Search: “agents”

Governing AI-Assisted Security Operations: A Design Science Framework for Operational Decision Support

arXiv:2605.09534v1 Announce Type: cross Abstract: Engineering managers increasingly must decide how to introduce generative artificial intelligence (AI), retrieval-augmented generation, and coding age

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Safety

Intelligent Autonomous Orchestration for Distributed Cloud Resources using Complex-Stability Analysis

DGX agent

arXiv:2605.08139v1 Announce Type: cross Abstract: In modern distributed cloud environments, efficient resource allocation is required as traditional scaling mechanisms are often subject to cloud thras

safetyarxiv-cs-ai

12 May 2026

Is Your Driving World Model an All-Around Player?

arXiv:2605.10858v1 Announce Type: new Abstract: Today's driving world models can generate remarkably realistic dash-cam videos, yet no single model excels universally. Some generate photorealistic tex

LEAF-SQL: Level-wise Exploration with Adaptive Fine-graining for Text-to-SQL Skeleton Prediction

model-releasesarxiv-cs-cl

arXiv:2605.09295v1 Announce Type: new Abstract: Text-to-SQL translates natural language questions into executable SQL queries, enabling intuitive database access for non-experts. While large language

Learning from Trials and Errors: Reflective Test-Time Planning for Embodied LLMs

arXiv:2602.21198v2 Announce Type: replace-cross Abstract: Embodied LLMs endow robots with high-level task reasoning, but they cannot reflect on what went wrong or why, turning deployment into a sequen

NEXUS: Continual Learning of Symbolic Constraints for Safe and Robust Embodied Planning

arXiv:2605.09387v1 Announce Type: new Abstract: While Large Language Models (LLMs) have catalyzed progress in embodied intelligence, a fundamental gap between their inherent probabilistic uncertainty

ProactBench: Beyond What The User Asked For

arXiv:2605.09228v1 Announce Type: cross Abstract: Most LLM benchmarks score how well a model responds to explicit requests. They leave unmeasured a different conversational ability: noticing and actin

Reinforcement Learning for Scalable and Trustworthy Intelligent Systems

arXiv:2605.08378v1 Announce Type: cross Abstract: Reinforcement learning has become a powerful paradigm for improving the capability of intelligent systems, but its practical deployment faces two cent

UniUncer: Unified Dynamic Static Uncertainty for End to End Driving

arXiv:2603.07686v2 Announce Type: replace-cross Abstract: End-to-end (E2E) driving has become a cornerstone of both industry deployment and academic research, offering a single learnable pipeline that

local-aiarxiv-cs-cv

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems

arXiv:2506.04565v2 Announce Type: replace-cross Abstract: Compound AI Systems (CAIS) are an emerging paradigm that integrates large language models (LLMs) with external components, including retriever

GazeVLM: Active Vision via Internal Attention Control for Multimodal Reasoning

arXiv:2605.07817v1 Announce Type: cross Abstract: Human visual reasoning is governed by active vision, a process where metacognitive control drives top-down goal-directed attention, dynamically routin

Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs

model-releasesarxiv-cs-lg

arXiv:2605.07961v1 Announce Type: new Abstract: Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated

MathlibPR: Pull Request Merge-Readiness Benchmark for Formal Mathematical Libraries

arXiv:2605.07147v1 Announce Type: cross Abstract: The ecosystem of Lean and Mathlib has become the de facto standard for large language model (LLM) assisted formal reasoning with remarkable successes

Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners

arXiv:2605.08019v1 Announce Type: new Abstract: Humans rapidly learn abstract knowledge when encountering novel environments and flexibly deploy this knowledge to guide efficient and intelligent actio

Scalable Option Learning in High-Throughput Environments

arXiv:2509.00338v3 Announce Type: replace-cross Abstract: Hierarchical reinforcement learning (RL) has the potential to enable effective decision-making over long timescales. Existing approaches, whil

researcharxiv-cs-ai

SCENE: Recognizing Social Norms and Sanctioning in Group Chats

model-releasesarxiv-cs-cl

arXiv:2605.07823v1 Announce Type: new Abstract: Online group chats are social spaces with implicit behavior patterns that, when broken, are often met with social sanctioning from the group. The abilit

Self Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale

arXiv:2605.07022v1 Announce Type: new Abstract: Manually curated biomedical repositories -- spanning bioactivity, genomics, and chemistry -- are expensive to maintain, lag behind primary literature, a

local-aiarxiv-cs-lg

Towards Highly-Constrained Human Motion Generation with Retrieval-Guided Diffusion Noise Optimization

arXiv:2605.08054v1 Announce Type: new Abstract: Generating human motion that satisfies customized zero-shot goal functions, enabling applications such as controllable character animation and behavior

researcharxiv-cs-cv

Deco: Extending Personal Physical Objects into Pervasive AI Companion through a Dual-Embodiment Framework

arXiv:2605.03882v1 Announce Type: cross Abstract: Individuals frequently form deep attachments to physical objects (e.g., plush toys) that usually cannot sense or respond to their emotions. While AI c

researcharxiv-cs-ai

Information Coordination as a Bridge: A Neuro-Symbolic Architecture for Reliable Autonomous Driving Scene Understanding

arXiv:2605.04475v1 Announce Type: new Abstract: Reliable autonomous driving requires scene understanding that is semantically consistent across heterogeneous sensors and verifiable at the reasoning st

LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems

model-releasesarxiv-cs-lg

arXiv:2605.04323v1 Announce Type: new Abstract: Understanding soil is fundamental to agriculture, carbon cycling, and environmental sustainability, yet progress is limited by fragmented and heterogene

Safety Must Precede the Deployment of Open-Ended AI

arXiv:2502.04512v3 Announce Type: replace Abstract: AI advancements have been significantly driven by a combination of foundation models and curiosity-driven learning aimed at increasing capability an

Learning Reactive Dexterous Grasping via Hierarchical Task-Space RL Planning and Joint-Space QP Control

arXiv:2605.03363v1 Announce Type: new Abstract: In this work, we propose a hybrid hierarchical control framework for reactive dexterous grasping that explicitly decouples high-level spatial intent fro

safetyarxiv-cs-ro

MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers

arXiv:2602.00933v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) is rapidly becoming the standard interface for Large Language Models (LLMs) to discover and invoke external t

MINT: Minimal Information Neuro-Symbolic Tree for Objective-Driven Knowledge-Gap Reasoning and Active Elicitation

arXiv:2602.05048v2 Announce Type: replace Abstract: Joint planning through language-based interactions is a key area of human-AI teaming. Planning problems in the open world often involve various aspe

Optimal control of the future via prospective learning with control

model-releasesarxiv-cs-lg

arXiv:2511.08717v4 Announce Type: replace-cross Abstract: Optimal control of the future is the next frontier for AI. Current approaches to this problem are typically rooted in reinforcement learning (

Tutorials

Preemptive Solving of Future Problems: Multitask Preplay in Humans and Machines

arXiv:2507.05561v2 Announce Type: replace Abstract: Humans can pursue a near-infinite variety of tasks, but typically can only pursue a small number at the same time. We hypothesize that humans levera

tutorialsarxiv-cs-lg

AI Alignment via Incentives and Correction

arXiv:2605.01643v1 Announce Type: new Abstract: We study AI alignment through the lens of law-and-economics models of deterrence and enforcement. In these models, misconduct is not treated as an exter

NaviMaster: Learning a Unified Policy for GUI and Embodied Navigation Tasks

arXiv:2508.02046v4 Announce Type: replace-cross Abstract: Recent advances in Graphical User Interface (GUI) and embodied navigation have driven progress, yet these domains have largely evolved in isol

Hardware

The extit{Silicon Society} Cookbook: Design Space of LLM-based Social Simulations

arXiv:2605.00197v1 Announce Type: cross Abstract: Studies attempting to simulate human behavior with extit{Silicon Societies} grow in numbers while LLM-only social networks have started appearing outs

hardwarearxiv-cs-ai

TRAP: Tail-aware Ranking Attack for World-Model Planning

arXiv:2605.01950v1 Announce Type: new Abstract: World models enable long-horizon planning by internally generating and evaluating imagined trajectories, making them a promising foundation for generali

Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning

arXiv:2605.00347v1 Announce Type: cross Abstract: Given the rapidly growing capabilities of vision-language models (VLMs), extending them to interactive decision-making tasks such as video games has e

4 May 2026

Structure Liberates: How Constrained Sensemaking Produces More Novel Research Output

arXiv:2605.00557v1 Announce Type: new Abstract: Scientific discovery is an extended process of ideation--surveying prior work, forming hypotheses, and refining reasoning--yet existing approaches treat

4 May 2026

FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting

arXiv:2604.27974v1 Announce Type: new Abstract: Despite the rapid progress of large vision-language models (LVLMs), fine-grained, state-conditioned GUI interaction remains challenging. Current evaluat

HAVEN: Hybrid Automated Verification ENgine for UVM Testbench Synthesis with LLMs

arXiv:2604.27643v1 Announce Type: cross Abstract: Integrated Circuit (IC) verification consumes nearly 70% of the IC development cycle, and recent research leverages Large Language Models (LLMs) to au

researcharxiv-cs-ai

Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

arXiv:2604.28158v1 Announce Type: new Abstract: Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of meth

Learning-to-Explain through 20Q Gaming: An Explainable Recommender for Cybersecurity Education

arXiv:2604.26964v1 Announce Type: cross Abstract: The growing sophistication of contemporary cyber threats necessitates a more effective and adaptive approach to cybersecurity training. Intuitive and

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

model-releasesarxiv-cs-cl

arXiv:2604.27488v1 Announce Type: new Abstract: We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-

SpatialGrammar: A Domain-Specific Language for LLM-Based 3D Indoor Scene Generation

arXiv:2604.27555v1 Announce Type: new Abstract: Automatically generating interactive 3D indoor scenes from natural language is crucial for virtual reality, gaming, and embodied AI. However, existing L

Omni2Sound: Towards Unified Video-Text-to-Audio Generation

arXiv:2601.02731v3 Announce Type: replace-cross Abstract: Training a unified model integrating video-to-audio (V2A), text-to-audio (T2A), and joint video-text-to-audio (VT2A) generation offers signifi

30 Apr 2026

Probe-then-Plan: Environment-Aware Planning for Industrial E-commerce Search

arXiv:2603.15262v2 Announce Type: replace Abstract: Modern e-commerce search is evolving to resolve complex user intents. While Large Language Models (LLMs) offer strong reasoning, existing LLM-based

30 Apr 2026

Applications

The hidden risks of temporal resampling in clinical reinforcement learning

arXiv:2602.06603v3 Announce Type: replace Abstract: Reinforcement learning (RL) is a type of artificial intelligence for making optimal choices. In healthcare, researchers generally use offline RL (OR

applicationsarxiv-cs-lg

30 Apr 2026

A Deep Reinforcement Learning Approach to Automated Stock Trading, using xLSTM Networks

arXiv:2503.09655v2 Announce Type: replace-cross Abstract: Traditional Long Short-Term Memory (LSTM) networks are effective for handling sequential data but have limitations such as gradient vanishing

A Survey on LLM-based Conversational User Simulation

arXiv:2604.24977v1 Announce Type: new Abstract: User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary

From World-Gen to Quest-Line: A Dependency-Driven Prompt Pipeline for Coherent RPG Generation

arXiv:2604.25482v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for narrative generation, but their use in complex, multi-layered role-playing game (RPG) world

local-aiarxiv-cs-cl

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

arXiv:2604.25296v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional

safetyarxiv-cs-cl

OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning

arXiv:2511.20211v2 Announce Type: replace Abstract: Transparency-aware generation requires modeling not only RGB appearance but also alpha-based opacity and cross-layer composition, which are essentia

local-aiarxiv-cs-cv

VISION-SLS: Safe Perception-Based Control from Learned Visual Representations via System Level Synthesis

arXiv:2604.24894v1 Announce Type: cross Abstract: We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction gu

safetyarxiv-cs-cv