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Found 19 papers, 5 papers with code
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity
We introduce Multi-SimLex, a large-scale lexical resource and evaluation benchmark covering data sets for 12 typologically diverse languages, including major languages (e. g., Mandarin Chinese, Spanish, Russian) as well as less-resourced ones (e. g., Welsh, Kiswahili).
Can Rule-Based Insights Enhance LLMs for Radiology Report Classification? Introducing the RadPrompt Methodology
Developing imaging models capable of detecting pathologies from chest X-rays can be cost and time-prohibitive for large datasets as it requires supervision to attain state-of-the-art performance.
Few-Shot Table-to-Text Generation with Prototype Memory
Neural table-to-text generation models have achieved remarkable progress on an array of tasks.
Non-Autoregressive Text Generation with Pre-trained Language Models
In this work, we show that BERT can be employed as the backbone of a NAG model to greatly improve performance.
New dimension bounds for $αβ$ sets
In this paper we obtain new lower bounds for the upper box dimension of $\alpha\beta$ sets.
Dynamical Systems Metric Geometry Number Theory
Dialogue Response Selection with Hierarchical Curriculum Learning
As for IC, it progressively strengthens the model's ability in identifying the mismatching information between the dialogue context and a response candidate.
Ranked #3 on
Conversational Response Selection
on RRS
Stylistic Dialogue Generation via Information-Guided Reinforcement Learning Strategy
To enable better balance between the content quality and the style, we introduce a new training strategy, know as Information-Guided Reinforcement Learning (IG-RL).
Prototype-to-Style: Dialogue Generation with Style-Aware Editing on Retrieval Memory
A stylistic response generator then takes the prototype and the desired language style as model input to obtain a high-quality and stylistic response.
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity
We introduce Multi-SimLex, a large-scale lexical resource and evaluation benchmark covering datasets for 12 typologically diverse languages, including major languages (e. g., Mandarin Chinese, Spanish, Russian) as well as less-resourced ones (e. g., Welsh, Kiswahili).
Equidistribution results for self-similar measures
A well known theorem due to Koksma states that for Lebesgue almost every $x>1$ the sequence $(x^n)_{n=1}^{\infty}$ is uniformly distributed modulo one.
Dynamical Systems Classical Analysis and ODEs Number Theory
Enhancing biomedical word embeddings by retrofitting to verb clusters
Verbs play a fundamental role in many biomed-ical tasks and applications such as relation and event extraction.
Variable Typing: Assigning Meaning to Variables in Mathematical Text
Our results show that the best performing MIR models make use of our typed index, compared to a formula index only containing raw symbols, thereby demonstrating the usefulness of variable typing.
Initializing neural networks for hierarchical multi-label text classification
Many tasks in the biomedical domain require the assignment of one or more predefined labels to input text, where the labels are a part of a hierarchical structure (such as a taxonomy).
Cancer Hallmark Text Classification Using Convolutional Neural Networks
Methods based on deep learning approaches have recently achieved state-of-the-art performance in a range of machine learning tasks and are increasingly applied to natural language processing (NLP).
Robust Text Classification for Sparsely Labelled Data Using Multi-level Embeddings
The conventional solution for handling sparsely labelled data is extensive feature engineering.
Automatic semantic classification of scientific literature according to the hallmarks of cancer
The hallmarks of cancer have become highly influential in cancer research.
A Database and Evaluation Methodology for Optical Flow
The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance.
