Learning-based Multi-agent Race Strategies in Formula 1
arXiv:2602.23056v1 Announce Type: new Abstract: In Formula 1, race strategies are adapted according to evolving race conditions and competitors' actions. This paper proposes a reinforcement …
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arXiv:2602.23056v1 Announce Type: new Abstract: In Formula 1, race strategies are adapted according to evolving race conditions and competitors' actions. This paper proposes a reinforcement …
arXiv:2602.23092v1 Announce Type: new Abstract: The Capacitated Vehicle Routing Problem (CVRP), a fundamental combinatorial optimization challenge, focuses on optimizing fleet operations under vehicle capacity constraints. …
arXiv:2602.22351v1 Announce Type: new Abstract: Large language models (LLMs) learn contextual embeddings that capture rich semantic information, yet they often overlook structured lexical knowledge such …
arXiv:2602.22359v1 Announce Type: new Abstract: This paper tests whether large language models (LLMs) can support interpretative citation context analysis (CCA) by scaling in thick, text-grounded …
arXiv:2602.22404v1 Announce Type: new Abstract: Stereotype repositories are critical to assess generative AI model safety, but currently lack adequate global coverage. It is imperative to …
arXiv:2602.22424v1 Announce Type: new Abstract: Do large language models (LLMs) represent concepts abstractly, i.e., independent of input format? We revisit Function Vectors (FVs), compact representations …
arXiv:2602.22449v1 Announce Type: new Abstract: Cyberbullying has become a serious and growing concern in todays virtual world. When left unnoticed, it can have adverse consequences …
arXiv:2602.22453v1 Announce Type: new Abstract: Recent work has identified a subset of attention heads in Transformer as retrieval heads, which are responsible for retrieving information …
arXiv:2602.22475v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in culturally sensitive real-world tasks. However, existing cultural alignment approaches fail to align …
arXiv:2602.22481v1 Announce Type: new Abstract: The way LLM-based entities conceive of the relationship between AI and humans is an important topic for both cultural and …
arXiv:2602.22483v1 Announce Type: new Abstract: Errors in medical text can cause delays or even result in incorrect treatment for patients. Recently, language models have shown …
arXiv:2602.22522v1 Announce Type: new Abstract: Taiwanese Hakka is a low-resource, endangered language that poses significant challenges for automatic speech recognition (ASR), including high dialectal variability …