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pro vyhledávání: '"A. Hardt"'
We experimentally study the breakup of water-glycerol liquid bridges on non-conductive surfaces and find that spontaneous charge deposition at the receding contact line, slide electrification, can have a substantial influence. Electrostatic forces sl
Externí odkaz:
http://arxiv.org/abs/2410.17679
High quality annotations are increasingly a bottleneck in the explosively growing machine learning ecosystem. Scalable evaluation methods that avoid costly annotation have therefore become an important research ambition. Many hope to use strong exist
Externí odkaz:
http://arxiv.org/abs/2410.13341
We simulate the charging of a single electrolyte-filled pore using the modified Poisson-Nernst-Planck and Navier-Stokes equations. We find that electroconvection, previously ignored in this context, can substantially speed up the charging dynamics. W
Externí odkaz:
http://arxiv.org/abs/2410.12653
Drivers on food delivery platforms often run a loss on low-paying orders. In response, workers on DoorDash started a campaign, #DeclineNow, to purposefully decline orders below a certain pay threshold. For each declined order, the platform returns th
Externí odkaz:
http://arxiv.org/abs/2410.12633
We use a double shifted power analog of free fermion fields to introduce current operators, Hamiltonians, and vertex operators which are deformed by two families of parameters and satisfy analogous formulas to the classical case. We show that the def
Externí odkaz:
http://arxiv.org/abs/2410.06582
The breakup dynamics of viscous liquid bridges on solid surfaces is studied experimentally. It is found that the dynamics bears similarities to the breakup of free liquid bridges in the viscous regime. Nevertheless, the dynamics is significantly infl
Externí odkaz:
http://arxiv.org/abs/2408.01790
Autor:
Dominguez-Olmedo, Ricardo, Nanda, Vedant, Abebe, Rediet, Bechtold, Stefan, Engel, Christoph, Frankenreiter, Jens, Gummadi, Krishna, Hardt, Moritz, Livermore, Michael
Annotation and classification of legal text are central components of empirical legal research. Traditionally, these tasks are often delegated to trained research assistants. Motivated by the advances in language modeling, empirical legal scholars ar
Externí odkaz:
http://arxiv.org/abs/2407.16615
Current question-answering benchmarks predominantly focus on accuracy in realizable prediction tasks. Conditioned on a question and answer-key, does the most likely token match the ground truth? Such benchmarks necessarily fail to evaluate LLMs' abil
Externí odkaz:
http://arxiv.org/abs/2407.14614
We study a fundamental problem in the evaluation of large language models that we call training on the test task. Unlike wrongful practices like training on the test data, leakage, or data contamination, training on the test task is not a malpractice
Externí odkaz:
http://arxiv.org/abs/2407.07890
We study the predictability of online speech on social media, and whether predictability improves with information outside a user's own posts. Recent work suggests that the predictive information contained in posts written by a user's peers can surpa
Externí odkaz:
http://arxiv.org/abs/2407.12850