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Found 18 papers, 8 papers with code
RuCCoN: Clinical Concept Normalization in Russian
We present RuCCoN, a new dataset for clinical concept normalization in Russian manually annotated by medical professionals.
Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking
Medical data annotation requires highly qualified expertise.
Topological Data Analysis for Speech Processing
We apply topological data analysis (TDA) to speech classification problems and to the introspection of a pretrained speech model, HuBERT.
Personality-Driven Social Multimedia Content Recommendation
In order to run organic and paid social media marketing efficiently, it is necessary to understand the audience, tailoring the content to fit their interests and online behaviours, which is impossible to do manually at a large scale.
DetIE: Multilingual Open Information Extraction Inspired by Object Detection
Our model sets the new state of the art performance of 67. 7% F1 on CaRB evaluated as OIE2016 while being 3. 35x faster at inference than previous state of the art.
Ranked #1 on
Open Information Extraction
on LSOIE
Near-Zero-Shot Suggestion Mining with a Little Help from WordNet
In this work, we explore the constructive side of online reviews: advice, tips, requests, and suggestions that users provide about goods, venues, services, and other items of interest.
Ad Lingua: Text Classification Improves Symbolism Prediction in Image Advertisements
Understanding image advertisements is a challenging task, often requiring non-literal interpretation.
Towards General Purpose Geometry-Preserving Single-View Depth Estimation
Our work shows that a model trained on this data along with conventional datasets can gain accuracy while predicting correct scene geometry.
Improving unsupervised neural aspect extraction for online discussions using out-of-domain classification
Deep learning architectures based on self-attention have recently achieved and surpassed state of the art results in the task of unsupervised aspect extraction and topic modeling.
The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews
For the sentence classification task, our model achieves the macro F1 score of 68. 82% gaining 7. 47% over the score of BERT model trained on Russian data.
High-Resolution Daytime Translation Without Domain Labels
We present the high-resolution daytime translation (HiDT) model for this task.
CommentsRadar: Dive into Unique Data on All Comments on the Web
We introduce an entity-centric search engineCommentsRadarthatpairs entity queries with articles and user opinions covering a widerange of topics from top commented sites.
Free-Lunch Saliency via Attention in Atari Agents
We show experimentally that a network with an FLS module exhibits performance similar to the baseline (i. e., it is "free", with no performance cost) and can be used as a drop-in replacement for reinforcement learning agents.
AspeRa: Aspect-Based Rating Prediction Based on User Reviews
We propose a novel Aspect-based Rating Prediction model (AspeRa) that estimates user rating based on review texts for the items.
Large-Scale Transfer Learning for Natural Language Generation
Large-scale pretrained language models define state of the art in natural language processing, achieving outstanding performance on a variety of tasks.
Breast Tumor Cellularity Assessment using Deep Neural Networks
Breast cancer is one of the main causes of death worldwide.
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Generative models are becoming a tool of choice for exploring the molecular space.
Sequence Learning with RNNs for Medical Concept Normalization in User-Generated Texts
In this work, we consider the medical concept normalization problem, i. e., the problem of mapping a disease mention in free-form text to a concept in a controlled vocabulary, usually to the standard thesaurus in the Unified Medical Language System (UMLS).
