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arXiv:2602.13516v1 Announce Type: new Abstract: LLM-powered agents are beginning to automate user's tasks across the open web, often with access to user resources such as …
arXiv:2602.13530v1 Announce Type: new Abstract: Humans excel at remembering concrete experiences along spatiotemporal contexts and performing reasoning across those events, i.e., the capacity for episodic …
arXiv:2602.13559v1 Announce Type: new Abstract: To fulfill user instructions, autonomous web agents must contend with the inherent complexity and volatile nature of real-world websites. Conventional …
arXiv:2602.13568v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in environments where they encounter social information such as other agents' answers, tool outputs, …
arXiv:2602.13583v1 Announce Type: new Abstract: Rule learning-based models are widely used in highly interpretable scenarios due to their transparent structures. Inductive logic programming (ILP), a …
arXiv:2602.13587v1 Announce Type: new Abstract: This monograph reports a multi-agent proof sprint on ten research-level problems, combining rapid draft generation with adversarial verification, targeted repair, …
arXiv:2602.13594v1 Announce Type: new Abstract: Agentic AI require persistent memory to store user-specific histories beyond the limited context window of LLMs. Existing memory systems use …
arXiv:2602.13595v1 Announce Type: new Abstract: Neural scaling laws provide a predictable recipe for AI advancement: reducing numerical precision should linearly improve computational efficiency and energy …
arXiv:2602.13616v1 Announce Type: new Abstract: We propose DiffusionRollout, a novel selective rollout planning strategy for autoregressive diffusion models, aimed at mitigating error accumulation in long-horizon …
arXiv:2602.13639v1 Announce Type: new Abstract: With recent breakthroughs in large language models (LLMs) for reasoning, planning, and complex task generation, artificial intelligence systems are transitioning …
arXiv:2602.13653v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have substantially driven the progress of autonomous agents for Graphical User Interface …
arXiv:2602.13665v1 Announce Type: new Abstract: While agentic AI systems rely on LLMs to translate user intent into structured function calls, this process is fraught with …