Papers with LFG

2 papers
Can Multiple-choice Questions Really Be Useful in Detecting the Abilities of LLMs? (2024.lrec-main)

Copied to clipboard

Challenge: Multiple-choice questions (MCQs) are widely used in the evaluation of large language models (LLMs) however, there are concerns about whether MCQ can truly measure LLM’s capabilities.
Approach: They propose to use multiple choice questions to evaluate large language models (LLMs) to assess their capabilities.
Outcome: The proposed methods show that MCQs are less reliable than LFGQs in terms of expected calibration error.
Implementation and Evaluation of an LFG-based Parser for Wolof (2020.lrec-1)

Copied to clipboard

Challenge: a parsing system for Wolof is developed based on the Lexical Functional Grammar (LFG) system provides detailed syntactic analysis essential for the further development of NLP applications.
Approach: They propose a parsing system for Wolof based on the Lexical Functional Grammar (LFG) system uses finite-state transducers for word tokenization and morphological analysis .
Outcome: The proposed system achieves 67.2% recall, 92.8% precision and an f-score of 77.9%.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations