arXiv AI
Jun 12
A Tutorial on World Models and Physical AI
arXiv:2606. 12783v1 Announce Type: new Abstract: World modeling is emerging as a central principle for building intelligent systems capable of prediction, reasoning, and decision making.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv AI
Jun 12
SAIGuard: Communication-State Simulation for Proactive Defense of LLM Multi-Agent Systems
arXiv:2606. 12474v1 Announce Type: cross Abstract: LLM-based multi-agent systems (MAS) solve complex tasks through inter-agent collaboration, but their communication-driven nature also allows security risks to spread across agents and trigger system-wide failures.
arXiv AI
Jun 12
Teach-and-Repeat: Accurately Extracting Operational Knowledge from Mobile Screen Demonstrations to Empower GUI Agents
arXiv:2606. 12817v1 Announce Type: new Abstract: Understanding the digital world on mobile devices is shifting from static UI perception to dynamic action comprehension.
arXiv AI
Jun 12
The Containment Gap: How Deployed Agentic AI Frameworks Fail Public-Facing Safety Requirements
arXiv:2606. 12797v1 Announce Type: new Abstract: Agentic large language model systems that autonomously invoke tools, maintain persistent memory, and execute multi-step plans are increasingly deployed in public-facing domains, including government services, healthcare triage, and financial advising.
arXiv AI
Jun 12
Multi-Agent Reinforcement Learning from Delayed Marketplace Feedback for Objective-Weight Adaptation in Three-Sided Dispatch
arXiv:2606. 13604v1 Announce Type: new Abstract: Dispatch in three-sided marketplaces provides a natural setting for reinforcement learning from world feedback: decisions are evaluated by delayed operational outcomes such as delivery speed, courier utilization, and merchant congestion.
arXiv AI
Jun 12
WISE: A Long-Horizon Agent in Minecraft with Why-Which Reasoning
arXiv:2606. 12852v1 Announce Type: new Abstract: Rapid advances have been made in developing general-purpose embodied agent in environments like Minecraft through the adoption of LLM-augmented hierarchical approaches.
arXiv AI
Jun 12
Topical Phase Transitions in Artificial Intelligence Research: Large-Scale Evidence and an Early-Warning Signature for Emerging Topics
arXiv:2606. 12828v1 Announce Type: new Abstract: Do research topics in artificial intelligence grow gradually, or do they advance through abrupt, detectable jumps?
arXiv AI
Jun 12
Can I Buy Your KV Cache?
arXiv:2606. 13361v1 Announce Type: new Abstract: Right now, across the world, AI agents are repeating the same absurd act: to read one document, they each recompute it from scratch.
arXiv AI
Jun 12
A Three-Layer Framework for AI in Scientific Discovery
arXiv:2606. 13566v1 Announce Type: new Abstract: Current discussions of AI in scientific discovery are often dominated by two visible capabilities: search over existing knowledge and execution through optimization, simulation, and automation.
arXiv AI
Jun 12
PersonaDrive: Human-Style Retrieval-Augmented VLA Agents for Closed-Loop Driving Simulation
arXiv:2606. 12616v1 Announce Type: new Abstract: Closed-loop driving simulators typically populate their environments with non-ego traffic agents that behave largely the same way, produced either by rule-based traffic managers or by learned models trained toward a single behavioral mode.
arXiv AI
Jun 12
GeoNatureAgent Benchmark: Benchmarking LLM Agents for Environmental Geospatial Analysis Across Frontier and Open-Weight Foundation Models
arXiv:2606. 12821v1 Announce Type: new Abstract: Environmental scientists spend disproportionate effort on data wrangling rather than analysis, and AI agents that automate geospatial workflows remain unvalidated: no benchmark evaluates agents operating through structured tool calling against real APIs.
arXiv AI
Jun 12
MemRefine: LLM-Guided Compression for Long-Term Agent Memory
arXiv:2606. 13177v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly expected to operate over long-term interactions, where information from past dialogues must be preserved and recalled to support future tasks.
arXiv AI
Jun 12
TrajGenAgent: A Hierarchical LLM Agent for Human Mobility Trajectory Generation
arXiv:2606. 12657v1 Announce Type: new Abstract: Human mobility data is important for transportation, urban planning, and epidemic control, but large-scale trajectory collection is often costly and privacy-constrained, motivating realistic synthetic trajectory generation.
arXiv AI
Jun 12
IterCAD: An Iterative Multimodal Agent for Visually-Grounded CAD Generation and Editing
arXiv:2606. 13368v1 Announce Type: new Abstract: Computer-Aided Design is pivotal in modern manufacturing, yet existing automated methods predominantly rely on open-loop, one-shot generation, creating a mismatch with iterative real-world practices.
arXiv AI
Jun 12
SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning
arXiv:2606. 13673v1 Announce Type: cross Abstract: Spatial reasoning, the ability to determine where objects are, how they relate, and how they move in 3D, remains a fundamental challenge for vision-language models (VLMs).
arXiv AI
Jun 12
G-Long: Graph-Enhanced Memory Management for Efficient Long-Term Dialogue Agents
arXiv:2606. 13115v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have advanced open-domain dialogue systems, maintaining long-term consistency remains a challenge due to inherent limitations in long-context reasoning and the inefficiency of processing extensive raw text.
arXiv AI
Jun 12
The Illusion of Multi-Agent Advantage
arXiv:2606. 13003v1 Announce Type: new Abstract: Prevailing wisdom posits that Multi-Agent Systems (MAS) are superior to Single-Agent Systems (SAS), citing advantages like context protection, parallel processing and distributed decision-making.
arXiv AI
Jun 12
Agentic MPC for Semantic Control System Resynthesis
arXiv:2606. 12774v1 Announce Type: cross Abstract: While MPC effectively handles structured, diverse, and low-level specifications, it lacks the capability to dynamically incorporate high-level contextual information such as social norms, user intent, or natural language instructions.
arXiv AI
Jun 12
Mana: Dexterous Manipulation of Articulated Tools
arXiv:2606. 13677v1 Announce Type: cross Abstract: Articulated tool manipulation remains a major challenge in dexterous robotics due to the need to coordinate internal degrees of freedom and contact-rich interactions.
arXiv AI
Jun 12
Multiagent Protocols with Aggregated Confidence Signals
arXiv:2606. 13591v1 Announce Type: new Abstract: Confidence is used for reliability, oversight, and a range of downstream decision tasks in Natural Language Processing (NLP), yet no existing method produces or evaluates a confidence for the output of a multiagent system.