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Found 41 papers, 17 papers with code
CCTC: A Cross-Sentence Chinese Text Correction Dataset for Native Speakers
The Chinese text correction (CTC) focuses on detecting and correcting Chinese spelling errors and grammatical errors.
ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language Models
To this end, we propose \textbf{\textit{ChemEval}}, which provides a comprehensive assessment of the capabilities of LLMs across a wide range of chemical domain tasks.
SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model
Large language models (LLMs) have shown remarkable achievements across various language tasks. To enhance the performance of LLMs in scientific literature services, we developed the scientific literature LLM (SciLit-LLM) through pre-training and supervised fine-tuning on scientific literature, building upon the iFLYTEK Spark LLM.
JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving
Specially, we construct a Mixture-of-Experts~(MoE) architecture for modeling mathematical text, so as to capture the common mathematical knowledge across tasks.
SHINE: Syntax-augmented Hierarchical Interactive Encoder for Zero-shot Cross-lingual Information Extraction
The proposed encoder is capable of interactively capturing complementary information between features and contextual information, to derive language-agnostic representations for various IE tasks.
GIFT: Graph-Induced Fine-Tuning for Multi-Party Conversation Understanding
Addressing the issues of who saying what to whom in multi-party conversations (MPCs) has recently attracted a lot of research attention.
Multi-Stage Coarse-to-Fine Contrastive Learning for Conversation Intent Induction
The key to automatic intention induction is that, for any given set of new data, the sentence representation obtained by the model can be well distinguished from different labels.
SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary
Sports game summarization aims to generate news articles from live text commentaries.
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
Adversarial training (AT) as a regularization method has proved its effectiveness on various tasks.
Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering
To deal with this challenge, most of the existing works consider paragraphs as nodes in a graph and propose graph-based methods to retrieve them.
Unsupervised Explanation Generation for Machine Reading Comprehension
With the blooming of various Pre-trained Language Models (PLMs), Machine Reading Comprehension (MRC) has embraced significant improvements on various benchmarks and even surpass human performances.
CharBERT: Character-aware Pre-trained Language Model
Most pre-trained language models (PLMs) construct word representations at subword level with Byte-Pair Encoding (BPE) or its variations, by which OOV (out-of-vocab) words are almost avoidable.
Combining ResNet and Transformer for Chinese Grammatical Error Diagnosis
Grammatical error diagnosis is an important task in natural language processing.
Revisiting Pre-Trained Models for Chinese Natural Language Processing
Bidirectional Encoder Representations from Transformers (BERT) has shown marvelous improvements across various NLP tasks, and consecutive variants have been proposed to further improve the performance of the pre-trained language models.
Ranked #13 on
Stock Market Prediction
on Astock
Conversational Word Embedding for Retrieval-Based Dialog System
Human conversations contain many types of information, e. g., knowledge, common sense, and language habits.
Is Graph Structure Necessary for Multi-hop Question Answering?
We construct a strong baseline model to establish that, with the proper use of pre-trained models, graph structure may not be necessary for multi-hop question answering.
A Sentence Cloze Dataset for Chinese Machine Reading Comprehension
To add diversity in this area, in this paper, we propose a new task called Sentence Cloze-style Machine Reading Comprehension (SC-MRC).
TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing
In this paper, we introduce TextBrewer, an open-source knowledge distillation toolkit designed for natural language processing.
Discriminative Sentence Modeling for Story Ending Prediction
Story Ending Prediction is a task that needs to select an appropriate ending for the given story, which requires the machine to understand the story and sometimes needs commonsense knowledge.
Contextual Recurrent Units for Cloze-style Reading Comprehension
Recurrent Neural Networks (RNN) are known as powerful models for handling sequential data, and especially widely utilized in various natural language processing tasks.
Improving Machine Reading Comprehension via Adversarial Training
With virtual adversarial training (VAT), we explore the possibility of improving the RC models with semi-supervised learning and prove that examples from a different task are also beneficial.
IFlyLegal: A Chinese Legal System for Consultation, Law Searching, and Document Analysis
To our knowledge, IFlyLegal is the first Chinese legal system that employs up-to-date NLP techniques and caters for needs of different user groups, such as lawyers, judges, procurators, and clients.
TripleNet: Triple Attention Network for Multi-Turn Response Selection in Retrieval-based Chatbots
The heart of TripleNet is a novel attention mechanism named triple attention to model the relationships within the triple at four levels.
Learning Dynamic Context Augmentation for Global Entity Linking
Despite of the recent success of collective entity linking (EL) methods, these "global" inference methods may yield sub-optimal results when the "all-mention coherence" assumption breaks, and often suffer from high computational cost at the inference stage, due to the complex search space.
Ranked #5 on
Entity Disambiguation
on AIDA-CoNLL
Cross-Lingual Machine Reading Comprehension
In this paper, we propose Cross-Lingual Machine Reading Comprehension (CLMRC) task for the languages other than English.
KCAT: A Knowledge-Constraint Typing Annotation Tool
Fine-grained Entity Typing is a tough task which suffers from noise samples extracted from distant supervision.
EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction
In EERNN, we simply summarize each student's state into an integrated vector and trace it with a recurrent neural network, where we design a bidirectional LSTM to learn the encoding of each exercise's content.
Transcribing Content from Structural Images with Spotlight Mechanism
Then, we decide "what-to-write" by developing a GRU based network with the spotlight areas for transcribing the content accordingly.
Improving Distantly-supervised Entity Typing with Compact Latent Space Clustering
Recently, distant supervision has gained great success on Fine-grained Entity Typing (FET).
Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions
Machine Reading Comprehension (MRC) with multiple-choice questions requires the machine to read given passage and select the correct answer among several candidates.
A Span-Extraction Dataset for Chinese Machine Reading Comprehension
Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention.
Neural Multitask Learning for Simile Recognition
Simile is a special type of metaphor, where comparators such as like and as are used to compare two objects.
Chinese Grammatical Error Diagnosis using Statistical and Prior Knowledge driven Features with Probabilistic Ensemble Enhancement
This paper describes our system at NLPTEA-2018 Task {\#}1: Chinese Grammatical Error Diagnosis.
HFL-RC System at SemEval-2018 Task 11: Hybrid Multi-Aspects Model for Commonsense Reading Comprehension
This paper describes the system which got the state-of-the-art results at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge.
The First Evaluation of Chinese Human-Computer Dialogue Technology
In this paper, we introduce the first evaluation of Chinese human-computer dialogue technology.
Dataset for the First Evaluation on Chinese Machine Reading Comprehension
Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention.
Discourse Mode Identification in Essays
Evaluation results show that discourse modes can be identified automatically with an average F1-score of 0. 7.
Attention-over-Attention Neural Networks for Reading Comprehension
Cloze-style queries are representative problems in reading comprehension.
Ranked #3 on
Question Answering
on Children's Book Test
Consensus Attention-based Neural Networks for Chinese Reading Comprehension
Reading comprehension has embraced a booming in recent NLP research.
Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution
Most existing approaches for zero pronoun resolution are heavily relying on annotated data, which is often released by shared task organizers.
