Search Results for author:
Found 6 papers, 2 papers with code
ACT2: A multi-disciplinary semi-structured dataset for importance and purpose classification of citations
This modified corpus has annotations for both citation function and importance classes newly enriched with supplementary contextual and non-contextual feature sets the selection of which follows from the lists of features used by the more successful teams in these shared tasks.
Benchmark for Research Theme Classification of Scholarly Documents
We present a new gold-standard dataset and a benchmark for the Research Theme Identification task, a sub-task of the Scholarly Knowledge Graph Generation shared task, at the 3rd Workshop on Scholarly Document Processing.
Benchmarking and Analyzing In-context Learning, Fine-tuning and Supervised Learning for Biomedical Knowledge Curation: a focused study on chemical entities of biological interest
Five setups were designed to assess ML and FT model performance across different data availability scenarios. Datasets for curation tasks included: task 1 (620, 386), task 2 (611, 430), and task 3 (617, 381), maintaining a 50:50 positive versus negative ratio.
Searching for Carriers of the Diffuse Interstellar Bands Across Disciplines, using Natural Language Processing
As a practical example, we have used NLP to conduct an interdisciplinary search for compounds that could be carriers for Diffuse Interstellar Bands (DIBs), a long-standing open question in astrophysics.
Leveraging knowledge graphs to update scientific word embeddings using latent semantic imputation
The most interesting words in scientific texts will often be novel or rare.
Domain-adaptation of spherical embeddings
Two new document classification data-sets are collated from general and chemistry scientific journals to compare the proposed update training strategies with benchmark models.
