research
∙
08/08/2023
Shepherd: A Critic for Language Model Generation
As large language models improve, there is increasing interest in techni...
share
research
∙
06/26/2023
Understanding In-Context Learning via Supportive Pretraining Data
In-context learning (ICL) improves language models' performance on a var...
research
∙
06/20/2023
Open-Domain Text Evaluation via Meta Distribution Modeling
Recent advances in open-domain text generation models powered by large p...
research
∙
05/24/2023
Gender Biases in Automatic Evaluation Metrics: A Case Study on Image Captioning
Pretrained model-based evaluation metrics have demonstrated strong perfo...
research
∙
03/14/2023
Variation of Gender Biases in Visual Recognition Models Before and After Finetuning
We introduce a framework to measure how biases change before and after f...
research
∙
12/22/2022
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization
Recent work has shown that fine-tuning large pre-trained language models...
research
∙
12/16/2022
ALERT: Adapting Language Models to Reasoning Tasks
Current large language models can perform reasonably well on complex tas...
research
∙
10/04/2022
Text Characterization Toolkit
In NLP, models are usually evaluated by reporting single-number performa...
research
∙
05/02/2022
OPT: Open Pre-trained Transformer Language Models
Large language models, which are often trained for hundreds of thousands...
research
∙
12/20/2021
Few-shot Learning with Multilingual Language Models
Large-scale autoregressive language models such as GPT-3 are few-shot le...
research
∙
10/14/2021
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models
Recently, NLP models have achieved remarkable progress across a variety ...
research
∙
08/04/2021
The Impact of Traceability on Software Maintenance and Evolution: A Mapping Study
Software traceability plays a critical role in software maintenance and ...
research
∙
11/27/2020
General Multi-label Image Classification with Transformers
Multi-label image classification is the task of predicting a set of labe...
research
∙
10/08/2020
VisualNews : Benchmark and Challenges in Entity-aware Image Captioning
In this paper we propose VisualNews-Captioner, an entity-aware model for...
research
∙
10/05/2020
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation
NLP models are shown to suffer from robustness issues, i.e., a model's p...
research
∙
05/03/2020
Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation
Word embeddings derived from human-generated corpora inherit strong gend...
research
∙
04/05/2019
Gender Bias in Contextualized Word Embeddings
In this paper, we quantify, analyze and mitigate gender bias exhibited i...
research
∙
11/20/2018
Adversarial Removal of Gender from Deep Image Representations
In this work we analyze visual recognition tasks such as object and acti...
research
∙
04/18/2018
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
We introduce a new benchmark, WinoBias, for coreference resolution focus...
research
∙
10/23/2017
Feedback-prop: Convolutional Neural Network Inference under Partial Evidence
In this paper, we propose an inference procedure for deep convolutional ...
research
∙
07/29/2017
