arXiv:2509.10018v1 Announce Type: new Abstract: With the rapid advancement of Large Language Model (LLM), LLM-based agents exhibit exceptional abilities in understanding and generating natural language, facilitating human-like collaboration and information transmission in LLM-based Multi-Agent System (MAS). High-performance LLMs are often…
arXiv:2508.02773v3 Announce Type: replace-cross Abstract: The convergence of Web3 technologies and AI agents represents a rapidly evolving frontier poised to reshape decentralized ecosystems. This paper presents the first and most comprehensive analysis of the intersection between Web3 and AI agents,…
arXiv:2509.10054v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has significantly enhanced the capabilities of Multi-Agent Systems (MAS) in supporting humans with complex, real-world tasks. However, MAS still face challenges in effective task planning when handling…
arXiv:2509.06806v4 Announce Type: replace-cross Abstract: Large language models (LLMs) possess broad world knowledge and strong general-purpose reasoning ability, yet they struggle to learn from many in-context examples on standard machine learning (ML) tasks, that is, to leverage many-shot demonstrations purely…
arXiv:2509.10104v1 Announce Type: new Abstract: The absolute dominance of Artificial Intelligence (AI) introduces unprecedented societal harms and risks. Existing AI risk assessment models focus on internal compliance, often neglecting diverse stakeholder perspectives and real-world consequences. We propose a paradigm shift…
arXiv:2509.10063v1 Announce Type: cross Abstract: Robot skill acquisition processes driven by reinforcement learning often rely on simulations to efficiently generate large-scale interaction data. However, the absence of simulation models for tactile sensors has hindered the use of tactile sensing in…
arXiv:2509.10147v1 Announce Type: new Abstract: The rapid adoption of autonomous AI agents is giving rise to a new economic layer where agents transact and coordinate at scales and speeds beyond direct human oversight. We propose the “sandbox economy” as a…
arXiv:2509.10179v1 Announce Type: cross Abstract: This study investigates the register variation in texts written by humans and comparable texts produced by large language models (LLMs). Biber’s multidimensional analysis (MDA) is applied to a sample of human-written texts and AI-created texts…
arXiv:2509.10162v1 Announce Type: new Abstract: Online planning in Markov Decision Processes (MDPs) enables agents to make sequential decisions by simulating future trajectories from the current state, making it well-suited for large-scale or dynamic environments. Sample-based methods such as Sparse Sampling…
arXiv:2509.10345v1 Announce Type: cross Abstract: Visual grounding refers to the ability of a model to identify a region within some visual input that matches a textual description. Consequently, a model equipped with visual grounding capabilities can target a wide range…
