Search Results for author:
Found 7 papers, 4 papers with code
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models
The dynamic nature of knowledge in an ever-changing world presents challenges for language models trained on static data; the model in the real world often requires not only acquiring new knowledge but also overwriting outdated information into updated ones.
HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning
With the proliferation of social media, accurate detection of hate speech has become critical to ensure safety online.
Cross-Modal Retrieval Meets Inference:Improving Zero-Shot Classification with Cross-Modal Retrieval
Given a query image, we harness the power of CLIP's cross-modal representations to retrieve relevant textual information from an external image-text pair dataset.
Large Language Models Are Reasoning Teachers
We evaluate our method on a wide range of public models and complex tasks.
Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction
Historically, this challenge has been tackled using numerical weather prediction (NWP) models, grounded on physics-based simulations.
ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning
Cross-domain few-shot learning (CD-FSL), where there are few target samples under extreme differences between source and target domains, has recently attracted huge attention.
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty
This data enables self-supervised pre-training on the target domain, in addition to supervised pre-training on the source domain.
