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09/20/2023
DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services
We propose DISC-LawLLM, an intelligent legal system utilizing large lang...
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08/29/2023
SpikeBERT: A Language Spikformer Trained with Two-Stage Knowledge Distillation from BERT
Spiking neural networks (SNNs) offer a promising avenue to implement dee...
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08/28/2023
DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultation
We propose DISC-MedLLM, a comprehensive solution that leverages Large La...
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06/27/2023
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection
Detecting adversarial samples that are carefully crafted to fool the mod...
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06/16/2023
From Hypergraph Energy Functions to Hypergraph Neural Networks
Hypergraphs are a powerful abstraction for representing higher-order int...
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06/08/2023
Open Set Relation Extraction via Unknown-Aware Training
The existing supervised relation extraction methods have achieved impres...
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05/29/2023
Do Large Language Models Know What They Don't Know?
Large language models (LLMs) have a wealth of knowledge that allows them...
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05/26/2023
KNSE: A Knowledge-aware Natural Language Inference Framework for Dialogue Symptom Status Recognition
Symptom diagnosis in medical conversations aims to correctly extract bot...
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05/23/2023
Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement
Prompting methods such as Chain-of-Thought (CoT) have shed new light on ...
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05/21/2023
A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition
Existing models for named entity recognition (NER) are mainly based on l...
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05/20/2023
Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization
Models trained with empirical risk minimization (ERM) are revealed to ea...
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05/11/2023
Enhancing Contrastive Learning with Noise-Guided Attack: Towards Continual Relation Extraction in the Wild
The principle of continual relation extraction (CRE) involves adapting t...
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05/04/2023
CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing
Dataset bias, i.e., the over-reliance on dataset-specific literal heuris...
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03/18/2023
A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models
GPT series models, such as GPT-3, CodeX, InstructGPT, ChatGPT, and so on...
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03/01/2023
How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks
The GPT-3.5 models have demonstrated impressive performance in various N...
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12/21/2022
Cross-Linguistic Syntactic Difference in Multilingual BERT: How Good is It and How Does It Affect Transfer?
Multilingual BERT (mBERT) has demonstrated considerable cross-lingual sy...
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12/19/2022
Rethinking Label Smoothing on Multi-hop Question Answering
Label smoothing is a regularization technique widely used in supervised ...
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11/14/2022
Efficient Adversarial Training with Robust Early-Bird Tickets
Adversarial training is one of the most powerful methods to improve the ...
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11/06/2022
Robust Lottery Tickets for Pre-trained Language Models
Recent works on Lottery Ticket Hypothesis have shown that pre-trained la...
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10/14/2022
Kernel-Whitening: Overcome Dataset Bias with Isotropic Sentence Embedding
Dataset bias has attracted increasing attention recently for its detrime...
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10/10/2022
Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER
As the categories of named entities rapidly increase in real-world appli...
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09/29/2022
COLO: A Contrastive Learning based Re-ranking Framework for One-Stage Summarization
Traditional training paradigms for extractive and abstractive summarizat...
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08/27/2022
A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck
Event argument extraction (EAE) aims to extract arguments with given rol...
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08/22/2022
Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering
Multi-hop reasoning requires aggregating multiple documents to answer a ...
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08/19/2022
Causal Intervention Improves Implicit Sentiment Analysis
Despite having achieved great success for sentiment analysis, existing n...
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06/11/2022
A Unified Continuous Learning Framework for Multi-modal Knowledge Discovery and Pre-training
Multi-modal pre-training and knowledge discovery are two important resea...
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05/29/2022
CoNT: Contrastive Neural Text Generation
Recently, contrastive learning attracts increasing interests in neural t...
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05/27/2022
What Dense Graph Do You Need for Self-Attention?
Transformers have made progress in miscellaneous tasks, but suffer from ...
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04/19/2022
A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasets
In recent years, interest has arisen in using machine learning to improv...
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04/09/2022
MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspective
NER model has achieved promising performance on standard NER benchmarks....
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02/16/2022
Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective
Natural language understanding (NLU) models tend to rely on spurious cor...
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01/29/2022
MVPTR: Multi-Stage Vision-Language Pre-Training via Multi-Level Semantic Alignment
In this paper, we propose a Multi-stage Vision-language Pre-TRaining (MV...
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10/14/2021
Plug-Tagger: A Pluggable Sequence Labeling Framework Using Language Models
Plug-and-play functionality allows deep learning models to adapt well to...
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10/13/2021
Towards Efficient NLP: A Standard Evaluation and A Strong Baseline
Supersized pre-trained language models have pushed the accuracy of vario...
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10/06/2021
KNN-BERT: Fine-Tuning Pre-Trained Models with KNN Classifier
Pre-trained models are widely used in fine-tuning downstream tasks with ...
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09/28/2021
Template-free Prompt Tuning for Few-shot NER
Prompt-based methods have been successfully applied in sentence-level fe...
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09/26/2021
Paradigm Shift in Natural Language Processing
In the era of deep learning, modeling for most NLP tasks has converged t...
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09/12/2021
Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval
Existing research for image text retrieval mainly relies on sentence-lev...
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09/10/2021
Learning to Teach with Student Feedback
Knowledge distillation (KD) has gained much attention due to its effecti...
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08/19/2021
Fine-Grained Element Identification in Complaint Text of Internet Fraud
Existing system dealing with online complaint provides a final decision ...
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06/22/2021
SENT: Sentence-level Distant Relation Extraction via Negative Training
Distant supervision for relation extraction provides uniform bag labels ...
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06/21/2021
TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning
Existing research for image captioning usually represents an image using...
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06/01/2021
SpanNER: Named Entity Re-/Recognition as Span Prediction
Recent years have seen the paradigm shift of Named Entity Recognition (N...
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05/31/2021
Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models
A sequence-to-sequence learning with neural networks has empirically pro...
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05/28/2021
Accelerating BERT Inference for Sequence Labeling via Early-Exit
Both performance and efficiency are crucial factors for sequence labelin...
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05/28/2021
Early Exiting with Ensemble Internal Classifiers
As a simple technique to accelerate inference of large-scale pre-trained...
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05/08/2021
Certified Robustness to Text Adversarial Attacks by Randomized [MASK]
Recently, few certified defense methods have been developed to provably ...
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04/17/2021
Who Responded to Whom: The Joint Effects of Latent Topics and Discourse in Conversation Structure
Numerous online conversations are produced on a daily basis, resulting i...
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04/09/2021
Larger-Context Tagging: When and Why Does It Work?
The development of neural networks and pretraining techniques has spawne...
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04/07/2021
