292 citations · 610 across the 56 of their papers we have counts for
35 papers · 1 filter
Can Pre-trained Language Models Understand Chinese Humor?
Yuyan Chen, Zhixu Li, Jiaqing Liang +3
Humor understanding is an important and challenging research in natural language processing. As the popularity of pre-trained language models (PLMs), some recent work makes prelimi…
AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities
Jingdan Zhang, Jiaan Wang, Xiaodan Wang +2
Multi-modal knowledge graphs (MMKGs) combine different modal data (e.g., text and image) for a comprehensive understanding of entities. Despite the recent progress of large-scale M…
Can Large Language Models Understand Real-World Complex Instructions?
Qianyu He, Jie Zeng, Wenhao Huang +14
Large language models (LLMs) can understand human instructions, showing their potential for pragmatic applications beyond traditional NLP tasks. However, they still struggle with c…
KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Bases
Xintao Wang, Qianwen Yang, Yongting Qiu +5
Large language models (LLMs) have demonstrated impressive impact in the field of natural language processing, but they still struggle with several issues regarding, such as complet…
Translate Meanings, Not Just Words: IdiomKB's Role in Optimizing Idiomatic Translation with Language Models
Shuang Li, Jiangjie Chen, Siyu Yuan +4
To translate well, machine translation (MT) systems and general-purposed language models (LMs) need a deep understanding of both source and target languages and cultures. Therefore…
Piecing Together Clues: A Benchmark for Evaluating the Detective Skills of Large Language Models
Zhouhong Gu, Lin Zhang, Jiangjie Chen +8
Detectives frequently engage in information detection and reasoning simultaneously when making decisions across various cases, especially when confronted with a vast amount of info…
Adaptive Ordered Information Extraction with Deep Reinforcement Learning
Wenhao Huang, Jiaqing Liang, Zhixu Li +2
Information extraction (IE) has been studied extensively. The existing methods always follow a fixed extraction order for complex IE tasks with multiple elements to be extracted in…
HAUSER: Towards Holistic and Automatic Evaluation of Simile Generation
Qianyu He, Yikai Zhang, Jiaqing Liang +3
Similes play an imperative role in creative writing such as story and dialogue generation. Proper evaluation metrics are like a beacon guiding the research of simile generation (SG…
QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search
Jian Xie, Yidan Liang, Jingping Liu +3
In light of the success of the pre-trained language models (PLMs), continual pre-training of generic PLMs has been the paradigm of domain adaption. In this paper, we propose QUERT,…
Causality-aware Concept Extraction based on Knowledge-guided Prompting
Siyu Yuan, Deqing Yang, Jinxi Liu +4
Concepts benefit natural language understanding but are far from complete in existing knowledge graphs (KGs). Recently, pre-trained language models (PLMs) have been widely used in…
Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation
Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye +16
New Natural Langauge Process~(NLP) benchmarks are urgently needed to align with the rapid development of large language models (LLMs). We present Xiezhi, the most comprehensive eva…
Distilling Script Knowledge from Large Language Models for Constrained Language Planning
Siyu Yuan, Jiangjie Chen, Ziquan Fu +5
In everyday life, humans often plan their actions by following step-by-step instructions in the form of goal-oriented scripts. Previous work has exploited language models (LMs) to…
Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense Knowledge
Jiangjie Chen, Wei Shi, Ziquan Fu +3
Large language models (LLMs) have been widely studied for their ability to store and utilize positive knowledge. However, negative knowledge, such as "lions don't live in the ocean…
Beneath Surface Similarity: Large Language Models Make Reasonable Scientific Analogies after Structure Abduction
Siyu Yuan, Jiangjie Chen, Xuyang Ge +2
The vital role of analogical reasoning in human cognition allows us to grasp novel concepts by linking them with familiar ones through shared relational structures. Despite the att…
ANALOGYKB: Unlocking Analogical Reasoning of Language Models with A Million-scale Knowledge Base
Siyu Yuan, Jiangjie Chen, Changzhi Sun +3
Analogical reasoning is a fundamental cognitive ability of humans. However, current language models (LMs) still struggle to achieve human-like performance in analogical reasoning t…
Domain Mastery Benchmark: An Ever-Updating Benchmark for Evaluating Holistic Domain Knowledge of Large Language Model--A Preliminary Release
Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye +7
Domain knowledge refers to the in-depth understanding, expertise, and familiarity with a specific subject, industry, field, or area of special interest. The existing benchmarks are…
Sem4SAP: Synonymous Expression Mining From Open Knowledge Graph For Language Model Synonym-Aware Pretraining
Zhouhong Gu, Sihang Jiang, Wenhao Huang +3
The model's ability to understand synonymous expression is crucial in many kinds of downstream tasks. It will make the model to better understand the similarity between context, an…
BBT-Fin: Comprehensive Construction of Chinese Financial Domain Pre-trained Language Model, Corpus and Benchmark
Dakuan Lu, Hengkui Wu, Jiaqing Liang +6
To advance Chinese financial natural language processing (NLP), we introduce BBT-FinT5, a new Chinese financial pre-training language model based on the T5 model. To support this e…
MAPS-KB: A Million-scale Probabilistic Simile Knowledge Base
Qianyu He, Xintao Wang, Jiaqing Liang +1
The ability to understand and generate similes is an imperative step to realize human-level AI. However, there is still a considerable gap between machine intelligence and human co…
Harnessing Knowledge and Reasoning for Human-Like Natural Language Generation: A Brief Review
Jiangjie Chen, Yanghua Xiao
The rapid development and application of natural language generation (NLG) techniques has revolutionized the field of automatic text production. However, these techniques are still…
Converge to the Truth: Factual Error Correction via Iterative Constrained Editing
Jiangjie Chen, Rui Xu, Wenxuan Zeng +3
Given a possibly false claim sentence, how can we automatically correct it with minimal editing? Existing methods either require a large number of pairs of false and corrected clai…
Generative Entity Typing with Curriculum Learning
Siyu Yuan, Deqing Yang, Jiaqing Liang +4
Entity typing aims to assign types to the entity mentions in given texts. The traditional classification-based entity typing paradigm has two unignorable drawbacks: 1) it fails to…
Language Models as Knowledge Embeddings
Xintao Wang, Qianyu He, Jiaqing Liang +1
Knowledge embeddings (KE) represent a knowledge graph (KG) by embedding entities and relations into continuous vector spaces. Existing methods are mainly structure-based or descrip…
Tackling Math Word Problems with Fine-to-Coarse Abstracting and Reasoning
Ailisi Li, Xueyao Jiang, Bang Liu +2
Math Word Problems (MWP) is an important task that requires the ability of understanding and reasoning over mathematical text. Existing approaches mostly formalize it as a generati…