Zobrazeno 1 - 10
of 8 667
pro vyhledávání: '"Ruas A"'
In this work, we describe a prenormal form for the generators of the semigroup of a toric variety $X \subset \mathbb{C}^p$ with isolated singularity at the origin and smooth normalization. A complete description of the semigroup is given when $X$ is
Externí odkaz:
http://arxiv.org/abs/2412.05083
The quality of meeting summaries generated by natural language generation (NLG) systems is hard to measure automatically. Established metrics such as ROUGE and BERTScore have a relatively low correlation with human judgments and fail to capture nuanc
Externí odkaz:
http://arxiv.org/abs/2411.18444
Autor:
Horych, Tomas, Mandl, Christoph, Ruas, Terry, Greiner-Petter, Andre, Gipp, Bela, Aizawa, Akiko, Spinde, Timo
High annotation costs from hiring or crowdsourcing complicate the creation of large, high-quality datasets needed for training reliable text classifiers. Recent research suggests using Large Language Models (LLMs) to automate the annotation process,
Externí odkaz:
http://arxiv.org/abs/2411.11081
Meeting summarization is crucial in digital communication, but existing solutions struggle with salience identification to generate personalized, workable summaries, and context understanding to fully comprehend the meetings' content. Previous attemp
Externí odkaz:
http://arxiv.org/abs/2410.14545
We show that the Nash blowup of 2-generic determinantal varieties over fields of positive characteristic is non-singular. We prove this in two steps. Firstly, we explicitly describe the toric structure of such varieties. Secondly, we show that in thi
Externí odkaz:
http://arxiv.org/abs/2409.04688
Meeting summarization has become a critical task since digital encounters have become a common practice. Large language models (LLMs) show great potential in summarization, offering enhanced coherence and context understanding compared to traditional
Externí odkaz:
http://arxiv.org/abs/2407.11919
State-of-the-art deep learning entity linking methods rely on extensive human-labelled data, which is costly to acquire. Current datasets are limited in size, leading to inadequate coverage of biomedical concepts and diminished performance when appli
Externí odkaz:
http://arxiv.org/abs/2407.06292
We present CiteAssist, a system to automate the generation of BibTeX entries for preprints, streamlining the process of bibliographic annotation. Our system extracts metadata, such as author names, titles, publication dates, and keywords, to create s
Externí odkaz:
http://arxiv.org/abs/2407.03192
We introduce the module of derivations $\Theta_{h,M}$ attached to a given analytic map $h:(\mathbb C^n,0)\to (\mathbb C^p,0)$ and a submodule $M\subseteq \mathcal O_n^p$ and analyse several exact sequences related to $\Theta_{h,M}$. Moreover, we obta
Externí odkaz:
http://arxiv.org/abs/2407.02947
Paraphrases represent a human's intuitive ability to understand expressions presented in various different ways. Current paraphrase evaluations of language models primarily use binary approaches, offering limited interpretability of specific text cha
Externí odkaz:
http://arxiv.org/abs/2407.02302