Search: “applications”

Gugak-VocalSet: A Multi-Genre Studio-Quality Dataset of Korean Traditional Singing with Sigimsae Annotations

arXiv:2610.15350v1 Announce Type: cross Abstract: We present Gugak-VocalSet, the first publicly available audio dataset for Korean traditional singing with dense annotations of sigimsae, a structured

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Heterogeneous Agentic Coevolution

DGX agent

arXiv:2610.16078v1 Announce Type: new Abstract: Recent advances in self-improving LLM agents have demonstrated the potential of AI systems that drive their own intelligence. However, many domain-speci

safetyarxiv-cs-ai

15 Oct 2026

HiFun: a Hierarchical Framework for Efficient Functional Dexterous Manipulation Learning

arXiv:2610.19518v1 Announce Type: new Abstract: While multi-fingered dexterous robot hands have the potential to provide human-level dexterity, using them for functional manipulation remains difficult

safetyarxiv-cs-ro

Humans vs. Machines: A Comparison With AI Agents in Software Reverse Engineering

arXiv:2610.14960v1 Announce Type: cross Abstract: Can an autonomous AI agent reverse engineer a binary as well as a skilled human analyst? Do they adopt the same strategy, and can agents scale to real

Integrated Novelty Detection Systems: From Sensor Networks to Multi-Novelty Computer Vision

arXiv:2610.19347v1 Announce Type: cross Abstract: Novelty detection is crucial in various technological and scientific domains. Its importance spans from ensuring the reliability of sensor networks to

researcharxiv-cs-cv

Joint Discrete and SE(3) Diffusion for Protein Interface Design

arXiv:2610.14699v1 Announce Type: new Abstract: The design of high-affinity, target-specific protein binders is central to the development of modern therapeutics. However, existing protein-generation

Learning to Play: Reinforcement Learning and Games

arXiv:2610.17391v1 Announce Type: new Abstract: Amazing breakthroughs in reinforcement learning have taken place. Computers teach themselves to play Chess and Go and beat world champions. There is tal

Lingdan-V2: Large language models for clinically grounded reasoning in traditional Chinese medicine

arXiv:2610.14705v1 Announce Type: cross Abstract: Large language models have advanced medical reasoning, but clinically grounded reasoning in traditional Chinese medicine (TCM) remains challenging bec

LLMRec: Benchmarking Large Language Models on Recommendation Task

arXiv:2308.12241v2 Announce Type: replace-cross Abstract: Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilit

LYNX: Analytical Program Synthesis via Grounding and Closed-Loop Refinement

arXiv:2610.14777v1 Announce Type: new Abstract: LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing a

agentsarxiv-cs-ai

MAS-Gate: Unlocking Multi-Agent System Lifecycle via Node-Centric Quantification

arXiv:2610.17613v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) can solve complex problems beyond the reach of a single agent by decomposing tasks and coordi

agentsarxiv-cs-ai

Measuring Epistemic Humility in Multimodal Large Language Models

arXiv:2509.09658v3 Announce Type: replace Abstract: Hallucinations in multimodal large language models (MLLMs), where a model generates content inconsistent with the input image, pose significant risk

MontageFlow: Physically Valid High Fidelity EEG Generation

arXiv:2610.14507v1 Announce Type: new Abstract: Generative modeling offers a promising solution to the scarcity of labeled clinical electroencephalography (EEG) data under strict privacy constraints.

Neural Supervised Clustering for Learning Individualized Treatment Rules with Many Treatments

arXiv:2610.19104v1 Announce Type: cross Abstract: Learning an individualized treatment rule (ITR) with many treatments requires estimating treatment-specific effects from limited observations per arm.

safetyarxiv-cs-lg

Occupancy Modeling via Drifting: One-Step Generation Enables Direct Policy Extraction

arXiv:2610.19883v1 Announce Type: new Abstract: The growing interest in behavior foundation models, combined with recent advancements in generative modeling, has led to an appealing recipe for reinfor

safetyarxiv-cs-lg

On Inherent Privacy of Posterior Sampling: A Unified Renyi-Divergence Framework

arXiv:2610.19573v1 Announce Type: cross Abstract: Differential Privacy (DP) provides a rigorous framework for quantifying privacy guarantees. While most methods achieve DP by injecting calibrated rand

On the Limits of Representation-Based Test-Time Adaptation for Multimodal LLMs

arXiv:2610.19892v1 Announce Type: cross Abstract: Vision-language models suffer significant accuracy drops under common corruptions. While test-time adaptation (TTA) successfully mitigates these shift

safetyarxiv-cs-cv

Pack Light, CarryOn: Building Object-Oriented Context for Long-Horizon Agents

arXiv:2610.18784v2 Announce Type: new Abstract: Long-horizon agents accumulate progress in persistent task state, yet repeatedly process interaction histories describing how that progress was achieved

PersEvalBench: Can LLM Evaluators Judge Contextually Appropriate Use of Persona Information?

model-releasesarxiv-cs-cl

arXiv:2610.19314v1 Announce Type: new Abstract: Large language model (LLM) evaluators are increasingly used to assess personalized assistants, yet whether they can reliably judge personalization has r

Plant Memory: Technical Language Processing and a Verified Maintenance Ontology for Agent-Accessible Failure Knowledge from SAP PM Work Orders

arXiv:2610.19131v1 Announce Type: cross Abstract: Maintenance work orders are the largest written record of how industrial equipment fails, yet in most plants they are close to unusable for analysis.

agentsarxiv-cs-cl

Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation

arXiv:2409.00696v4 Announce Type: replace-cross Abstract: Rating-based human evaluation has become an essential tool to accurately evaluate the impressive performance of large language models (LLMs).

ProtoArena: Can AI Agents Discover and Exploit Real-World Cross-Component Protocol Vulnerabilities?

arXiv:2610.17837v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly used for vulnerability analysis, yet existing benchmarks provide limited coverage of exploitation t

Recursive Improvement of a Differentiable Scientific Software Ecosystem

arXiv:2610.04561v2 Announce Type: replace Abstract: Differentiable programming connects scientific computation with gradient-based inference, learning and design. Extending these capabilities across a

Relational Semantic Grounding for Test-Time Discovery

arXiv:2610.14721v1 Announce Type: new Abstract: Test-Time Discovery (TTD) aims to recognize known classes and detect novel ones from a continuous unlabeled test stream after deployment. Existing TTD m

Robota-Embed: Unified VLA Embeddings for Robot In-Context Learning and Evolution

arXiv:2610.19495v1 Announce Type: cross Abstract: Retrieving useful context for a robot requires matching its task, execution stage, and the continuation that should follow. We introduce Robota-Embed,

SceneAE: Scene Generation and Reconstruction in Queryable 3D-Anchored Latent Space

arXiv:2610.19708v1 Announce Type: new Abstract: Recent video world models have increasingly adopted 3D memory mechanisms to integrate historical observations into a lightweight and persistent scene re

researcharxiv-cs-cv

Self-Evolving Agent Harness

arXiv:2610.18813v1 Announce Type: new Abstract: Harness self-evolution revises an agent's software scaffolding, including prompts, memory, workflows, and executable components, while keeping model wei

Sig-DEG for Distillation: Making Diffusion Models Faster and Lighter

arXiv:2508.16939v2 Announce Type: replace Abstract: Diffusion models achieve state-of-the-art generative performance but remain computationally expensive at inference, often requiring many discretizat

SPARC: Reliable Spatial Annotations from Robot Demonstrations at Scale

arXiv:2606.13497v2 Announce Type: replace-cross Abstract: This work introduces Spatial Annotations from Robot Demonstrations with Reliability Calibration (SPARC), a risk-aware framework that automatic

TEX-MEX: Similarity-Guided Temporal Contrastive Learning for Time Series

model-releasesarxiv-cs-lg

arXiv:2610.19557v1 Announce Type: new Abstract: Contrastive learning for time series depends on deciding which pairs of inputs should be treated as similar and dissimilar. Because few augmentations re

Text-Informed Training Data Filtering for Enhanced Virtual Flow Meter Performance

arXiv:2610.19860v1 Announce Type: cross Abstract: In sectors such as energy, aquaculture and chemical processing, the effectiveness of both mechanistic and data-driven models is frequently limited by

TextualRL: Textual Reinforcement Learning for Context Management

arXiv:2610.18216v1 Announce Type: cross Abstract: LLM agents can adapt to task feedback by revising the textual context that guides their behavior, without changing their model parameters. However, tu

Theoretical and Practical Advances in Hierarchical Bayesian Deep Learning Methodology

model-releasesarxiv-cs-lg

arXiv:2610.19074v1 Announce Type: new Abstract: Reliable uncertainty quantification remains an important challenge in AI. Hierarchical Bayesian methods provide a principled framework for this by repre

Using Evidence-Centered Design to Guide Prompt Engineering in Measurement: An Illustration with Automated Essay Scoring

arXiv:2610.15231v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) models, particularly large language models (LLMs), are increasingly used in educational settings for tasks su

Verification and Forward Invariance of Control Barrier Functions for Differential-Algebraic Systems

arXiv:2603.13509v2 Announce Type: replace-cross Abstract: Differential-algebraic equations (DAEs) arise in power networks, chemical processes, and multibody systems, where algebraic constraints encode

safetyarxiv-cs-ro

Vision: 'What Don't I Know About User's Preferences?' How Uncertainty Estimation Improves Proactive Assistant Alignment

arXiv:2610.15948v1 Announce Type: new Abstract: Proactive Smart Assistants (PSAs) increasingly use general knowledge, learned patterns from group-level data, patterns from individual user's data, and

VLRLA: Deployment-Time Adaptation of Vision-Language-Action Models through In-Context Reinforcement Learning

arXiv:2610.19517v1 Announce Type: cross Abstract: Vision-language-action (VLA) models connect visual perception and language understanding with robot control, providing a foundation for instruction-co

safetyarxiv-cs-ro

W-JEPA: Wavelet Joint-Embedding Predictive Architecture for Wearable Activity Recognition

arXiv:2610.19411v1 Announce Type: new Abstract: A major challenge in wearable device activity recognition is the heterogeneity across datasets in sensor placement, channel count, sampling rate and sub

What the Machine Invented: Mining New Mathematical Instruments from OpenAI's October 2026 Release of AI-Generated Mathematics

arXiv:2610.17090v1 Announce Type: cross Abstract: On 6 October 2026 OpenAI published an initial 722 AI-written mathematical manuscripts, organized into 372 problem families, in the public repository g

Local Ai

What We Talk About When We Talk About LLM Planning: Evidence for Two Distinct Planning Abilities

arXiv:2607.11197v2 Announce Type: replace Abstract: When LLMs exhibit uneven performance across planning tasks, these gaps are often attributed to task difficulty. We argue that this explanation is in

local-aiarxiv-cs-ai

When Messages Go Wrong: Understanding Communication Faults in LLM-Based Multi-Agent Systems

arXiv:2610.15459v1 Announce Type: cross Abstract: LLM-based multi-agent systems (LLM-MAS) use specialized agents that exchange messages to accomplish complex tasks. Their reliance on networked protoco

agentsarxiv-cs-ai

Who Should We Listen to More? Welfare-Aware Preference Acquisition for Pluralistic Alignment

arXiv:2610.19035v1 Announce Type: cross Abstract: Pluralistic alignment needs to accommodate diverse preferences under limited human feedback. Using AI simulators to label preference comparisons reduc

safetyarxiv-cs-cl

A Generalized McDiarmid Inequality: Sample Reuse and Non-Uniform Unbounded Differences

arXiv:2610.17159v1 Announce Type: cross Abstract: We develop a novel generalization of McDiarmid's concentration inequality and use it to obtain a uniform law of large numbers result and error bounds

A Note on Graphon-Signal Analysis of Graph Neural Networks

arXiv:2508.18564v2 Announce Type: replace Abstract: A recent paper, ``A Graphon-Signal Analysis of Graph Neural Networks'', by Levie, analyzed message passing graph neural networks (MPNNs) by embeddin

A physics-coupled graph neural operator for mid-plane six-component stress tensor field prediction in concrete penetration

arXiv:2610.16996v1 Announce Type: new Abstract: The penetration-resistant design of concrete structures requires the spatiotemporal evolution of the stress field within the target, whereas in design o

A text-guided vision model for enhanced recognition of small instances

arXiv:2602.19503v2 Announce Type: replace Abstract: As drone-based object detection technology continues to evolve, the demand is shifting from merely detecting objects to enabling users to accurately

Assessing the Quality of Concrete Scenarios Generated from Scenario Classes for Automated Driving

arXiv:2610.18169v1 Announce Type: cross Abstract: A scenario-based development approach has become state of the art for automated driving systems. Once a set of scenario classes covering the operation

researcharxiv-cs-ro

Asynchronous Sharpness-Aware Minimization For Fast and Accurate Deep Learning

model-releasesarxiv-cs-lg

arXiv:2503.11147v2 Announce Type: replace Abstract: Sharpness-Aware Minimization (SAM) is an optimization method that improves the generalization performance of machine learning models. Despite its ef