce Type: replace Abstract: Accurately predicting mortality risk in intensive care unit (ICU) patients is critical for clinical decision-making. Large language models (LLMs) ar

safetyarxiv-cs-lg

In-Distribution Imagination for Model-Based Offline Reinforcement Learning

arXiv:2609.38673v1 Announce Type: new Abstract: Model-based offline reinforcement learning (MBORL) improves sample efficiency through model-generated trajectories. However, accumulative model error ca

safetyarxiv-cs-lg

Inductive Visual Logic for Few-Shot Out-Of-Distribution Adaptation in VLMs

model-releasesarxiv-cs-cv

arXiv:2609.38362v1 Announce Type: new Abstract: Generative vision-language models (VLMs) such as Qwen-VL and LLaVA achieve strong zero-shot performance on tasks overlapping with their pretraining dist

Agents

Inference Auctions

arXiv:2609.40070v1 Announce Type: cross Abstract: When inference demand exceeds available compute capacity, model providers must decide which requests should be served first. Users have different tole

agentsarxiv-cs-ai

Tutorials

InfoAgent: Traceable Generation and Repair of Evidence-Grounded Infographics

arXiv:2609.39380v1 Announce Type: new Abstract: Reliable infographic generation requires facts, symbols, and visual relations to remain consistent through rendering and revision. Correcting one elemen

tutorialsarxiv-cs-cv

Agents

Information Thermodynamics of Agents: The Work Capacity of Channels with Memory

arXiv:2504.06209v2 Announce Type: replace Abstract: Predicting future observations plays a central role in machine learning, biology, economics, and many other fields. It lies at the heart of organiza

agentsarxiv-cs-lg

Introducing Agent Droplets: everything an agent needs, one price, one bill

model-releasesdigitalocean

Last week we launched DigitalOcean Managed Agents in public preview: a managed runtime, governed access to more than 16,000 tools, serverless inference, and persistent memory and storage, all on one c

Introducing the Server Side Cloud Swift SDK

model-releasesgoogle-cloud-ai

For years, Swift was perceived mainly as a UI language tied to Apple client devices. With the release of Swift 6 and strict concurrency checking, Swift has matured into a premier systems with cloud en

Is This Evidence Decision-Critical? Learning to Verify Rule-Governed Decisions

arXiv:2609.39608v1 Announce Type: new Abstract: Rule-based reasoning, as in eligibility checks and contract reviews, requires language models to assess evidence against individual conditions and combi

researcharxiv-cs-cl

ITO: Multi-View Alignment and Training-Time Fusion for Image-Text Pretraining

arXiv:2603.02767v4 Announce Type: replace-cross Abstract: Image--text contrastive pretraining has become a dominant paradigm for visual representation learning, yet existing methods often yield repres

safetyarxiv-cs-ai

Learning Adaptive and Visually Aligned Conditions for Generative Zero-Shot Learning

arXiv:2603.06281v3 Announce Type: replace Abstract: Generative zero-shot learning (ZSL) synthesizes visual features for unseen classes by learning a semantic-conditioned generator from seen classes. S

Learning from Runtime Feedback through Failure-Bank Self-Evolution for Vision-Language-Action Models

arXiv:2609.39820v1 Announce Type: cross Abstract: Vision-language-action (VLA) models generalize broadly across robotic manipulation tasks, but complex environments require balancing task success with

Learning Normal Diffusion Dynamics for Backdoor Defense in Text-to-Image Models

arXiv:2609.39548v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to the secure deployment of text-to-image (T2I) diffusion models. Existing defenses typically detect backdoors

Learning Reliable GUI Agents under Imperfect Priors

model-releasesarxiv-cs-lg

arXiv:2609.39547v1 Announce Type: new Abstract: GUI agents built on large language and vision-language models still struggle on unseen applications and complex multi-step tasks, as completing real GUI

Learning Semantic Inpainting for Animatable Gaussian Head Avatars

arXiv:2609.38343v1 Announce Type: new Abstract: We present SInGA, a novel method for learning Semantic Inpainting for animatable Gaussian head Avatars from a single image. Existing avatar approaches o

Tutorials

Learning Skills from Historical Action Trajectories: Action Experience Dictionary for World Action Models

arXiv:2609.40219v1 Announce Type: cross Abstract: World Action Models (WAMs) couple visual dynamics prediction with action generation, yet they do not explicitly support the reuse of action experience

tutorialsarxiv-cs-ai

Learning to Reason with Compressed Context: Ground-Truth-Free Adaptation of OmniLLMs via Self-Distillation

arXiv:2609.39953v1 Announce Type: new Abstract: Omni-modal large language models (OmniLLMs) enable unified audio-video understanding, but their long multimodal token sequences make deployment computat

Learning Under Forgetting: Statistical Support-Selective Retention in Stochastic Training Dynamics

arXiv:2609.38768v1 Announce Type: cross Abstract: Prior work has shown that neural networks exhibit implicit biases toward low-complexity structure (e.g., spectral bias), memorization dynamics, and co