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08/03/2023
SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning
Textual graphs (TGs) are graphs whose nodes correspond to text (sentence...
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07/25/2023
FacTool: Factuality Detection in Generative AI – A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios
The emergence of generative pre-trained models has facilitated the synth...
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06/26/2023
Composing Parameter-Efficient Modules with Arithmetic Operations
As an efficient alternative to conventional full finetuning, parameter-e...
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06/22/2023
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
The task of empowering large language models (LLMs) to accurately expres...
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06/08/2023
Learning A Foundation Language Model for Geoscience Knowledge Understanding and Utilization
Large language models (LLMs)have achieved great success in general domai...
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05/24/2023
Contrastive Learning of Sentence Embeddings from Scratch
Contrastive learning has been the dominant approach to train state-of-th...
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05/23/2023
Automatic Model Selection with Large Language Models for Reasoning
Chain-of-Thought and Program-Aided Language Models represent two distinc...
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05/23/2023
Evaluating Factual Consistency of Summaries with Large Language Models
Detecting factual errors in summaries has been an important and challeng...
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05/15/2023
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
New NLP benchmarks are urgently needed to align with the rapid developme...
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05/01/2023
Decomposition Enhances Reasoning via Self-Evaluation Guided Decoding
We endow Large Language Models (LLMs) with fine-grained self-evaluation ...
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09/21/2022
Mega: Moving Average Equipped Gated Attention
The design choices in the Transformer attention mechanism, including wea...
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09/13/2022
Non-Parametric Temporal Adaptation for Social Media Topic Classification
User-generated social media data is constantly changing as new trends in...
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04/29/2022
Prompt Consistency for Zero-Shot Task Generalization
One of the most impressive results of recent NLP history is the ability ...
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01/28/2022
Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval
Retrieval-based language models (R-LM) model the probability of natural ...
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10/08/2021
Towards a Unified View of Parameter-Efficient Transfer Learning
Fine-tuning large pre-trained language models on downstream tasks has be...
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10/06/2021
Capturing Structural Locality in Non-parametric Language Models
Structural locality is a ubiquitous feature of real-world datasets, wher...
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09/09/2021
Efficient Nearest Neighbor Language Models
Non-parametric neural language models (NLMs) learn predictive distributi...
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12/08/2020
CTRLsum: Towards Generic Controllable Text Summarization
Current summarization systems yield generic summaries that are disconnec...
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11/02/2020
On the Sentence Embeddings from Pre-trained Language Models
Pre-trained contextual representations like BERT have achieved great suc...
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06/29/2020
Learning Sparse Prototypes for Text Generation
Prototype-driven text generation uses non-parametric models that first c...
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02/10/2020
A Probabilistic Formulation of Unsupervised Text Style Transfer
We present a deep generative model for unsupervised text style transfer ...
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09/30/2019
Revisiting Self-Training for Neural Sequence Generation
Self-training is one of the earliest and simplest semi-supervised method...
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09/28/2019
The Source-Target Domain Mismatch Problem in Machine Translation
While we live in an increasingly interconnected world, different places ...
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09/02/2019
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
When trained effectively, the Variational Autoencoder (VAE) is both a po...
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06/06/2019
Cross-Lingual Syntactic Transfer through Unsupervised Adaptation of Invertible Projections
Cross-lingual transfer is an effective way to build syntactic analysis t...
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05/29/2019
Choosing Transfer Languages for Cross-Lingual Learning
Cross-lingual transfer, where a high-resource transfer language is used ...
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01/16/2019
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
The variational autoencoder (VAE) is a popular combination of deep laten...
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09/04/2018
Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation
We introduce Texar, an open-source toolkit aiming to support the broad s...
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08/28/2018
Unsupervised Learning of Syntactic Structure with Invertible Neural Projections
Unsupervised learning of syntactic structure is typically performed usin...
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06/20/2018
StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing
Semantic parsing is the task of transducing natural language (NL) uttera...
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07/01/2017
Efficient Correlated Topic Modeling with Topic Embedding
Correlated topic modeling has been limited to small model and problem si...
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10/02/2016