This is a research project in exploring self-supervised learning (SSL) for computer vision. It aims to learn general-purpose image features from raw pixels without relying on manual supervisions, and the learned networks serve as the backbone of various downstream tasks.…
This repository showcases building task-oriented bot at scale with handful examples via fine-tuning a pretrained model using SOLOIST framework, and contains the dataset, source code and pre-trained model for the following paper: SOLOIST: Building Task Bots at Scale with Transfer…
This project provides the source code for the object detection part of vision longformer paper.
This repository implements Ranking-Critical Training (RaCT) for Collaborative Filtering, accepted in International Conference on Learning Representations (ICLR), 2020. By using an actor-critic architecture to fine-tune a differentiable collaborative filtering model, we can improve the performance of a variety of MLE-based…
Gaussian Process for Any Neural Architecture: Reference Implementations This repo is a companion to the paper linked below, which shows that the Gaussian process behavior arises in wide, randomly initialized, neural networks regardless of architecture. Tensor Programs I: Wide Feedforward…
This repo is a companion to the paper “A Fine-Grained Spectral Perspective on Neural Networks”.
We introduce this dataset in order to support the novel task of Visual Question Generation (VQG), where, given an image, the system should ‘ask a natural and engaging question’. This dataset can be used to support research on common sense…
Sent2vec maps a pair of short text strings (e.g., sentences or query-answer pairs) to a pair of feature vectors in a continuous, low-dimensional space where the semantic similarity between the text strings is computed as the cosine similarity between their…
