1 code implementation • IWCS (ACL) 2021 • Zeming Chen, Qiyue Gao
Dependency parsing is a tool widely used in the field of Natural language processing and computational linguistics.
1 code implementation • Joint Conference on Lexical and Computational Semantics 2021 • Zeming Chen, Qiyue Gao, Lawrence S. Moss
Deep learning (DL) based language models achieve high performance on various benchmarks for Natural Language Inference (NLI).
Ranked #1 on Natural Language Inference on MED
1 code implementation • 3 Dec 2021 • Zeming Chen, Qiyue Gao
We propose a methodology for probing linguistic information for logical inference in pre-trained language model representations.
no code implementations • NAACL 2022 • Zeming Chen, Qiyue Gao
In the age of large transformer language models, linguistic evaluation play an important role in diagnosing models' abilities and limitations on natural language understanding.
1 code implementation • 20 Dec 2022 • Zeming Chen, Qiyue Gao, Antoine Bosselut, Ashish Sabharwal, Kyle Richardson
However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale.
no code implementations • 29 Aug 2023 • Valeria de Paiva, Qiyue Gao, Pavel Kovalev, Lawrence S. Moss
Where our study diverges from previous work is in (1) providing a more thorough analysis of what makes mathematical term extraction a difficult problem to begin with; (2) paying close attention to inter-annotator disagreements; (3) providing a set of guidelines which both human and machine annotators could use to standardize the extraction process; (4) introducing a new annotation tool to help humans with ATE, applicable to any mathematical field and even beyond mathematics; (5) using prompts to ChatGPT as part of the extraction process, and proposing best practices for such prompts; and (6) raising the question of whether ChatGPT could be used as an annotator on the same level as human experts.
1 code implementation • 8 Apr 2024 • Shibo Hao, Yi Gu, Haotian Luo, Tianyang Liu, Xiyan Shao, Xinyuan Wang, Shuhua Xie, Haodi Ma, Adithya Samavedhi, Qiyue Gao, Zhen Wang, Zhiting Hu
(2) We develop LLM Reasoners, a library for standardized modular implementation of existing and new reasoning algorithms, under a unified formulation of the search, reward, and world model components.