3 citations · 6 across the 9 of their papers we have counts for
9 papers
Beyond Hard Samples: Robust and Effective Grammatical Error Correction with Cycle Self-Augmenting
Zecheng Tang, Kaifeng Qi, Juntao Li +1
Recent studies have revealed that grammatical error correction methods in the sequence-to-sequence paradigm are vulnerable to adversarial attack, and simply utilizing adversarial e…
G-SPEED: General SParse Efficient Editing MoDel
Haoke Zhang, Yue Wang, Juntao Li +2
Large Language Models~(LLMs) have demonstrated incredible capabilities in understanding, generating, and manipulating languages. Through human-model interactions, LLMs can automati…
Harnessing the Power of David against Goliath: Exploring Instruction Data Generation without Using Closed-Source Models
Yue Wang, Xinrui Wang, Juntao Li +5
Instruction tuning is instrumental in enabling Large Language Models~(LLMs) to follow user instructions to complete various open-domain tasks. The success of instruction tuning dep…
GameEval: Evaluating LLMs on Conversational Games
Dan Qiao, Chenfei Wu, Yaobo Liang +2
The rapid advancements in large language models (LLMs) have presented challenges in evaluating those models. Existing evaluation methods are either reference-based or preference ba…
Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!
Zecheng Tang, Pinzheng Wang, Keyan Zhou +3
Diffusion models have been successfully adapted to text generation tasks by mapping the discrete text into the continuous space. However, there exist nonnegligible gaps between tra…
Test-Time Adaptation with Perturbation Consistency Learning
Yi Su, Yixin Ji, Juntao Li +2
Currently, pre-trained language models (PLMs) do not cope well with the distribution shift problem, resulting in models trained on the training set failing in real test scenarios.…