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05/27/2023
Weaker Than You Think: A Critical Look atWeakly Supervised Learning
Weakly supervised learning is a popular approach for training machine le...
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05/26/2023
Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation
Few-shot fine-tuning and in-context learning are two alternative strateg...
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08/04/2022
Fusing Sentence Embeddings Into LSTM-based Autoregressive Language Models
Although masked language models are highly performant and widely adopted...
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07/28/2022
Measuring Causal Effects of Data Statistics on Language Model's `Factual' Predictions
Large amounts of training data are one of the major reasons for the high...
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05/27/2022
StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and Stereotypes
Analyzing ethnic or religious bias is important for improving fairness, ...
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04/22/2022
MCSE: Multimodal Contrastive Learning of Sentence Embeddings
Learning semantically meaningful sentence embeddings is an open problem ...
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04/13/2022
Multilingual Language Model Adaptive Fine-Tuning: A Study on African Languages
Multilingual pre-trained language models (PLMs) have demonstrated impres...
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04/06/2022
Knowledge Base Index Compression via Dimensionality and Precision Reduction
Recently neural network based approaches to knowledge-intensive NLP task...
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01/24/2022
Artefact Retrieval: Overview of NLP Models with Knowledge Base Access
Many NLP models gain performance by having access to a knowledge base. A...
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06/16/2021
Do Acoustic Word Embeddings Capture Phonological Similarity? An Empirical Study
Several variants of deep neural networks have been successfully employed...
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11/02/2020
A Closer Look at Linguistic Knowledge in Masked Language Models: The Case of Relative Clauses in American English
Transformer-based language models achieve high performance on various ta...
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10/28/2020
Fusion Models for Improved Visual Captioning
Visual captioning aims to generate textual descriptions given images. Tr...
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10/06/2020
On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers
Fine-tuning pre-trained contextualized embedding models has become an in...
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07/12/2020
Sparse Graph to Sequence Learning for Vision Conditioned Long Textual Sequence Generation
Generating longer textual sequences when conditioned on the visual infor...
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06/08/2020
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Fine-tuning pre-trained transformer-based language models such as BERT h...
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02/08/2019
Adversarial Initialization -- when your network performs the way I want
The increase in computational power and available data has fueled a wide...
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10/29/2018