Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Buck, Christian"'
Autor:
Bulian, Jannis, Schäfer, Mike S., Amini, Afra, Lam, Heidi, Ciaramita, Massimiliano, Gaiarin, Ben, Hübscher, Michelle Chen, Buck, Christian, Mede, Niels G., Leippold, Markus, Strauß, Nadine
Publikováno v:
Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
As Large Language Models (LLMs) rise in popularity, it is necessary to assess their capability in critically relevant domains. We present a comprehensive evaluation framework, grounded in science communication research, to assess LLM responses to que
Externí odkaz:
http://arxiv.org/abs/2310.02932
Autor:
Adolphs, Leonard, Huebscher, Michelle Chen, Buck, Christian, Girgin, Sertan, Bachem, Olivier, Ciaramita, Massimiliano, Hofmann, Thomas
Neural retrieval models have superseded classic bag-of-words methods such as BM25 as the retrieval framework of choice. However, neural systems lack the interpretability of bag-of-words models; it is not trivial to connect a query change to a change
Externí odkaz:
http://arxiv.org/abs/2210.12084
Learning to search is the task of building artificial agents that learn to autonomously use a search box to find information. So far, it has been shown that current language models can learn symbolic query reformulation policies, in combination with
Externí odkaz:
http://arxiv.org/abs/2209.15469
The predictions of question answering (QA)systems are typically evaluated against manually annotated finite sets of one or more answers. This leads to a coverage limitation that results in underestimating the true performance of systems, and is typic
Externí odkaz:
http://arxiv.org/abs/2202.07654
Autor:
Adolphs, Leonard, Boerschinger, Benjamin, Buck, Christian, Huebscher, Michelle Chen, Ciaramita, Massimiliano, Espeholt, Lasse, Hofmann, Thomas, Kilcher, Yannic, Rothe, Sascha, Sessa, Pier Giuseppe, Saralegui, Lierni Sestorain
This paper presents first successful steps in designing search agents that learn meta-strategies for iterative query refinement in information-seeking tasks. Our approach uses machine reading to guide the selection of refinement terms from aggregated
Externí odkaz:
http://arxiv.org/abs/2109.00527
Autor:
Borschinger, Benjamin, Boyd-Graber, Jordan, Buck, Christian, Bulian, Jannis, Ciaramita, Massimiliano, Huebscher, Michelle Chen, Gajewski, Wojciech, Kilcher, Yannic, Nogueira, Rodrigo, Saralegu, Lierni Sestorain
We investigate a framework for machine reading, inspired by real world information-seeking problems, where a meta question answering system interacts with a black box environment. The environment encapsulates a competitive machine reader based on BER
Externí odkaz:
http://arxiv.org/abs/1911.04156
Publikováno v:
2019_JINST_14_P11007
There is rising interest in organic scintillators with low scattering length for future neutrino detectors. Therefore, a new scintillator system was developed based on admixtures of paraffin wax in linear alkyl benzene. The transparency and viscosity
Externí odkaz:
http://arxiv.org/abs/1908.03334
Autor:
Böser, Sebastian, Buck, Christian, Giunti, Carlo, Lesgourgues, Julien, Ludhova, Livia, Mertens, Susanne, Schukraft, Anne, Wurm, Michael
A number of anomalous results in short-baseline oscillation may hint at the existence of one or more light sterile neutrino states in the eV mass range and have triggered a wave of new experimental efforts to search for a definite signature of oscill
Externí odkaz:
http://arxiv.org/abs/1906.01739
Production and Properties of the Liquid Scintillators used in the Stereo Reactor Neutrino Experiment
Publikováno v:
2019_JINST_14_P01027
The electron antineutrino spectrum in the Stereo reactor experiment (ILL Grenoble) is measured via the inverse beta decay signals in an organic liquid scintillator. The six target cells of the Stereo detector are filled with about 1800 litres of Gd-l
Externí odkaz:
http://arxiv.org/abs/1812.02998