292 citations · 610 across the 56 of their papers we have counts for
56 papers
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…
Towards Visual Taxonomy Expansion
Tinghui Zhu, Jingping Liu, Jiaqing Liang +5
Taxonomy expansion task is essential in organizing the ever-increasing volume of new concepts into existing taxonomies. Most existing methods focus exclusively on using textual sem…
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…
M3PT: A Multi-Modal Model for POI Tagging
Jingsong Yang, Guanzhou Han, Deqing Yang +5
POI tagging aims to annotate a point of interest (POI) with some informative tags, which facilitates many services related to POIs, including search, recommendation, and so on. Mos…
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…
A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB Image
Changlong Jiang, Yang Xiao, Cunlin Wu +4
3D interacting hand pose estimation from a single RGB image is a challenging task, due to serious self-occlusion and inter-occlusion towards hands, confusing similar appearance pat…
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…
GANTEE: Generative Adversatial Network for Taxonomy Entering Evaluation
Zhouhong Gu, Sihang Jiang, Jingping Liu +5
Taxonomy is formulated as directed acyclic concepts graphs or trees that support many downstream tasks. Many new coming concepts need to be added to an existing taxonomy. The tradi…
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…