130 citations · 744 across the 49 of their papers we have counts for
16 papers · 1 filter
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
Weize Chen, Yusheng Su, Jingwei Zuo +13
Autonomous agents empowered by Large Language Models (LLMs) have undergone significant improvements, enabling them to generalize across a broad spectrum of tasks. However, in real-…
WebCPM: Interactive Web Search for Chinese Long-form Question Answering
Yujia Qin, Zihan Cai, Dian Jin +12
Long-form question answering (LFQA) aims at answering complex, open-ended questions with detailed, paragraph-length responses. The de facto paradigm of LFQA necessitates two proced…
Recyclable Tuning for Continual Pre-training
Yujia Qin, Cheng Qian, Xu Han +6
Continual pre-training is the paradigm where pre-trained language models (PLMs) continually acquire fresh knowledge from growing data and gradually get upgraded. Before an upgraded…
Emergent Modularity in Pre-trained Transformers
Zhengyan Zhang, Zhiyuan Zeng, Yankai Lin +7
This work examines the presence of modularity in pre-trained Transformers, a feature commonly found in human brains and thought to be vital for general intelligence. In analogy to…
Better Pre-Training by Reducing Representation Confusion
Haojie Zhang, Mingfei Liang, Ruobing Xie +3
In this work, we revisit the Transformer-based pre-trained language models and identify two different types of information confusion in position encoding and model representations,…
Prompt Tuning for Discriminative Pre-trained Language Models
Yuan Yao, Bowen Dong, Ao Zhang +6
Recent works have shown promising results of prompt tuning in stimulating pre-trained language models (PLMs) for natural language processing (NLP) tasks. However, to the best of ou…
Denoising Relation Extraction from Document-level Distant Supervision
Chaojun Xiao, Yuan Yao, Ruobing Xie +5
Distant supervision (DS) has been widely used to generate auto-labeled data for sentence-level relation extraction (RE), which improves RE performance. However, the existing succes…
Connecting Embeddings for Knowledge Graph Entity Typing
Yu Zhao, Anxiang Zhang, Ruobing Xie +2
Knowledge graph (KG) entity typing aims at inferring possible missing entity type instances in KG, which is a very significant but still under-explored subtask of knowledge graph c…
FAQ-based Question Answering via Knowledge Anchors
Ruobing Xie, Yanan Lu, Fen Lin +1
Question answering (QA) aims to understand questions and find appropriate answers. In real-world QA systems, Frequently Asked Question (FAQ) based QA is usually a practical and eff…
Neural Snowball for Few-Shot Relation Learning
Tianyu Gao, Xu Han, Ruobing Xie +4
Knowledge graphs typically undergo open-ended growth of new relations. This cannot be well handled by relation extraction that focuses on pre-defined relations with sufficient trai…
Knowledge Representation Learning: A Quantitative Review
Yankai Lin, Xu Han, Ruobing Xie +2
Knowledge representation learning (KRL) aims to represent entities and relations in knowledge graph in low-dimensional semantic space, which have been widely used in massive knowle…
Language Modeling with Sparse Product of Sememe Experts
Yihong Gu, Jun Yan, Hao Zhu +5
Most language modeling methods rely on large-scale data to statistically learn the sequential patterns of words. In this paper, we argue that words are atomic language units but no…
Incorporating Chinese Characters of Words for Lexical Sememe Prediction
Huiming Jin, Hao Zhu, Zhiyuan Liu +4
Sememes are minimum semantic units of concepts in human languages, such that each word sense is composed of one or multiple sememes. Words are usually manually annotated with their…
Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence
Ruobing Xie, Zhiyuan Liu, Fen Lin +1
Knowledge graphs (KGs), which could provide essential relational information between entities, have been widely utilized in various knowledge-driven applications. Since the overall…
Neural Emoji Recommendation in Dialogue Systems
Ruobing Xie, Zhiyuan Liu, Rui Yan +1
Emoji is an essential component in dialogues which has been broadly utilized on almost all social platforms. It could express more delicate feelings beyond plain texts and thus smo…
Knowledge Representation via Joint Learning of Sequential Text and Knowledge Graphs
Jiawei Wu, Ruobing Xie, Zhiyuan Liu +1
Textual information is considered as significant supplement to knowledge representation learning (KRL). There are two main challenges for constructing knowledge representations fro…