Zobrazeno 1 - 10
of 18 614
pro vyhledávání: '"Arno, P."'
Autor:
Simons, Arno
I present Astro-HEP-BERT, a transformer-based language model specifically designed for generating contextualized word embeddings (CWEs) to study the meanings of concepts in astrophysics and high-energy physics. Built on a general pretrained BERT mode
Externí odkaz:
http://arxiv.org/abs/2411.14877
Autor:
Simons, Arno
This paper explores the potential of contextualized word embeddings (CWEs) as a new tool in the history, philosophy, and sociology of science (HPSS) for studying contextual and evolving meanings of scientific concepts. Using the term "Planck" as a te
Externí odkaz:
http://arxiv.org/abs/2411.14073
Autor:
Han, Lankun, Zeng, Zhenyuan, Liu, Bo, Kofu, Maiko, Nakajima, Kenji, Steffens, Paul, Hiess, Arno, Su, Yixi, Li, Shiliang
A Dirac quantum spin liquid hosts Dirac spinons, which are low-energy fractionalized neutral quasiparticles with spin 1/2 that obey the Dirac equation. Recent studies have revealed cone spin continuum in YCu$_3$(OD)$_6$Br$_2$[Br$_{x}$(OD)$_{1-x}$], c
Externí odkaz:
http://arxiv.org/abs/2411.09883
Autor:
Agarwal, Mohit, Sun, Mimi, Kamath, Chaitanya, Muslim, Arbaaz, Sarker, Prithul, Paul, Joydeep, Yee, Hector, Sieniek, Marcin, Jablonski, Kim, Mayer, Yael, Fork, David, de Guia, Sheila, McPike, Jamie, Boulanger, Adam, Shekel, Tomer, Schottlander, David, Xiao, Yao, Manukonda, Manjit Chakravarthy, Liu, Yun, Bulut, Neslihan, Abu-el-haija, Sami, Eigenwillig, Arno, Kothari, Parth, Perozzi, Bryan, Bharel, Monica, Nguyen, Von, Barrington, Luke, Efron, Niv, Matias, Yossi, Corrado, Greg, Eswaran, Krish, Prabhakara, Shruthi, Shetty, Shravya, Prasad, Gautam
Supporting the health and well-being of dynamic populations around the world requires governmental agencies, organizations and researchers to understand and reason over complex relationships between human behavior and local contexts in order to ident
Externí odkaz:
http://arxiv.org/abs/2411.07207
This work explores the intersection of continual learning (CL) and differential privacy (DP). Crucially, continual learning models must retain knowledge across tasks, but this conflicts with the differential privacy requirement of restricting individ
Externí odkaz:
http://arxiv.org/abs/2411.04680
Open-weight large language model (LLM) zoos allow users to quickly integrate state-of-the-art models into systems. Despite increasing availability, selecting the most appropriate model for a given task still largely relies on public benchmark leaderb
Externí odkaz:
http://arxiv.org/abs/2411.00889
Autor:
Rodriguez, Pau, Blaas, Arno, Klein, Michal, Zappella, Luca, Apostoloff, Nicholas, Cuturi, Marco, Suau, Xavier
The increasing capabilities of large generative models and their ever more widespread deployment have raised concerns about their reliability, safety, and potential misuse. To address these issues, recent works have proposed to control model generati
Externí odkaz:
http://arxiv.org/abs/2410.23054
Autor:
Verma, Prakhar, Midigeshi, Sukruta Prakash, Sinha, Gaurav, Solin, Arno, Natarajan, Nagarajan, Sharma, Amit
We introduce Planning-guided Retrieval Augmented Generation (Plan$\times$RAG), a novel framework that augments the \emph{retrieve-then-reason} paradigm of existing RAG frameworks to \emph{plan-then-retrieve}. Plan$\times$RAG formulates a reasoning pl
Externí odkaz:
http://arxiv.org/abs/2410.20753
Autor:
Schemmer, Max, Cordier, Martin, Pache, Lucas, Schneeweiss, Philipp, Volz, Jürgen, Rauschenbeutel, Arno
We model and investigate the collective nonlinear optical response of an ensemble of two-level emitters that are weakly coupled to a single-mode waveguide. Our approach generalizes the insight that photon-photon correlations in the light scattered by
Externí odkaz:
http://arxiv.org/abs/2410.21202
Autor:
Blaas, Arno, Goliński, Adam, Miller, Andrew, Zappella, Luca, Jacobsen, Jörn-Henrik, Heinze-Deml, Christina
We consider robustness to distribution shifts in the context of diagnostic models in healthcare, where the prediction target $Y$, e.g., the presence of a disease, is causally upstream of the observations $X$, e.g., a biomarker. Distribution shifts ma
Externí odkaz:
http://arxiv.org/abs/2410.19575