Search Results for author:
Found 8 papers, 4 papers with code
Multilingual Aliasing for Auto-Generating Proposition Banks
To address these issues, we propose to manually alias TL verbs to existing English frames.
Machine Learning for Exam Triage
In this project, we extend the state-of-the-art CheXNet (Rajpurkar et al. [2017]) by making use of the additional non-image features in the dataset.
Attentive Aspect Modeling for Review-aware Recommendation
The common aspects mentioned in a user's reviews and a product's reviews indicate indirect connections between the user and product.
Jennifer for COVID-19: An NLP-Powered Chatbot Built for the People and by the People to Combat Misinformation
Just as SARS-CoV-2, a new form of coronavirus continues to infect a growing number of people around the world, harmful misinformation about the outbreak also continues to spread.
TDGIA:Effective Injection Attacks on Graph Neural Networks
In the GIA scenario, the adversary is not able to modify the existing link structure and node attributes of the input graph, instead the attack is performed by injecting adversarial nodes into it.
Polycentric Clustering and Structural Regularization for Source-free Unsupervised Domain Adaptation
In this paper, a novel framework named PCSR is proposed to tackle SFDA via a novel intra-class Polycentric Clustering and Structural Regularization strategy.
GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation
Despite the recent emergence of video captioning models, how to generate vivid, fine-grained video descriptions based on the background knowledge (i. e., long and informative commentary about the domain-specific scenes with appropriate reasoning) is still far from being solved, which however has great applications such as automatic sports narrative.
OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining
We envisage that OAG-Bench can serve as a common ground for the community to evaluate and compare algorithms in academic graph mining, thereby accelerating algorithm development and advancement in this field.
