Search Results for author:
Found 9 papers, 5 papers with code
Structure-Based Drug Design via 3D Molecular Generative Pre-training and Sampling
We develop a novel 3D graph editing model to generate molecules using fragments, and pre-train this model on abundant 3D ligands for learning target-independent properties.
Efficient Monotonic Multihead Attention
We introduce the Efficient Monotonic Multihead Attention (EMMA), a state-of-the-art simultaneous translation model with numerically-stable and unbiased monotonic alignment estimation.
AutoPlan: Automatic Planning of Interactive Decision-Making Tasks With Large Language Models
However, LLMs frequently fail in complex decision-making tasks due to the misalignment between the pre-trained knowledge in LLMs and the actual rules in the environment.
WACO: Word-Aligned Contrastive Learning for Speech Translation
In this paper, we propose Word-Aligned COntrastive learning (WACO), a simple and effective method for extremely low-resource speech-to-text translation.
Pre-trained Language Models Can be Fully Zero-Shot Learners
How can we extend a pre-trained model to many language understanding tasks, without labeled or additional unlabeled data?
Structured Knowledge Grounding for Question Answering
In this paper, we propose to solely leverage the LMs to combine the language and knowledge for knowledge based question-answering with flexibility, breadth of coverage and structured reasoning.
On the Impact of Noises in Crowd-Sourced Data for Speech Translation
Training speech translation (ST) models requires large and high-quality datasets.
Knowledge Guided Geometric Editing for Unsupervised Drug Design
Deep learning models have been widely used in automatic drug design.
KB4Rec: A Dataset for Linking Knowledge Bases with Recommender Systems
Based on our linked dataset, we first preform some interesting qualitative analysis experiments, in which we discuss the effect of two important factors (i. e. popularity and recency) on whether a RS item can be linked to a KB entity.
