Zobrazeno 1 - 10
of 1 498
pro vyhledávání: '"Schoenherr, P"'
Autor:
Bothmann, Enrico, Flower, Lois, Gütschow, Christian, Höche, Stefan, Hoppe, Mareen, Isaacson, Joshua, Knobbe, Max, Krauss, Frank, Meinzinger, Peter, Napoletano, Davide, Price, Alan, Reichelt, Daniel, Schönherr, Marek, Schumann, Steffen, Siegert, Frank
Sherpa is a general-purpose Monte Carlo event generator for the simulation of particle collisions in high-energy collider experiments. We summarise new developments, essential features, and ongoing improvements within the Sherpa 3 release series. Phy
Externí odkaz:
http://arxiv.org/abs/2410.22148
While generative AI (GenAI) offers countless possibilities for creative and productive tasks, artificially generated media can be misused for fraud, manipulation, scams, misinformation campaigns, and more. To mitigate the risks associated with malici
Externí odkaz:
http://arxiv.org/abs/2410.01574
Accurate camera calibration is a well-known and widely used task in computer vision that has been researched for decades. However, the standard approach based on checkerboard calibration patterns has some drawbacks that limit its applicability. For e
Externí odkaz:
http://arxiv.org/abs/2409.20127
System prompts that include detailed instructions to describe the task performed by the underlying large language model (LLM) can easily transform foundation models into tools and services with minimal overhead. Because of their crucial impact on the
Externí odkaz:
http://arxiv.org/abs/2409.11026
Large language models (LLMs) have shown great potential for automatic code generation and form the basis for various tools such as GitHub Copilot. However, recent studies highlight that many LLM-generated code contains serious security vulnerabilitie
Externí odkaz:
http://arxiv.org/abs/2409.06446
Retrieval Augmented Generation (RAG) is a technique commonly used to equip models with out of distribution knowledge. This process involves collecting, indexing, retrieving, and providing information to an LLM for generating responses. Despite its gr
Externí odkaz:
http://arxiv.org/abs/2408.05025
Autor:
Ju, Wan-Li, Schoenherr, Marek
In this paper, we calculate the differential transverse momentum and azimuthal decorrelation cross sections, $\mathrm{d}\sigma_{t\bar{t}}/\mathrm{d}q_{\mathrm{T}}$ and $\mathrm{d}\sigma_{t\bar{t}}/\mathrm{d}\Delta\phi_{t\bar{t}}$, in top-antitop pair
Externí odkaz:
http://arxiv.org/abs/2407.03501
In this work, we present the first full NLO predictions for the process $\mathrm{p}\mathrm{p}\to\mu^+\nu_\mu\mathrm{e}^+\nu_\mathrm{e}\mathrm{j}\mathrm{j}$ at the LHC in a typical tri-boson phase space. The NLO corrections reach 50% at the level of t
Externí odkaz:
http://arxiv.org/abs/2406.11516
Autor:
Debenedetti, Edoardo, Rando, Javier, Paleka, Daniel, Florin, Silaghi Fineas, Albastroiu, Dragos, Cohen, Niv, Lemberg, Yuval, Ghosh, Reshmi, Wen, Rui, Salem, Ahmed, Cherubin, Giovanni, Zanella-Beguelin, Santiago, Schmid, Robin, Klemm, Victor, Miki, Takahiro, Li, Chenhao, Kraft, Stefan, Fritz, Mario, Tramèr, Florian, Abdelnabi, Sahar, Schönherr, Lea
Large language model systems face important security risks from maliciously crafted messages that aim to overwrite the system's original instructions or leak private data. To study this problem, we organized a capture-the-flag competition at IEEE SaT
Externí odkaz:
http://arxiv.org/abs/2406.07954
Large Language Models (LLMs) are increasingly augmented with external tools and commercial services into LLM-integrated systems. While these interfaces can significantly enhance the capabilities of the models, they also introduce a new attack surface
Externí odkaz:
http://arxiv.org/abs/2402.06922