Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Nathani, Deepak"'
Language Models (LMs) have shown impressive performance in various natural language tasks. However, when it comes to natural language reasoning, LMs still face challenges such as hallucination, generating incorrect intermediate reasoning steps, and m
Externí odkaz:
http://arxiv.org/abs/2310.12426
Large language models (LLMs) have demonstrated remarkable performance across a wide array of NLP tasks. However, their efficacy is undermined by undesired and inconsistent behaviors, including hallucination, unfaithful reasoning, and toxic content. A
Externí odkaz:
http://arxiv.org/abs/2308.03188
Style transfer is the task of rewriting a sentence into a target style while approximately preserving content. While most prior literature assumes access to a large style-labelled corpus, recent work (Riley et al. 2021) has attempted "few-shot" style
Externí odkaz:
http://arxiv.org/abs/2110.07385
Publikováno v:
ICLR 2020
We propose to study the problem of few shot graph classification in graph neural networks (GNNs) to recognize unseen classes, given limited labeled graph examples. Despite several interesting GNN variants being proposed recently for node and graph cl
Externí odkaz:
http://arxiv.org/abs/2002.12815
We present an alternate formulation of the partial assignment problem as matching random clique complexes, that are higher-order analogues of random graphs, designed to provide a set of invariants that better detect higher-order structure. The propos
Externí odkaz:
http://arxiv.org/abs/1907.01739
The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of research on knowledge base completion (also known as relation prediction
Externí odkaz:
http://arxiv.org/abs/1906.01195
Persistent Homology is a powerful tool in Topological Data Analysis (TDA) to capture topological properties of data succinctly at different spatial resolutions. For graphical data, shape, and structure of the neighborhood of individual data items (no
Externí odkaz:
http://arxiv.org/abs/1811.04049
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Hegde, Narayan, Vardhan, Madhurima, Nathani, Deepak, Rosenzweig, Emily, Speed, Cathy, Karthikesalingam, Alan, Seneviratne, Martin
Publikováno v:
PLoS Digital Health; 4/2/2024, Vol. 3 Issue 4, p1-15, 15p
