95 citations · 172 across the 20 of their papers we have counts for
20 papers
UniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation
Xinyao Liao, Wei Wei, Dangyang Chen +1
Scene Graph Generation(SGG) is a scene understanding task that aims at identifying object entities and reasoning their relationships within a given image. In contrast to prevailing…
Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models
Zhenyi Lu, Jie Tian, Wei Wei +4
Text classification is a crucial task encountered frequently in practical scenarios, yet it is still under-explored in the era of large language models (LLMs). This study shows tha…
Position Debiasing Fine-Tuning for Causal Perception in Long-Term Dialogue
Shixuan Fan, Wei Wei, Wendi Li +3
The core of the dialogue system is to generate relevant, informative, and human-like responses based on extensive dialogue history. Recently, dialogue generation domain has seen ma…
Personalized Topic Selection Model for Topic-Grounded Dialogue
Shixuan Fan, Wei Wei, Xiaofei Wen +3
Recently, the topic-grounded dialogue (TGD) system has become increasingly popular as its powerful capability to actively guide users to accomplish specific tasks through topic-gui…
Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity Recognition
Zhuojun Ding, Wei Wei, Xiaoye Qu +1
Cross-lingual named entity recognition (NER) aims to train an NER model for the target language leveraging only labeled source language data and unlabeled target language data. Pri…
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
Chenghao Fan, Zhenyi Lu, Wei Wei +4
Efficient fine-tuning of large language models for task-specific applications is imperative, yet the vast number of parameters in these models makes their training increasingly cha…
Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging
Zhenyi Lu, Chenghao Fan, Wei Wei +3
In the era of large language models, model merging is a promising way to combine multiple task-specific models into a single multitask model without extra training. However, two ch…
Reinforcement Learning with Token-level Feedback for Controllable Text Generation
Wendi Li, Wei Wei, Kaihe Xu +3
To meet the requirements of real-world applications, it is essential to control generations of large language models (LLMs). Prior research has tried to introduce reinforcement lea…
Joint Multi-Facts Reasoning Network For Complex Temporal Question Answering Over Knowledge Graph
Rikui Huang, Wei Wei, Xiaoye Qu +3
Temporal Knowledge Graph (TKG) is an extension of regular knowledge graph by attaching the time scope. Existing temporal knowledge graph question answering (TKGQA) models solely ap…
Detection-based Intermediate Supervision for Visual Question Answering
Yuhang Liu, Daowan Peng, Wei Wei +3
Recently, neural module networks (NMNs) have yielded ongoing success in answering compositional visual questions, especially those involving multi-hop visual and logical reasoning.…
Enhancing Low-Resource Relation Representations through Multi-View Decoupling
Chenghao Fan, Wei Wei, Xiaoye Qu +4
Recently, prompt-tuning with pre-trained language models (PLMs) has demonstrated the significantly enhancing ability of relation extraction (RE) tasks. However, in low-resource sce…
MIRACLE: Towards Personalized Dialogue Generation with Latent-Space Multiple Personal Attribute Control
Zhenyi Lu, Wei Wei, Xiaoye Qu +3
Personalized dialogue systems aim to endow the chatbot agent with more anthropomorphic traits for human-like interactions. Previous approaches have explored explicitly user profile…
Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation
Sen Zhao, Wei Wei, Xian-Ling Mao +5
Conversational recommendation systems (CRS) aim to interactively acquire user preferences and accordingly recommend items to users. Accurately learning the dynamic user preferences…
TREA: Tree-Structure Reasoning Schema for Conversational Recommendation
Wendi Li, Wei Wei, Xiaoye Qu +4
Conversational recommender systems (CRS) aim to timely trace the dynamic interests of users through dialogues and generate relevant responses for item recommendations. Recently, va…
An Empirical Study on the Language Modal in Visual Question Answering
Daowan Peng, Wei Wei, Xian-Ling Mao +2
Generalization beyond in-domain experience to out-of-distribution data is of paramount significance in the AI domain. Of late, state-of-the-art Visual Question Answering (VQA) mode…
STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction
Shuo Liang, Wei Wei, Xian-Ling Mao +3
Aspect Sentiment Triplet Extraction (ASTE) has become an emerging task in sentiment analysis research, aiming to extract triplets of the aspect term, its corresponding opinion term…
HCL-TAT: A Hybrid Contrastive Learning Method for Few-shot Event Detection with Task-Adaptive Threshold
Ruihan Zhang, Wei Wei, Xian-Ling Mao +2
Conventional event detection models under supervised learning settings suffer from the inability of transfer to newly-emerged event types owing to lack of sufficient annotations. A…
Multi-level Contrastive Learning Framework for Sequential Recommendation
Ziyang Wang, Huoyu Liu, Wei Wei +5
Sequential recommendation (SR) aims to predict the subsequent behaviors of users by understanding their successive historical behaviors. Recently, some methods for SR are devoted t…
Improving Personality Consistency in Conversation by Persona Extending
Yifan Liu, Wei Wei, Jiayi Liu +3
Endowing chatbots with a consistent personality plays a vital role for agents to deliver human-like interactions. However, existing personalized approaches commonly generate respon…
Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning
Ding Zou, Wei Wei, Ziyang Wang +4
Incorporating Knowledge Graphs (KG) into recommeder system has attracted considerable attention. Recently, the technical trend of Knowledge-aware Recommendation (KGR) is to develop…