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20212024
most citedEvaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

59 citations · 88 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.CL2024

Refining Corpora from a Model Calibration Perspective for Chinese Spelling Correction

Dingyao Yu, Yang An, Wei Ye +4

Chinese Spelling Correction (CSC) commonly lacks large-scale high-quality corpora, due to the labor-intensive labeling of spelling errors in real-life human writing or typing scena…

cs.CL2024

FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models

Zhuohao Yu, Chang Gao, Wenjin Yao +6

The rapid development of large language model (LLM) evaluation methodologies and datasets has led to a profound challenge: integrating state-of-the-art evaluation techniques cost-e…

cs.CL202359 cited

Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Bo Li, Gexiang Fang, Yang Yang +4

The capability of Large Language Models (LLMs) like ChatGPT to comprehend user intent and provide reasonable responses has made them extremely popular lately. In this paper, we foc…

cs.CL2023

Dialog-to-Actions: Building Task-Oriented Dialogue System via Action-Level Generation

Yuncheng Hua, Xiangyu Xi, Zheng Jiang +4

End-to-end generation-based approaches have been investigated and applied in task-oriented dialogue systems. However, in industrial scenarios, existing methods face the bottlenecks…

cs.CL20224 cited

Exploiting Hybrid Semantics of Relation Paths for Multi-hop Question Answering Over Knowledge Graphs

Zile Qiao, Wei Ye, Tong Zhang +3

Answering natural language questions on knowledge graphs (KGQA) remains a great challenge in terms of understanding complex questions via multi-hop reasoning. Previous efforts usua…

cs.CL2021

Frequency-Aware Contrastive Learning for Neural Machine Translation

Tong Zhang, Wei Ye, Baosong Yang +7

Low-frequency word prediction remains a challenge in modern neural machine translation (NMT) systems. Recent adaptive training methods promote the output of infrequent words by emp…