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arXiv:2603.10133v1 Announce Type: new Abstract: Data products enable end users to gain greater insights about their data by providing supporting assets, such as example questionSQL pairs which can be answered using the data or views over the database tables.
arXiv:2603.10291v1 Announce Type: new Abstract: The remarkable progress of visionlanguage models VLMs has enabled GUI agents to interact with computers in a humanlike manner.
arXiv:2603.10359v1 Announce Type: new Abstract: Distilling reasoning capabilities from Large Reasoning Models LRMs into smaller models is typically constrained by the limitation of rejection sampling.
arXiv:2603.10384v1 Announce Type: new Abstract: Evaluating LLM reliability via scalar probabilities often fails to capture the structural dynamics of reasoning. We introduce TRACED, a framework that assesses reasoning quality through theoretically grounded geometric kinematics.
arXiv:2603.10396v1 Announce Type: new Abstract: Despite the growing demand for eliciting uncertainty from large language models LLMs, empirical evidence suggests that LLM behavior is not always adequately captured by the elicitation techniques developed under the classical probabilistic...
arXiv:2603.10512v1 Announce Type: new Abstract: Artificial intelligence has advanced significantly through the development of intelligent gameplaying systems, providing rigorous testbeds for decisionmaking, strategic planning, and adaptive learning.
arXiv:2603.10521v1 Announce Type: new Abstract: Instruction hierarchy IH defines how LLMs prioritize system, developer, user, and tool instructions under conflict, providing a concrete, trustordered policy for resolving instruction conflicts.
arXiv:2603.10564v1 Announce Type: new Abstract: The integration of Generative AI models into AInative network systems offers a transformative path toward achieving autonomous and adaptive control.
arXiv:2603.10577v1 Announce Type: new Abstract: ComputerUse Agents CUAs are emerging as a new paradigm in humancomputer interaction, enabling autonomous execution of tasks in desktop environment by perceiving highlevel naturallanguage instructions.
arXiv:2603.10588v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards RLVR has achieved remarkable success in logical reasoning tasks, yet whether large language model LLM alignment requires fundamentally different approaches remains unclear.
How NVIDIA AI-Q Reached \#1 on DeepResearch Bench I and II
Journalist Julia Angwin is one of the writers whose likeness was used in Grammarly’s “expert review” feature. | Photo: Eóin Noonan / Sportsfile via Getty Images For months, Grammarly has been using the identities of real people including us for its "Expert Review" AI suggestions without getting...