research
∙
08/09/2023
A General Implicit Framework for Fast NeRF Composition and Rendering
A variety of Neural Radiance Fields (NeRF) methods have recently achieve...
share
research
∙
06/08/2023
Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction
Protein-ligand binding affinity (PLBA) prediction is the fundamental tas...
research
∙
05/23/2023
i-Code Studio: A Configurable and Composable Framework for Integrative AI
Artificial General Intelligence (AGI) requires comprehensive understandi...
research
∙
05/21/2023
i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
The convergence of text, visual, and audio data is a key step towards hu...
research
∙
05/19/2023
Any-to-Any Generation via Composable Diffusion
We present Composable Diffusion (CoDi), a novel generative model capable...
research
∙
12/19/2022
APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning
Logical reasoning of text is an important ability that requires understa...
research
∙
11/15/2022
Empowering Language Models with Knowledge Graph Reasoning for Question Answering
Answering open-domain questions requires world knowledge about in-contex...
research
∙
10/23/2022
Tail Batch Sampling: Approximating Global Contrastive Losses as Optimization over Batch Assignments
Contrastive Learning has recently achieved state-of-the-art performance ...
research
∙
05/22/2022
Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners
The goal of this work is to build flexible video-language models that ca...
research
∙
05/19/2022
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution
Directed evolution is a versatile technique in protein engineering that ...
research
∙
05/18/2022
Automatic Rule Induction for Efficient Semi-Supervised Learning
Semi-supervised learning has shown promise in allowing NLP models to gen...
research
∙
05/03/2022
i-Code: An Integrative and Composable Multimodal Learning Framework
Human intelligence is multimodal; we integrate visual, linguistic, and a...
research
∙
01/20/2022
GASCN: Graph Attention Shape Completion Network
Shape completion, the problem of inferring the complete geometry of an o...
research
∙
10/09/2021
Natural Language for Human-Robot Collaboration: Problems Beyond Language Grounding
To enable robots to instruct humans in collaborations, we identify sever...
research
∙
09/10/2021
A Simple and Effective Method To Eliminate the Self Language Bias in Multilingual Representations
Language agnostic and semantic-language information isolation is an emer...
research
∙
12/28/2020
Universal Sentence Representation Learning with Conditional Masked Language Model
This paper presents a novel training method, Conditional Masked Language...
research
∙
09/02/2020
Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction
Current machine learning has made great progress on computer vision and ...
research
∙
06/05/2020
Anomaly Detection with Domain Adaptation
We study the problem of semi-supervised anomaly detection with domain ad...
research
∙
06/05/2020
Filtered Inner Product Projection for Multilingual Embedding Alignment
Due to widespread interest in machine translation and transfer learning,...
research
∙
02/07/2020
Memory Augmented Generative Adversarial Networks for Anomaly Detection
In this paper, we present a memory-augmented algorithm for anomaly detec...
research
∙
01/18/2020
Regularized Cycle Consistent Generative Adversarial Network for Anomaly Detection
In this paper, we investigate algorithms for anomaly detection. Previous...
research
∙
01/03/2020
TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising
Text summarization aims to extract essential information from a piece of...
research
∙
12/25/2019
Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization
Lead bias is a common phenomenon in news summarization, where early part...
research
∙
06/10/2019
Embedding Imputation with Grounded Language Information
Due to the ubiquitous use of embeddings as input representations for a w...
research
∙
09/30/2018
Zero-training Sentence Embedding via Orthogonal Basis
We propose a simple and robust training-free approach for building sente...
research
∙
02/26/2018
