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06/14/2023
Fed-ZERO: Efficient Zero-shot Personalization with Federated Mixture of Experts
One of the goals in Federated Learning (FL) is to create personalized mo...
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05/24/2023
GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions
Generalization to unseen tasks is an important ability for few-shot lear...
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04/21/2023
Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedback
Many approaches to Natural Language Processing (NLP) tasks often treat t...
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01/22/2023
An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models
Large-scale Pre-Trained Language Models (PTLMs) capture knowledge from m...
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10/31/2022
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning
Standard fine-tuning of large pre-trained language models (PLMs) for dow...
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10/20/2022
Boosting Natural Language Generation from Instructions with Meta-Learning
Recent work has shown that language models (LMs) trained with multi-task...
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10/14/2022
AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers
Neural architecture search (NAS) has demonstrated promising results on i...
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05/24/2022
AdaMix: Mixture-of-Adapter for Parameter-efficient Tuning of Large Language Models
Fine-tuning large-scale pre-trained language models to downstream tasks ...
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04/17/2022
Pathologies of Pre-trained Language Models in Few-shot Fine-tuning
Although adapting pre-trained language models with few examples has show...
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04/06/2022
Knowledge Infused Decoding
Pre-trained language models (LMs) have been shown to memorize a substant...
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01/29/2022
AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models
Knowledge distillation (KD) methods compress large models into smaller s...
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12/09/2021
Compositional Generalization for Natural Language Interfaces to Web APIs
This paper presents Okapi, a new dataset for Natural Language to executa...
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11/04/2021
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
Large-scale pre-trained language models have achieved tremendous success...
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11/04/2021
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding
Most recent progress in natural language understanding (NLU) has been dr...
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10/30/2021
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models
Gigantic pre-trained models have become central to natural language proc...
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10/16/2021
What do Compressed Large Language Models Forget? Robustness Challenges in Model Compression
Recent works have focused on compressing pre-trained language models (PL...
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10/12/2021
LiST: Lite Self-training Makes Efficient Few-shot Learners
We present a new method LiST for efficient fine-tuning of large pre-trai...
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09/15/2021
A Conditional Generative Matching Model for Multi-lingual Reply Suggestion
We study the problem of multilingual automated reply suggestions (RS) mo...
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09/09/2021
MetaXT: Meta Cross-Task Transfer between Disparate Label Spaces
Albeit the universal representational power of pre-trained language mode...
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08/29/2021
SummerTime: Text Summarization Toolkit for Non-experts
Recent advances in summarization provide models that can generate summar...
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08/28/2021
WALNUT: A Benchmark on Weakly Supervised Learning for Natural Language Understanding
Building quality machine learning models for natural language understand...
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06/23/2021
Fairness via Representation Neutralization
Existing bias mitigation methods for DNN models primarily work on learni...
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06/08/2021
XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
While deep and large pre-trained models are the state-of-the-art for var...
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06/03/2021
A Dataset and Baselines for Multilingual Reply Suggestion
Reply suggestion models help users process emails and chats faster. Prev...
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04/16/2021
MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learning
The combination of multilingual pre-trained representations and cross-li...
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04/12/2021
Self-Training with Weak Supervision
State-of-the-art deep neural networks require large-scale labeled traini...
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03/26/2021
NL-EDIT: Correcting semantic parse errors through natural language interaction
We study semantic parsing in an interactive setting in which users corre...
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10/24/2020
Structure-Grounded Pretraining for Text-to-SQL
Learning to capture text-table alignment is essential for table related ...
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10/07/2020
Adaptive Self-training for Few-shot Neural Sequence Labeling
Neural sequence labeling is an important technique employed for many Nat...
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06/27/2020
Uncertainty-aware Self-training for Text Classification with Few Labels
Recent success of large-scale pre-trained language models crucially hing...
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05/30/2020
An Empirical Study of Software Exceptions in the Field using Search Logs
Software engineers spend a substantial amount of time using Web search t...
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05/26/2020
Learning with Weak Supervision for Email Intent Detection
Email remains one of the most frequently used means of online communicat...
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05/05/2020
Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback
We study the task of semantic parse correction with natural language fee...
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05/05/2020
Smart To-Do : Automatic Generation of To-Do Items from Emails
Intelligent features in email service applications aim to increase produ...
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05/02/2020
Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer
Multilingual representations embed words from many languages into a sing...
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12/19/2019
The Usage of Web Search for Software Engineering
Internet plays a key role in accomplishing many tasks. For many such tas...
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11/10/2019
Meta Label Correction for Learning with Weak Supervision
Leveraging weak or noisy supervision for building effective machine lear...
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10/24/2019
Detecting Fake News with Weak Social Supervision
Limited labeled data is becoming the largest bottleneck for supervised l...
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10/04/2019
Distilling Transformers into Simple Neural Networks with Unlabeled Transfer Data
Recent advances in pre-training huge models on large amounts of text thr...
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01/14/2019
Characterizing and Predicting Email Deferral Behavior
Email triage involves going through unhandled emails and deciding what t...
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10/08/2018
Zero-Resource Multilingual Model Transfer: Learning What to Share
Modern natural language processing and understanding applications have e...
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12/26/2017
