Search Results for author:
Found 11 papers, 4 papers with code
On the Effects of Video Grounding on Language Models
The results show that the smaller model benefits from video grounding in predicting highly imageable words, while the results for the larger model seem harder to interpret. of lack of grounding, e. g., addressing issues like models’ insufficient commonsense knowledge.
How Reliable Are Automatic Evaluation Methods for Instruction-Tuned LLMs?
Work on instruction-tuned Large Language Models (LLMs) has used automatic methods based on text overlap and LLM judgments as cost-effective alternatives to human evaluation.
Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models
Inspired by this, we replace the semantic retrieval in Retro with a surface-level method based on BM25, obtaining a significant reduction in perplexity.
On the Generalization Ability of Retrieval-Enhanced Transformers
Recent work on the Retrieval-Enhanced Transformer (RETRO) model has shown that off-loading memory from trainable weights to a retrieval database can significantly improve language modeling and match the performance of non-retrieval models that are an order of magnitude larger in size.
SINA-BERT: A pre-trained Language Model for Analysis of Medical Texts in Persian
We have released Sina-BERT, a language model pre-trained on BERT (Devlin et al., 2018) to address the lack of a high-quality Persian language model in the medical domain.
Joint Persian Word Segmentation Correction and Zero-Width Non-Joiner Recognition Using BERT
Words are properly segmented in the Persian writing system; in practice, however, these writing rules are often neglected, resulting in single words being written disjointedly and multiple words written without any white spaces between them.
PerKey: A Persian News Corpus for Keyphrase Extraction and Generation
Since previous studies on Persian keyword or keyphrase extraction have not published their data, the field suffers from the lack of a human extracted keyphrase dataset.
Persian Keyphrase Generation Using Sequence-to-Sequence Models
Keyphrases are a very short summary of an input text and provide the main subjects discussed in the text.
Investigating Machine Learning Methods for Language and Dialect Identification of Cuneiform Texts
Identification of the languages written using cuneiform symbols is a difficult task due to the lack of resources and the problem of tokenization.
Ghmerti at SemEval-2019 Task 6: A Deep Word- and Character-based Approach to Offensive Language Identification
This paper presents the models submitted by Ghmerti team for subtasks A and B of the OffensEval shared task at SemEval 2019.
Persian Ezafe Recognition Using Transformers and Its Role in Part-Of-Speech Tagging
Ezafe is a grammatical particle in some Iranian languages that links two words together.
