7 citations · 16 across the 8 of their papers we have counts for
8 papers
Large Language Models Know What Makes Exemplary Contexts
Quanyu Long, Jianda Chen, Wenya Wang +1
In-context learning (ICL) has proven to be a significant capability with the advancement of Large Language models (LLMs). By instructing LLMs using few-shot demonstrative examples,…
Does In-Context Learning Really Learn? Rethinking How Large Language Models Respond and Solve Tasks via In-Context Learning
Quanyu Long, Yin Wu, Wenya Wang +1
In-context Learning (ICL) has emerged as a powerful capability alongside the development of scaled-up large language models (LLMs). By instructing LLMs using few-shot demonstrative…
Backdoor Attacks on Dense Retrieval via Public and Unintentional Triggers
Quanyu Long, Yue Deng, LeiLei Gan +2
Dense retrieval systems have been widely used in various NLP applications. However, their vulnerabilities to potential attacks have been underexplored. This paper investigates a no…
Adapt in Contexts: Retrieval-Augmented Domain Adaptation via In-Context Learning
Quanyu Long, Wenya Wang, Sinno Jialin Pan
Large language models (LLMs) have showcased their capability with few-shot inference known as in-context learning. However, in-domain demonstrations are not always readily availabl…
Interpretable Multimodal Misinformation Detection with Logic Reasoning
Hui Liu, Wenya Wang, Haoliang Li
Multimodal misinformation on online social platforms is becoming a critical concern due to increasing credibility and easier dissemination brought by multimedia content, compared t…
Vera: A General-Purpose Plausibility Estimation Model for Commonsense Statements
Jiacheng Liu, Wenya Wang, Dianzhuo Wang +3
Despite the much discussed capabilities of today's language models, they are still prone to silly and unexpected commonsense failures. We consider a retrospective verification appr…
Weakly-supervised Domain Adaption for Aspect Extraction via Multi-level Interaction Transfer
Tao Liang, Wenya Wang, Fengmao Lv
Fine-grained aspect extraction is an essential sub-task in aspect based opinion analysis. It aims to identify the aspect terms (a.k.a. opinion targets) of a product or service in e…
Integrating Deep Learning with Logic Fusion for Information Extraction
Wenya Wang, Sinno Jialin Pan
Information extraction (IE) aims to produce structured information from an input text, e.g., Named Entity Recognition and Relation Extraction. Various attempts have been proposed f…