All Articles
arXiv:2602.16958v1 Announce Type: new Abstract: Agent hijacking, highlighted by OWASP as a critical threat to the Large Language Model (LLM) ecosystem, enables adversaries to manipulate …
arXiv:2602.16976v1 Announce Type: new Abstract: Here's the corrected paragraph with all punctuation and formatting issues fixed: Financial risk systems usually follow a two-step routine: a …
arXiv:2602.16984v1 Announce Type: new Abstract: Black-box safety evaluation of AI systems assumes model behavior on test distributions reliably predicts deployment performance. We formalize and challenge …
arXiv:2602.16990v1 Announce Type: new Abstract: Most recommendation benchmarks evaluate how well a model imitates user behavior. In financial advisory, however, observed actions can be noisy …
arXiv:2602.17001v1 Announce Type: new Abstract: Natural Language Querying for Time Series Databases (NLQ4TSDB) aims to assist non-expert users retrieve meaningful events, intervals, and summaries from …
arXiv:2602.17015v1 Announce Type: new Abstract: A fair and fast matchmaking system is an important component of modern multiplayer online games, directly impacting player retention and …
arXiv:2602.17016v1 Announce Type: new Abstract: Automated formalization of mathematics enables mechanical verification but remains limited to isolated theorems and short snippets. Scaling to textbooks and …
arXiv:2602.17017v1 Announce Type: new Abstract: Enterprises increasingly need AI systems that can answer sales-leader questions over live, customized CRM data, but most available models do …
arXiv:2602.17046v1 Announce Type: new Abstract: Large Language Model (LLM) agents often run for many steps while re-ingesting long system instructions and large tool catalogs each …
arXiv:2602.17049v1 Announce Type: new Abstract: Computer-use agents operate over long horizons under noisy perception, multi-window contexts, evolving environment states. Existing approaches, from RL-based planners to …
arXiv:2602.17053v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) exhibit strong performance, yet often produce rationales that sound plausible but fail to reflect their true …
arXiv:2602.17062v1 Announce Type: new Abstract: Value decomposition is a core approach for cooperative multi-agent reinforcement learning (MARL). However, existing methods still rely on a single …
