Search: “papers”

Multi-Agent Reinforcement Learning for Online Traffic Scheduling in Time-Sensitive Application

arXiv:2608.05346v1 Announce Type: cross Abstract: Time-sensitive networking (TSN) is increasingly integrated into mobile edge computing (MEC) to support applications with stringent latency requirement

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Observation-Grounded Self-Predictive Reinforcement Learning for Visual Continuous Control

DGX agent

arXiv:2608.05989v1 Announce Type: new Abstract: Sample-efficient policy learning from pixels is a long-standing challenge in reinforcement learning (RL). Recent dynamics-based representation learning

safetyarxiv-cs-lg

7 Aug 2026

One Ranking, Any Budget: Matryoshka Evidence-to-Context Frame Selection for Long-Video Understanding

arXiv:2608.05707v1 Announce Type: new Abstract: Frame selection is essential for applying Large Multimodal Models (LMMs) to long videos due to severe frame redundancy and limited context windows. Sinc

Hardware

Parallel-in-Time Nonlinear Optimal Control via GPU-native Sequential Convex Programming

arXiv:2603.10711v3 Announce Type: replace Abstract: Real-time solution of nonlinear optimal control problems remains challenging on embedded robotic hardware, where conventional solvers often rely on

hardwarearxiv-cs-ro

Patient Pose Assessment Using a CT-Based Framework for Synthetic Data Generation

arXiv:2608.06126v1 Announce Type: new Abstract: An adequate diagnostic quality of radiographs is essential for reliable diagnoses and treatment planning. The patient's pose during radiography is one o

Applications

Persona-Pruner: Sculpting Lightweight Models for Role-Playing

arXiv:2606.14695v2 Announce Type: replace-cross Abstract: Language Models (LMs) have shown remarkable potential as role-playing chatbots, delivering consistent, stylized interactions when given a spec

applicationsarxiv-cs-cl

Position: It's Time to Optimize LLMs for Self-Consistency

arXiv:2608.05188v1 Announce Type: cross Abstract: Despite ever-increasing sophistication in language model (LM) pre- and post-training pipelines, many important failures persist: models overcondition

Posture and Sustainment Optimization Under Adversarial Uncertainty

arXiv:2608.05256v1 Announce Type: new Abstract: Pre-commitment posture, the assignment of military assets to theater locations before conflict scenarios resolve, is a critical and formally unsolved pr

Agents

PPDL: LLM-Based Flows as Probabilistic Programs

arXiv:2608.05234v1 Announce Type: new Abstract: Building reliable applications that leverage large language models (LLMs) remains a significant challenge. While LLMs offer impressive capabilities acro

agentsarxiv-cs-lg

Predicting Social Media User Actions: A Hybrid Approach for Common and Rare Behavior Prediction on Bluesky

arXiv:2511.17241v2 Announce Type: replace Abstract: Understanding and predicting user behavior on social media platforms is crucial for content recommendation and platform design. While existing appro

ProDVI: Programmatic Dynamics Priors for Value Network Initialization

arXiv:2608.06015v1 Announce Type: cross Abstract: Deep Reinforcement Learning (RL) is notoriously sample inefficient. One contributing factor is that RL agents are typically initialized from scratch,

Tutorials

Quantum-Structured World Models (QSWMs) for Predictive Latent Dynamics

arXiv:2608.05371v1 Announce Type: new Abstract: World models learn latent states that summarize interaction histories, evolve over time, and support prediction, simulation, or planning. Most existing

tutorialsarxiv-cs-lg

Tutorials

Reversible Unlearnable Examples: Towards the Copyright Protection in Deep Learning Era

arXiv:2608.06211v1 Announce Type: cross Abstract: Significant advancements in deep learning have been made possible by the utilization of large datasets, underscoring the critical importance of copyri

tutorialsarxiv-cs-cv

Robot Learning from Human Demonstrations: Handwritten Alphabet Trajectories and Human-Likeness Evaluation

model-releasesarxiv-cs-lg

arXiv:2608.06221v1 Announce Type: cross Abstract: Learning from demonstration (LfD) provides a developmental framework through which robots can develop motor skills by observing and imitating human dy

Runtime Observability for Heterogeneous Attention Memory

arXiv:2608.05863v1 Announce Type: new Abstract: Modern models no longer keep a plain KV cache: latent caches, learned sparse selectors and recurrent states each carry the model's memory in a different

Shape-Aware Oriented Bounding Box (OBB) to Horizontal Bounding Box (HBB) Conversion

arXiv:2608.05858v1 Announce Type: new Abstract: Accurate object detection in aerial and satellite imagery is dependent upon the bounding box representation. This is especially true for spatially orien

Sparse Mutual Information Graph Averaging for Improving Random Indexing Embeddings

arXiv:2608.05724v1 Announce Type: new Abstract: Sparse word embedding pipelines can avoid dense co-occurrence matrix materialization, dense factorization, and gradient training while still relying on

Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for their Ability to Replicate a Human Survey with Synthetic Data

arXiv:2603.00059v3 Announce Type: replace-cross Abstract: How well can AI-derived synthetic research data replicate the responses of human participants? An emerging literature has begun to engage with

Task-Conditional Flow Matching for Balanced Multilingual Text Embedding Adaptation

arXiv:2608.05785v1 Announce Type: cross Abstract: Multilingual text embedding models are commonly adapted using a single training objective across diverse tasks, despite different tasks requiring fund

The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AI

arXiv:2608.05173v1 Announce Type: cross Abstract: As AI capabilities advance, AI systems will pose greater risks to national security and potentially humanity as a whole. Governments may eventually co

Threshold-Based Early Stopping of Accumulations in Neural Networks with Binary Activation

model-releasesarxiv-cs-lg

arXiv:2608.06177v1 Announce Type: new Abstract: Binary neural networks are very attractive for constrained deployment, enabling small footprint and low-power inference. For binary activations, the dot

Local Ai

Topometric Autonomous Vehicle Localization by Combining Visual Embeddings and Feed-Forward 3D Models

arXiv:2608.06021v1 Announce Type: new Abstract: Effective Visual Localization (VL) requires a map of the environment that combines compactness for efficient scalability with robustness against visual

local-aiarxiv-cs-ro

Trust-Based Incentive Mechanisms in Semi-Decentralized Federated Learning Systems

arXiv:2602.08290v2 Announce Type: replace-cross Abstract: In federated learning (FL), decentralized model training allows multi-ple participants to collaboratively improve a shared machine learning mo

Universal Concept Disruption for SAM3 Image Segmentation

arXiv:2608.05983v1 Announce Type: new Abstract: SAM3 extends promptable segmentation from geometry-driven mask prediction to open-vocabulary concept segmentation, where a text-conditioned grounding mo

What Drives Test-Time Adaptation for CLIP? A Controlled Empirical Study from an Update Perspective

model-releasesarxiv-cs-cv

arXiv:2606.14299v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) such as CLIP have become a standard backbone for open-vocabulary recognition, yet their zero-shot predictions remain v

Where Models Converge and Humans Diverge: A Coverage Framework for Distributional Pluralism in Open-Ended Generation

arXiv:2608.05576v1 Announce Type: new Abstract: When a large language model (LLM) writes Harry Potter fanfiction, it reliably produces fundamental elements of the Hogwarts universe, such as recognizab

Applications

A GitOps-Driven Annotation Catalog for Fully Automatic Railway Operations

arXiv:2608.04724v1 Announce Type: cross Abstract: Automatic train operation (ATO) at grade of automation 3 and above (GoA3-GoA4) requires robust AI-based perception systems capable of reliably detecti

applicationsarxiv-cs-cv

A Modular Part-of-Speech Tagger for Scottish Gaelic using spaCy

arXiv:2608.04808v1 Announce Type: new Abstract: Part-of-speech tagging for low-resource languages remains challenging due to limited annotated data, especially for linguistically complex languages. Ga

A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents

arXiv:2602.06052v4 Announce Type: replace-cross Abstract: Research in artificial intelligence is shifting from model innovations and benchmark scores towards problem definition and rigorous real-world

ABSeeker: Training Long-Horizon Search Agents via Answer-Backtracked Credit Assignment

arXiv:2608.05102v1 Announce Type: new Abstract: Long-horizon search agents must make multiple sequential actions (steps) to search, retrieve, verify, and integrate evidence to reach a final answer. Ho

Adaptive Finite-Budget Training for CVaR Risk-Aware Q-Learning

model-releasesarxiv-cs-lg

arXiv:2608.04305v1 Announce Type: new Abstract: Risk-aware Q-learning (RaQL) provides a model-free, two-timescale estimator for dynamic risk objectives, but its finite-budget behavior remains fragile:

Hardware

An Explainable LLM Agent Layer for Open-World Anomaly Detection in Oil Wells

arXiv:2608.04041v1 Announce Type: new Abstract: Open-World Learning (OWL) pipelines for oil well anomaly detection have recently been shown to combine autoencoder-based detection, multiclass classific

hardwarearxiv-cs-lg

An Inline Control Architecture for Language Models in Intelligent Transportation Systems

arXiv:2608.04065v1 Announce Type: cross Abstract: Vehicle-to-everything (V2X) systems increasingly incorporate large language models (LLMs) for semantic tasks such as message summarization, operator a

Argus: A General-Purpose Agentic Runtime for Long-Horizon Reasoning

arXiv:2608.05144v1 Announce Type: new Abstract: Long-horizon reasoning requires an agentic runtime that can persist when evidence supports its current approach and pivot when measurements reveal failu

ATLAS: Adaptive Topological Learning with Abstract Successors for Continual Learning

arXiv:2608.04334v1 Announce Type: cross Abstract: Contemporary model-free reinforcement learning algorithms can achieve very high performance, but have low sample efficiency and are not robust to chan

Attention, Anomalies! Handling Attention Layers in Unsupervised Federated Outlier Detection

arXiv:2608.04753v1 Announce Type: new Abstract: Attention layers are the backbone of today's most powerful and impactful models. Models with multi-million and billion parameters rely on contextual kno

researcharxiv-cs-lg

Attention Fusion for Bridge Deck Delamination Detection

arXiv:2512.20113v4 Announce Type: replace Abstract: Subsurface delaminations in reinforced concrete bridge decks escape conventional visual inspection, and the two principal sensing techniques used to

safetyarxiv-cs-cv

Beyond the QBER Threshold: A Temporal QBER Based Machine Learning Framework for Multi Attack Detection in BB84 QKD

arXiv:2608.04047v1 Announce Type: cross Abstract: Conventional BB84 Quantum Key Distribution (QKD) systems rely on a fixed 11% Quantum Bit Error Rate (QBER) threshold to detect eavesdropping. However,

Can Post-Training Transform LLMs into Causal Reasoners?

arXiv:2602.06337v2 Announce Type: replace-cross Abstract: Causal inference is essential for decision-making but remains challenging for non-experts. While large language models (LLMs) show promise in

ColorFD: A Finite-Difference Guided Black-Box Physical Adversarial Attack for Remote Sensing Object Detection

arXiv:2608.04559v1 Announce Type: new Abstract: Although deep neural network-based remote sensing object detectors have achieved strong performance, they remain vulnerable to adversarial perturbations

Cooking beyond Frames: A Stereo Event Camera Dataset in the Kitchen

model-releasesarxiv-cs-cv

arXiv:2608.04865v1 Announce Type: new Abstract: Event cameras, also known as neuromorphic cameras, have gained significant attention in recent years due to their high temporal resolution, high dynamic

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation

arXiv:2608.04333v1 Announce Type: new Abstract: Large language model (LLM) configuration evaluation is challenging due to limited evaluation budgets, varying costs, and multiple competing objectives.

researcharxiv-cs-lg

Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability

arXiv:2503.14833v2 Announce Type: replace-cross Abstract: One of the bottlenecks in robotic intelligence is the instability of neural network models. This leads to risks when applying intelligence in

DataRx: Missingness-Aware Sampling for Safer Large Language Model Task-Specific Fine-Tuning

arXiv:2608.04322v1 Announce Type: new Abstract: Task-specific fine-tuning can improve the performance of large language models (LLMs) on downstream tasks. However, our study reveals that task-specific

safetyarxiv-cs-cl

Easy to Complete, Hard to Choose: Investigating LLM Performance on the ProverbIT Benchmark

arXiv:2608.04670v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed computational linguistics and achieved remarkable performance across numerous natural language processin

Agents

Embedding Large Language Models into Flow Controls: An Agentic Framework for Adaptive and Trustworthy Automated Cooking

arXiv:2608.04768v1 Announce Type: new Abstract: Automated cooking robots have traditionally relied on predefined procedures and rule-based control, ensuring stable execution but offering limited perso

agentsarxiv-cs-cv

Enabling Urgency-aware Robot Swarm Intralogistics using Smart IoT Tags

arXiv:2608.04721v1 Announce Type: new Abstract: Warehouse items differ in how urgently they must be moved: perishable goods, pharmaceutical shipments, and just-in-time production materials must be del

safetyarxiv-cs-ro

EndoVLM: An Endoscopy Vision-Language Pre-training Model via Anatomy-Guided Sparsity and Progressive Alignment

arXiv:2608.04472v1 Announce Type: cross Abstract: The development of foundation models (FMs) is crucial for advancing endoscopic image analysis. However, existing endoscopy FMs mainly rely on self-sup