research
∙
09/14/2023
MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning
Starting from the resurgence of deep learning, vision-language models (V...
share
research
∙
07/03/2023
Mining Clues from Incomplete Utterance: A Query-enhanced Network for Incomplete Utterance Rewriting
Incomplete utterance rewriting has recently raised wide attention. Howev...
research
∙
06/10/2023
Human-in-the-Loop through Chain-of-Thought
While the emergence of powerful language models along with Chain-of-thou...
research
∙
05/24/2023
DialogVCS: Robust Natural Language Understanding in Dialogue System Upgrade
In the constant updates of the product dialogue systems, we need to retr...
research
∙
05/22/2023
Can We Edit Factual Knowledge by In-Context Learning?
Previous studies have shown that large language models (LLMs) like GPTs ...
research
∙
05/20/2023
DiffCap: Exploring Continuous Diffusion on Image Captioning
Current image captioning works usually focus on generating descriptions ...
research
∙
05/18/2023
On the Off-Target Problem of Zero-Shot Multilingual Neural Machine Translation
While multilingual neural machine translation has achieved great success...
research
∙
05/06/2023
SANTA: Separate Strategies for Inaccurate and Incomplete Annotation Noise in Distantly-Supervised Named Entity Recognition
Distantly-Supervised Named Entity Recognition effectively alleviates the...
research
∙
04/06/2023
On the Pareto Front of Multilingual Neural Machine Translation
In this work, we study how the generalization performance of a given dir...
research
∙
12/31/2022
A Survey for In-context Learning
With the increasing ability of large language models (LLMs), in-context ...
research
∙
09/29/2022
A Two-Stage Method for Chinese AMR Parsing
In this paper, we provide a detailed description of our system at CAMRP-...
research
∙
09/04/2022
SCL-RAI: Span-based Contrastive Learning with Retrieval Augmented Inference for Unlabeled Entity Problem in NER
Named Entity Recognition is the task to locate and classify the entities...
research
∙
06/18/2022
A Double-Graph Based Framework for Frame Semantic Parsing
Frame semantic parsing is a fundamental NLP task, which consists of thre...
research
∙
05/02/2022
Robust Fine-tuning via Perturbation and Interpolation from In-batch Instances
Fine-tuning pretrained language models (PLMs) on downstream tasks has be...
research
∙
04/30/2022
A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction
Most previous studies aim at extracting events from a single sentence, w...
research
∙
04/19/2022
ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
As Abstract Meaning Representation (AMR) implicitly involves compound se...
research
∙
04/18/2022
StableMoE: Stable Routing Strategy for Mixture of Experts
The Mixture-of-Experts (MoE) technique can scale up the model size of Tr...
research
∙
04/15/2022
Mixture of Experts for Biomedical Question Answering
Biomedical Question Answering (BQA) has attracted increasing attention i...
research
∙
04/10/2022
DISK: Domain-constrained Instance Sketch for Math Word Problem Generation
A math word problem (MWP) is a coherent narrative which reflects the und...
research
∙
03/06/2022
Focus on the Target's Vocabulary: Masked Label Smoothing for Machine Translation
Label smoothing and vocabulary sharing are two widely used techniques in...
research
∙
12/14/2021
From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression
Pre-trained Language Models (PLMs) have achieved great success in variou...
research
∙
10/15/2021
Hierarchical Curriculum Learning for AMR Parsing
Abstract Meaning Representation (AMR) parsing translates sentences to th...
research
∙
09/27/2021
An Enhanced Span-based Decomposition Method for Few-Shot Sequence Labeling
Few-Shot Sequence Labeling (FSSL) is a canonical solution for the taggin...
research
∙
09/13/2021
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
Recent pretrained language models extend from millions to billions of pa...
research
∙
08/29/2021
Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot Event Classification
Few-Shot Event Classification (FSEC) aims at developing a model for even...
research
∙
06/21/2021
Explicit Interaction Network for Aspect Sentiment Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) aims to recognize targets, th...
research
∙
06/15/2021
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Artificial Intelligence (AI), along with the recent progress in biomedic...
research
∙
06/03/2021
SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction
Document-level relation extraction has attracted much attention in recen...
research
∙
05/31/2021
Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker
Document-level event extraction aims to recognize event information from...
research
∙
04/20/2021
Problems and Countermeasures in Natural Language Processing Evaluation
Evaluation in natural language processing guides and promotes research o...
research
∙
03/26/2021
Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehension
Conventional Machine Reading Comprehension (MRC) has been well-addressed...
research
∙
02/17/2021
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View
In open domain table-to-text generation, we notice that the unfaithful g...
research
∙
12/14/2020
Generating Math Word Problems from Equations with Topic Controlling and Commonsense Enforcement
Recent years have seen significant advancement in text generation tasks ...
research
∙
12/04/2020
Coarse-to-Fine Entity Representations for Document-level Relation Extraction
Document-level Relation Extraction (RE) requires extracting relations ex...
research
∙
10/08/2020
An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference
The prior work on natural language inference (NLI) debiasing mainly targ...
research
∙
10/08/2020
Discriminatively-Tuned Generative Classifiers for Robust Natural Language Inference
While discriminative neural network classifiers are generally preferred,...
research
∙
09/29/2020
Double Graph Based Reasoning for Document-level Relation Extraction
Document-level relation extraction aims to extract relations among entit...
research
∙
09/27/2020
Inductively Representing Out-of-Knowledge-Graph Entities by Optimal Estimation Under Translational Assumptions
Conventional Knowledge Graph Completion (KGC) assumes that all test enti...
research
∙
03/05/2020
HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference
Many recent studies have shown that for models trained on datasets for n...
research
∙
10/24/2019
Pun-GAN: Generative Adversarial Network for Pun Generation
In this paper, we focus on the task of generating a pun sentence given a...
research
∙
05/24/2019
A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer
Unsupervised text style transfer aims to transfer the underlying style o...
research
∙
05/21/2018
Incorporating Glosses into Neural Word Sense Disambiguation
Word Sense Disambiguation (WSD) aims to identify the correct meaning of ...
research
∙
11/27/2017
Table-to-text Generation by Structure-aware Seq2seq Learning
Table-to-text generation aims to generate a description for a factual ta...
research
∙
09/01/2017
Order-Planning Neural Text Generation From Structured Data
Generating texts from structured data (e.g., a table) is important for v...
research
∙
04/03/2017
Syntax Aware LSTM Model for Chinese Semantic Role Labeling
As for semantic role labeling (SRL) task, when it comes to utilizing par...
research
∙
02/22/2017
Improving Chinese SRL with Heterogeneous Annotations
Previous studies on Chinese semantic role labeling (SRL) have concentrat...
research
∙
06/15/2016
Learning Word Sense Embeddings from Word Sense Definitions
Word embeddings play a significant role in many modern NLP systems. Sinc...
research
∙
03/04/2016