research
∙
07/20/2023
Gender-tuning: Empowering Fine-tuning for Debiasing Pre-trained Language Models
Recent studies have revealed that the widely-used Pre-trained Language M...
share
research
∙
07/19/2023
Improving Pre-trained Language Models' Generalization
The reusability of state-of-the-art Pre-trained Language Models (PLMs) i...
research
∙
06/05/2023
Orca: Progressive Learning from Complex Explanation Traces of GPT-4
Recent research has focused on enhancing the capability of smaller model...
research
∙
03/22/2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Artificial intelligence (AI) researchers have been developing and refini...
research
∙
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...
research
∙
11/20/2022
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness
Data-driven predictive solutions predominant in commercial applications ...
research
∙
11/20/2022
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
Large pre-trained models decay over long-term deployment as input distri...
research
∙
08/11/2022
Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages
Machine translation has seen rapid progress with the advent of Transform...
research
∙
07/05/2022
Multi-modal Robustness Analysis Against Language and Visual Perturbations
Joint visual and language modeling on large-scale datasets has recently ...
research
∙
07/04/2022
Large-scale Robustness Analysis of Video Action Recognition Models
We have seen a great progress in video action recognition in recent year...
research
∙
03/17/2022
ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection
Toxic language detection systems often falsely flag text that contains m...
research
∙
06/02/2021
Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization
Abstractive summarization, the task of generating a concise summary of i...
research
∙
05/19/2021
Compositional Processing Emerges in Neural Networks Solving Math Problems
A longstanding question in cognitive science concerns the learning mecha...
research
∙
11/18/2020
Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language
Neuro-symbolic representations have proved effective in learning structu...
research
∙
06/20/2020
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"
Visual reasoning tasks such as visual question answering (VQA) require a...
research
∙
10/25/2019
HUBERT Untangles BERT to Improve Transfer across NLP Tasks
We introduce HUBERT which combines the structured-representational power...
research
∙
10/05/2019
Natural- to formal-language generation using Tensor Product Representations
Generating formal-language represented by relational tuples, such as Lis...
research
∙
09/24/2019
Unified Vision-Language Pre-Training for Image Captioning and VQA
This paper presents a unified Vision-Language Pre-training (VLP) model. ...
research
∙
09/22/2019
Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generators
Grounding language to visual relations is critical to various language-a...
research
∙
05/23/2017
Question-Answering with Grammatically-Interpretable Representations
We introduce an architecture, the Tensor Product Recurrent Network (TPRN...
research
∙
02/24/2015
