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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 …
arXiv:2602.13680v1 Announce Type: new Abstract: Large Language Models (LLMs) encounter significant performance bottlenecks in long-sequence tasks due to the computational complexity and memory overhead inherent …
arXiv:2602.13691v1 Announce Type: new Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated strong capabilities in executing complex tasks through tool use. However, …
arXiv:2602.13263v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems often degrade on accented speech because acoustic-phonetic and prosodic shifts induce a mismatch to training …