arXiv:2607.09502v1 Announce Type: cross Abstract: Explaining machine-learning models is increasingly important for decision-making and consumer trust, yet it is widely…
arXiv:2606.31650v2 Announce Type: replace-cross Abstract: Long-horizon language agents must repeatedly interact with tools, accumulate evidence, and make decisions under bounded…
arXiv:2607.09183v1 Announce Type: cross Abstract: The groundbreaking development of generative artificial intelligence (AI) is rapidly boosting the ability to generate…
arXiv:2607.09566v1 Announce Type: cross Abstract: Decision-making is posing an increasingly formidable challenge to investors because of the growing number of…
arXiv:2607.08773v1 Announce Type: new Abstract: In this work we present a rigorous theoretical framework to a foundational problem of AI…
arXiv:2607.07740v2 Announce Type: replace-cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and…
arXiv:2607.09378v1 Announce Type: cross Abstract: We study an adversarial bandit problem for entanglement-based quantum-network routing over a modest graph corpus.…
arXiv:2607.09366v1 Announce Type: cross Abstract: Program verification is crucial for software correctness, but producing fully verified programs remains difficult in…
arXiv:2607.07047v2 Announce Type: replace-cross Abstract: Understanding the geometric structure of pre-trained language model embeddings matters for interpretability and safety. We…
arXiv:2607.07721v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) and agentic frameworks have advanced enterprise AI considerably, yet agents remain fundamentally…
