23 citations · 41 across the 11 of their papers we have counts for
11 papers
PACT: Preserving Anchored Cores in Task-vectors for Model Merging
Ningyuan Shi, Zhipeng Zhou, Hao Wang +2
Model merging has emerged as a training-free alternative to multi-task learning, aiming to combine multiple task-specific fine-tuned models into a single multi-task model. Most exi…
UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense Disambiguation
Michael Ogezi, Bradley Hauer, Talgat Omarov +2
We describe the systems of the University of Alberta team for the SemEval-2023 Visual Word Sense Disambiguation (V-WSD) Task. We present a novel algorithm that leverages glosses re…
From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework
Yangyi Chen, Hongcheng Gao, Ganqu Cui +10
Textual adversarial attacks can discover models' weaknesses by adding semantic-preserved but misleading perturbations to the inputs. The long-lasting adversarial attack-and-defense…
Interactive Natural Language Processing
Zekun Wang, Ge Zhang, Kexin Yang +19
Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within the field of NLP, aimed at addressing limitations in existing frameworks while aligning with t…
Don't Trust ChatGPT when Your Question is not in English: A Study of Multilingual Abilities and Types of LLMs
Xiang Zhang, Senyu Li, Bradley Hauer +2
Large Language Models (LLMs) have demonstrated exceptional natural language understanding abilities and have excelled in a variety of natural language processing (NLP)tasks in rece…
RoChBert: Towards Robust BERT Fine-tuning for Chinese
Zihan Zhang, Jinfeng Li, Ning Shi +6
Despite of the superb performance on a wide range of tasks, pre-trained language models (e.g., BERT) have been proved vulnerable to adversarial texts. In this paper, we present RoC…
Text Editing as Imitation Game
Ning Shi, Bin Tang, Bo Yuan +4
Text editing, such as grammatical error correction, arises naturally from imperfect textual data. Recent works frame text editing as a multi-round sequence tagging task, where oper…
Counterfactual Adversarial Learning with Representation Interpolation
Wei Wang, Boxin Wang, Ning Shi +4
Deep learning models exhibit a preference for statistical fitting over logical reasoning. Spurious correlations might be memorized when there exists statistical bias in training da…
Incorporating External POS Tagger for Punctuation Restoration
Ning Shi, Wei Wang, Boxin Wang +3
Punctuation restoration is an important post-processing step in automatic speech recognition. Among other kinds of external information, part-of-speech (POS) taggers provide inform…
Recurrent Inference in Text Editing
Ning Shi, Ziheng Zeng, Haotian Zhang +1
In neural text editing, prevalent sequence-to-sequence based approaches directly map the unedited text either to the edited text or the editing operations, in which the performance…
Revisit Systematic Generalization via Meaningful Learning
Ning Shi, Boxin Wang, Wei Wang +2
Humans can systematically generalize to novel compositions of existing concepts. Recent studies argue that neural networks appear inherently ineffective in such cognitive capacity,…