Zobrazeno 1 - 10
of 18 590
pro vyhledávání: '"A. Matthes"'
We study a system of drift-diffusion PDEs for a potentially infinite number of incompressible phases, subject to a joint pointwise volume constraint. Our analysis is based on the interpretation as a collection of coupled Wasserstein gradient flows or
Externí odkaz:
http://arxiv.org/abs/2411.13969
Given the growing trend of many organizations integrating Retrieval Augmented Generation (RAG) into their operations, we assess RAG on domain-specific data and test state-of-the-art models across various optimization techniques. We incorporate four o
Externí odkaz:
http://arxiv.org/abs/2411.08438
The increasing popularity of Large Language Models (LLMs) in recent years has changed the way users interact with and pose questions to AI-based conversational systems. An essential aspect for increasing the trustworthiness of generated LLM answers i
Externí odkaz:
http://arxiv.org/abs/2410.17112
We provide a framework for efficiently estimating impulse response functions with Local Projections (LPs). Our approach offers a Bayesian treatment for LPs with Instrumental Variables, accommodating multiple shocks and instruments per shock, accounts
Externí odkaz:
http://arxiv.org/abs/2410.17105
Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes
Scientific document classification is a critical task and often involves many classes. However, collecting human-labeled data for many classes is expensive and usually leads to label-scarce scenarios. Moreover, recent work has shown that sentence emb
Externí odkaz:
http://arxiv.org/abs/2410.05770
The field of privacy-preserving Natural Language Processing has risen in popularity, particularly at a time when concerns about privacy grow with the proliferation of Large Language Models. One solution consistently appearing in recent literature has
Externí odkaz:
http://arxiv.org/abs/2410.00751
Autor:
Schneider, Phillip, Matthes, Florian
Traditional search methods primarily depend on string matches, while semantic search targets concept-based matches by recognizing underlying intents and contextual meanings of search terms. Semantic search is particularly beneficial for discovering s
Externí odkaz:
http://arxiv.org/abs/2410.00427
Knowledge models are fundamental to dialogue systems for enabling conversational interactions, which require handling domain-specific knowledge. Ensuring effective communication in information-providing conversations entails aligning user understandi
Externí odkaz:
http://arxiv.org/abs/2408.01088
The task of $\textit{keyword extraction}$ is often an important initial step in unsupervised information extraction, forming the basis for tasks such as topic modeling or document classification. While recent methods have proven to be quite effective
Externí odkaz:
http://arxiv.org/abs/2407.14085