Search: “framework”

SkillAlign: Aligning Skill Interfaces for LLM-based Agents

arXiv:2609.07255v1 Announce Type: new Abstract: Language-model agents increasingly rely on skills: reusable procedural knowledge for reasoning, tool use, and interaction. Existing work studies how ski

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SkillSpec: Intent-Masked Specification Reasoning for Agent Skill Correctness

DGX agent

arXiv:2609.06052v1 Announce Type: cross Abstract: Autonomous agent systems increasingly depend on reusable skill abstractions for consolidating experiential knowledge and domain expertise. These artif

local-aiarxiv-cs-ai

10 Sept 2026

Hardware

SkNeXt enables topology-guided neuronal reconstruction from petabyte-scale microscopy data

arXiv:2609.09832v1 Announce Type: new Abstract: Recent advances in high-resolution fluorescence and electron microscopy have enabled nanoscale imaging across increasingly large brain volumes, but the

hardwarearxiv-cs-cv

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Skynet: Workflow-Level Anomaly Detection for Agentic AI via Semantic and Structural Modeling

arXiv:2609.06835v1 Announce Type: cross Abstract: Agentic AI systems execute complex tasks through long-horizon workflows of planning, tool use, and multi-agent coordination. Task failures in these sy

local-aiarxiv-cs-ai

SocialRL: Refining LLMs' Social Intelligence through Multi-turn Reinforcement Learning and Reward Design

arXiv:2609.09764v1 Announce Type: new Abstract: Social intelligence enables agents to read social context, infer intent, and adapt over sustained dialogue. As language models become autonomous collabo

agentsarxiv-cs-cl

Applications

SQLMorph: Query Mutation and Fine-Grained Metrics for Text-to-SQL Evaluation

arXiv:2609.08950v1 Announce Type: cross Abstract: Text-to-SQL systems translate natural language queries into executable SQL, democratizing access to structured data. Despite recent advances driven by

applicationsarxiv-cs-ai

StreamAlign: Streaming Text-Aligned Speech Tokenization

arXiv:2609.09719v1 Announce Type: new Abstract: Text-aligned speech tokenization methods have emerged to better align speech tokens with LLM token spaces, enabling more effective utilization of pretra

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Structure-Aware Unsupervised Anomaly Detection for Spacecraft Telemetry with Adaptive EVT Thresholding

arXiv:2609.10017v1 Announce Type: new Abstract: Operational anomaly detection in spacecraft telemetry typically requires labeled historical anomalies or extended warm-up periods. These requirements ar

Support Discovery With Iteratively Reweighted Least Squares for Fixed-Charge Network Flow

model-releasesarxiv-cs-lg

arXiv:2609.09295v1 Announce Type: cross Abstract: The fixed-charge network flow problem (FCNFP) couples continuous flow allocation with discrete arc-activation decisions, making it a canonical but com

SwingBot: Learning Whole-Body Brachiation for Humanoid Robots

arXiv:2609.10283v1 Announce Type: new Abstract: Brachiation enables primates to move across overhead supports when ground paths are blocked, suggesting a complementary locomotion mode for robots opera

researcharxiv-cs-ro

Symbolic Informalization: Fluent, Productive, Multilingual

arXiv:2606.16893v2 Announce Type: replace Abstract: Symbolic informalization enables a reliable conversion of formal mathematics to natural language. It has the potential to make machine-checked conte

researcharxiv-cs-ai

SynThermFace: Amplifying Limited Paired Data for Visible-Thermal Face Recognition via Synthetic Data Generation

arXiv:2609.10303v1 Announce Type: new Abstract: Face recognition (FR) is a widely used modality for biometric authentication, but conventional models rely on visible-spectrum imagery and degrade when

researcharxiv-cs-cv

Test-time Prompt Refinement for Text-to-Image Models

model-releasesarxiv-cs-lg

arXiv:2507.22076v2 Announce Type: replace Abstract: Text-to-image (T2I) generation models have made significant strides but still struggle with prompt sensitivity: even minor changes in prompt wording

The convergent laboratory: when AI reasoning, autonomous experiments, high performance and quantum computing reshape chemistry

arXiv:2609.05643v1 Announce Type: new Abstract: This Comment emerges from TPC26 (https://tpc26.org), a conference convening leaders from academia, national laboratories, and industry who are reshaping

agentsarxiv-cs-ai

The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies

model-releasesarxiv-cs-ai

arXiv:2609.05514v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents are increasingly used as proxies for human participants in social science research, yet it remains unclear wheth

Time-Varying Data as Sheaves: an Invitation to Narratives

arXiv:2609.09056v1 Announce Type: new Abstract: Modern science and engineering increasingly rely on time-varying data, yet the mathematical tools used to model temporal phenomena are often developed w

agentsarxiv-cs-ai

Towards a Resilience-Theoretic Foundation for Adversarial Robustness in Industrial Control System Anomaly Detection

model-releasesarxiv-cs-ai

arXiv:2609.07244v1 Announce Type: cross Abstract: Anomaly-based intrusion detection systems in industrial control systems (ICS) and operational technology (OT) environments are increasingly required t

Towards Automatic Evolution Tree Generation from Citation Graphs

model-releasesarxiv-cs-cl

arXiv:2609.09561v1 Announce Type: new Abstract: Surveys remain the primary way researchers grasp the lineage of methods within an AI subfield, but they scale poorly against the current rate of publica

TRACE: Trajectory-robust Admission with Evidence Ordering for Efficient GUI Agents

model-releasesarxiv-cs-cv

arXiv:2609.10297v1 Announce Type: new Abstract: GUI agents accumulate high-resolution screenshots as the trajectory unfolds, increasing inference latency and memory usage. Training-free visual token p

Applications

Train Overcomplete, Deploy Compact: Scaling Recovery Capacity for Structured LLM Pruning

arXiv:2609.06974v1 Announce Type: cross Abstract: Large language models achieve strong performance across diverse tasks, but deployment remains costly because of memory, latency, and energy demands. S

applicationsarxiv-cs-ai

Unbiased and Biased Variance-Reduced Forward-Reflected-Backward Splitting Methods for Stochastic Composite Inclusions

arXiv:2603.15576v2 Announce Type: replace Abstract: This paper develops new variance-reduction techniques for the forward-reflected-backward splitting (FRBS) method to solve a class of possibly nonmon

ViBe: Visual Behavior Adaptation for Perceptive Humanoid Whole-Body Control

model-releasesarxiv-cs-ro

arXiv:2609.09918v1 Announce Type: new Abstract: Motion tracking provides a scalable recipe for humanoid whole-body control. By design, the resulting trackers lack exteroceptive feedback hence reacting

VideoTIR: Accurate Understanding for Long Videos with Efficient Tool-Integrated Reasoning

arXiv:2603.25021v3 Announce Type: replace Abstract: Existing Multimodal Large Language Models (MLLMs) often suffer from hallucinations in long video understanding (LVU), primarily due to the imbalance

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VLX-VR: An Agentic-Aware Video Reasoning Model

arXiv:2609.09985v1 Announce Type: new Abstract: Real-world video understanding requires integrating visual, audio, textual, and temporal evidence distributed across a video. Yet many pipelines use a f

agentsarxiv-cs-cl

WAPP: Safe Learning of Positive Security WAF Policies from Live Traffic

arXiv:2609.06840v1 Announce Type: cross Abstract: Web Application Firewalls (WAFs) mainly rely on signatures to detect known attacks, which can leave gaps against modified or previously unseen payload

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We're Cooked! - Probing LLM Political Alignment Via Conflict-Framed Recipe Translation

model-releasesarxiv-cs-ai

arXiv:2609.07568v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed for translation tasks, yet their implicit political positioning in such contexts remains unders

When Can LLM Digital Twins Reduce Human Measurement? From Behavioral Fidelity to Statistical Substitutability

arXiv:2609.07987v1 Announce Type: new Abstract: LLM-based digital twins promise to reduce repeated human data collection by generating person- specific responses, yet existing evaluations provide litt

researcharxiv-cs-ai

When Can One Obtain Certificates of Optimality Using Positivstellensaetze?

arXiv:2609.08736v1 Announce Type: new Abstract: We study certificates of positivity and optimality for learning problems whose objectives and constraints need not be polynomial. We isolate an axiomati

researcharxiv-cs-ai

When Does Low-Bit Quantization Preserve the Decisions of Vector Search?

arXiv:2609.09854v1 Announce Type: cross Abstract: Low-bit quantization can achieve high recall on some vector representations and fail sharply on others, while average distortion and global rank corre

Who Argues What? Joint Argument-Entity Detection and Classification in Political Debates

arXiv:2609.10192v1 Announce Type: new Abstract: Political debates are often analyzed through Argument Mining (AM) to investigate the key arguments that drive them. However, political arguments are rar

researcharxiv-cs-cl

Why Learning Rediscovers the Closed-Form Diagonal Regularizer

arXiv:2609.09656v1 Announce Type: cross Abstract: We identify a diagonal saturation principle in modal inverse problems: when truncation noise is isotropic, the Bayes-optimal Tikhonov shape is a close

World-Time Compute with Verified Code World Models

arXiv:2609.09163v1 Announce Type: new Abstract: LLMs generalize across a domain only after seeing many real, labeled examples, which most domains lack. We study a way to manufacture it cheaply. When a

WorldAgen: Unified State-Action Prediction with Test-Time World Model Training

arXiv:2609.08162v1 Announce Type: new Abstract: How can vision-language-action (VLA) models adapt to new environments where world dynamics shift? While recent research has combined world modeling and

agentsarxiv-cs-ai

XAI-Refine: An Automated Explanation-Knowledge Loop for Brain-Age Prediction

arXiv:2609.09388v1 Announce Type: new Abstract: Brain-age prediction models are commonly evaluated by predictive accuracy, yet accurate predictions alone do not establish that a model relies on reprod

3DHarnessBench: Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.06535v1 Announce Type: new Abstract: We introduce 3DHarnessBench, a benchmark that evaluates the agentic ability of frontier vision-language models (VLMs) to recover 3D geometry as Blender

A Better Spur Should Start From Each Objective

arXiv:2609.08211v1 Announce Type: cross Abstract: Real-world Multi-Objective Reinforcement Learning (MORL) often suffers from sparse rewards, reward conflicts, and late-stage reward tug-of-war, causin

Tutorials

A Joint 2D-3D Statistical Shape Model for Orthopedic Reconstruction

arXiv:2609.09010v1 Announce Type: new Abstract: Three-dimensional femoral reconstruction from radiographs supports surgical planning, implant sizing, and post-operative follow-up, but remains ill-pose

tutorialsarxiv-cs-cv

A Multi-Modal Perception Pipeline for Object Detection and Tracking in Autonomous Racing

arXiv:2609.08338v1 Announce Type: new Abstract: Object detection and tracking are fundamental components of perception systems for autonomous driving. Achieving robust performance under adverse condit

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A Theoretical Analysis of Generalization Dynamics in Neural Networks under Gradient Descent with Weight Decay

arXiv:2609.07755v1 Announce Type: new Abstract: Understanding generalization remains a central challenge in machine learning because it requires jointly considering data, architecture, and training dy

A*-Thought-V2: Efficient Latent Reasoning via Geometric Dynamics of LLM

arXiv:2609.07821v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) improves the reasoning ability of Large Language Models (LLMs) but incurs substantial computation and context costs. Existing m

Applications

A4A: Cross-Embodiment Transfer of Action-Oriented 4D Affordances from Human Demonstrations

arXiv:2609.05892v1 Announce Type: new Abstract: Human demonstrations contain rich manipulation knowledge, but it remains unclear what information can be transferred effectively to robot control. Exist

applicationsarxiv-cs-ro

Accelerated Spatio-Temporal Gaussian Rendering via Kinematic and Semantic Priors

arXiv:2605.25909v2 Announce Type: replace Abstract: Reconstructing dynamic 3D scenes from multi-view videos is a foundational task for robotics, AR/VR, and digital twins. While 3D Gaussian Splatting (

researcharxiv-cs-cv

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AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization

arXiv:2508.04175v2 Announce Type: replace Abstract: While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities across diverse domains, their application to specialized anomaly

local-aiarxiv-cs-cv

Adapting Technical-Service LLM Agents with Latent Logic Augmentation, Robust Noise Reduction, and Hybrid Reward Modeling

arXiv:2603.18074v2 Announce Type: replace Abstract: Technical-service LLM agents are entering production workflows, where value depends on whether engineers adopt generated replies. Service tickets hi

Adaptively Incorporating Directional Hints into Zeroth-Order Optimization

arXiv:2609.08277v1 Announce Type: new Abstract: We study zeroth-order optimization of non-convex functions with the aid of directional hints, which are cheap but potentially inaccurate approximations

Tutorials

ADELE - Adaptive Delaunay Grids for High-Fidelity Mesh-Native Reconstruction

arXiv:2609.06723v1 Announce Type: new Abstract: Meshes remain the most practical representation for geometry reasoning and integration into graphics pipelines, yet existing reconstruction methods stru

tutorialsarxiv-cs-cv

Agentic Visual Generation: From Generative Models to Agentic Control

arXiv:2609.06758v1 Announce Type: new Abstract: Visual generation is evolving from generative models used through a single invocation into agentic control processes that can plan, select tools, inspec

agentsarxiv-cs-cv

All for 1-Bit: Towards Genuine 1-Bit Post-Training Quantization for LLMs

model-releasesarxiv-cs-lg

arXiv:2609.06161v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable progress, yet their massive storage and memory-bandwidth demands still hinder efficient deployment