research
∙
08/24/2023
Large Language Model as Autonomous Decision Maker
While large language models (LLMs) exhibit impressive language understan...
share
research
∙
07/31/2023
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Despite the advancements of open-source large language models (LLMs) and...
research
∙
07/29/2023
Towards Codable Text Watermarking for Large Language Models
As large language models (LLMs) generate texts with increasing fluency a...
research
∙
06/04/2023
Arbitrary Few Parameters are Good Enough for Adapting Large-scale Pre-trained Language Models
Parameter-efficient tuning (PET) methods can effectively drive extremely...
research
∙
05/28/2023
Emergent Modularity in Pre-trained Transformers
This work examines the presence of modularity in pre-trained Transformer...
research
∙
05/28/2023
Plug-and-Play Knowledge Injection for Pre-trained Language Models
Injecting external knowledge can improve the performance of pre-trained ...
research
∙
05/28/2023
Stochastic Bridges as Effective Regularizers for Parameter-Efficient Tuning
Parameter-efficient tuning methods (PETs) have achieved promising result...
research
∙
05/28/2023
Plug-and-Play Document Modules for Pre-trained Models
Large-scale pre-trained models (PTMs) have been widely used in document-...
research
∙
05/15/2023
Recyclable Tuning for Continual Pre-training
Continual pre-training is the paradigm where pre-trained language models...
research
∙
05/11/2023
WebCPM: Interactive Web Search for Chinese Long-form Question Answering
Long-form question answering (LFQA) aims at answering complex, open-ende...
research
∙
05/02/2023
UNTER: A Unified Knowledge Interface for Enhancing Pre-trained Language Models
Recent research demonstrates that external knowledge injection can advan...
research
∙
04/17/2023
Tool Learning with Foundation Models
Humans possess an extraordinary ability to create and utilize tools, all...
research
∙
01/25/2023
When to Trust Aggregated Gradients: Addressing Negative Client Sampling in Federated Learning
Federated Learning has become a widely-used framework which allows learn...
research
∙
11/14/2022
MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction
The diverse relationships among real-world events, including coreference...
research
∙
10/25/2022
Exploring Mode Connectivity for Pre-trained Language Models
Recent years have witnessed the prevalent application of pre-trained lan...
research
∙
10/24/2022
Different Tunes Played with Equal Skill: Exploring a Unified Optimization Subspace for Delta Tuning
Delta tuning (DET, also known as parameter-efficient tuning) is deemed a...
research
∙
10/18/2022
ROSE: Robust Selective Fine-tuning for Pre-trained Language Models
Even though the large-scale language models have achieved excellent perf...
research
∙
10/12/2022
Step out of KG: Knowledge Graph Completion via Knowledgeable Retrieval and Reading Comprehension
Knowledge graphs, as the cornerstone of many AI applications, usually fa...
research
∙
10/11/2022
From Mimicking to Integrating: Knowledge Integration for Pre-Trained Language Models
Investigating better ways to reuse the released pre-trained language mod...
research
∙
09/20/2022
Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models
Prompting, which casts downstream applications as language modeling task...
research
∙
08/16/2022
Manual-Guided Dialogue for Flexible Conversational Agents
How to build and use dialogue data efficiently, and how to deploy models...
research
∙
07/18/2022
Towards a General Pre-training Framework for Adaptive Learning in MOOCs
Adaptive learning aims to stimulate and meet the needs of individual lea...
research
∙
04/02/2022
CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation
Existing reference-free metrics have obvious limitations for evaluating ...
research
∙
03/12/2022
ELLE: Efficient Lifelong Pre-training for Emerging Data
Current pre-trained language models (PLM) are typically trained with sta...
research
∙
02/27/2022
A Simple but Effective Pluggable Entity Lookup Table for Pre-trained Language Models
Pre-trained language models (PLMs) cannot well recall rich factual knowl...
research
∙
12/14/2021
Model Uncertainty-Aware Knowledge Amalgamation for Pre-Trained Language Models
As many fine-tuned pre-trained language models (PLMs) with promising per...
research
∙
11/12/2021
On Transferability of Prompt Tuning for Natural Language Understanding
Prompt tuning (PT) is a promising parameter-efficient method to utilize ...
research
∙
10/15/2021
Exploring Low-dimensional Intrinsic Task Subspace via Prompt Tuning
How can pre-trained language models (PLMs) learn universal representatio...
research
∙
10/15/2021
RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models
Backdoor attacks, which maliciously control a well-trained model's outpu...
research
∙
10/08/2021
Topology-Imbalance Learning for Semi-Supervised Node Classification
The class imbalance problem, as an important issue in learning node repr...
research
∙
10/05/2021
MoEfication: Conditional Computation of Transformer Models for Efficient Inference
Transformer-based pre-trained language models can achieve superior perfo...
research
∙
09/23/2021
Dynamic Knowledge Distillation for Pre-trained Language Models
Knowledge distillation (KD) has been proved effective for compressing la...
research
∙
09/13/2021
Pack Together: Entity and Relation Extraction with Levitated Marker
Named Entity Recognition (NER) and Relation Extraction (RE) are the core...
research
∙
05/31/2021
Fully Hyperbolic Neural Networks
Hyperbolic neural networks have shown great potential for modeling compl...
research
∙
05/30/2021
CLEVE: Contrastive Pre-training for Event Extraction
Event extraction (EE) has considerably benefited from pre-trained langua...
research
∙
05/28/2021
Knowledge Inheritance for Pre-trained Language Models
Recent explorations of large-scale pre-trained language models (PLMs) su...
research
∙
05/25/2021
TR-BERT: Dynamic Token Reduction for Accelerating BERT Inference
Existing pre-trained language models (PLMs) are often computationally ex...
research
∙
05/20/2021
Manual Evaluation Matters: Reviewing Test Protocols of Distantly Supervised Relation Extraction
Distantly supervised (DS) relation extraction (RE) has attracted much at...
research
∙
02/07/2021
CSS-LM: A Contrastive Framework for Semi-supervised Fine-tuning of Pre-trained Language Models
Fine-tuning pre-trained language models (PLMs) has demonstrated its effe...
research
∙
02/07/2021
Representation Learning for Natural Language Processing
This book aims to review and present the recent advances of distributed ...
research
∙
12/30/2020
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning
Pre-trained Language Models (PLMs) have shown strong performance in vari...
research
∙
12/29/2020
Accelerating Pre-trained Language Models via Calibrated Cascade
Dynamic early exiting aims to accelerate pre-trained language models' (P...
research
∙
10/28/2020
DisenE: Disentangling Knowledge Graph Embeddings
Knowledge graph embedding (KGE), aiming to embed entities and relations ...
research
∙
10/06/2020
Disentangle-based Continual Graph Representation Learning
Graph embedding (GE) methods embed nodes (and/or edges) in graph into a ...
research
∙
10/05/2020
Learning from Context or Names? An Empirical Study on Neural Relation Extraction
Neural models have achieved remarkable success on relation extraction (R...
research
∙
09/29/2020
Contextual Knowledge Selection and Embedding towards Enhanced Pre-Trained Language Models
Several recent efforts have been devoted to enhancing pre-trained langua...
research
∙
06/09/2020
Learning to Recover from Multi-Modality Errors for Non-Autoregressive Neural Machine Translation
Non-autoregressive neural machine translation (NAT) predicts the entire ...
research
∙
04/28/2020
MAVEN: A Massive General Domain Event Detection Dataset
Event detection (ED), which identifies event trigger words and classifie...
research
∙
04/15/2020
Coreferential Reasoning Learning for Language Representation
Language representation models such as BERT could effectively capture co...
research
∙
04/07/2020
