Search Results for author:
Found 7 papers, 3 papers with code
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation
Specifically, we introduce FreshQA, a novel dynamic QA benchmark encompassing a diverse range of question and answer types, including questions that require fast-changing world knowledge as well as questions with false premises that need to be debunked.
PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification
Most existing work on adversarial data generation focuses on English.
Multilingual Universal Sentence Encoder for Semantic Retrieval
We introduce two pre-trained retrieval focused multilingual sentence encoding models, respectively based on the Transformer and CNN model architectures.
Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction
Experiments on a complex biomedical information extraction task using expert and lay annotators show that: (i) simply excluding from the training data instances predicted to be difficult yields a small boost in performance; (ii) using difficulty scores to weight instances during training provides further, consistent gains; (iii) assigning instances predicted to be difficult to domain experts is an effective strategy for task routing.
Universal Sentence Encoder for English
We present easy-to-use TensorFlow Hub sentence embedding models having good task transfer performance.
Universal Sentence Encoder
For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance.
Ranked #2 on
Text Classification
on TREC-6
Conversational Response Selection
Semantic Textual Similarity
+7
A Growing Long-term Episodic & Semantic Memory
The long-term memory of most connectionist systems lies entirely in the weights of the system.
