Lingzhi Wang
20 papers · 2019–2026 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (45) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π€ Dynamic Duo (15)
π§¬
Topic Evolution
π
Keyword Champion
ποΈ
Keyword Collector
(101)
π₯
Unstoppable Β· Bronze
β
The Questioner
β‘
Prolific Year Β· Productive
π
Trend Setter
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(16)
Artificial Intelligence
(14)
Natural Language Processing
(13)
Core AI
(13)
Learning Types Β· Machine Learning
(10)
Generation
(8)
Application Areas
(7)
Applications Β· Natural Language Processing
(5)
Core Methods
(5)
Deep Learning
(4)
Data Science & Analytics
(3)
Applications Β· Data Science & Analytics
(3)
Learning Paradigms
(3)
Learning Types Β· Deep Learning
(3)
Resources & Methods
(2)
Keywords
large language model
(6)
dialogue system
(4)
dialogue generation
(3)
conversational recommender system
(3)
text generation
(3)
response generation
(2)
quotation recommendation
(2)
conversational recommendation
(2)
machine unlearning
(2)
opinion mining
(1)
conversational ai
(1)
social media analysis
(1)
text classification
(1)
representation learning
(1)
attention mechanism
(1)
self-supervised learning
(1)
multi-task learning
(1)
fine-grained classification
(1)
bias detection
(1)
dataset creation
(1)
Papers
Cognitive Policy-Driven LLM for Diagnosis and Intervention of Cognitive Distortions in Emotional Support Conversation
ACL 2026
ToolACE-R: Model-aware Iterative Training and Adaptive Refinement for Tool learning
AAAI 2026
Do Mentioned Items Truly Matter? Enhancing Conversational Recommender Systems with Causal Intervention and Large Language Models
IJCAI 2025
FedCSR: A Federated Framework for Multi-Platform Cross-Domain Sequential Recommendation with Dual Contrastive Learning
COLING 2025
Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception
COLING 2025
Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models
AAAI 2025
DPDLLM: A Black-box Framework for Detecting Pre-training Data from Large Language Models
ACL 2024
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators
EACL 2024
LLMEdgeRefine: Enhancing Text Clustering with LLM-Based Boundary Point Refinement
EMNLP 2024
LLM-REDIAL: A Large-Scale Dataset for Conversational Recommender Systems Created from User Behaviors with LLMs
ACL 2024
PACAR: Automated Fact-Checking with Planning and Customized Action Reasoning Using Large Language Models
COLING 2024
KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment
ACL 2023
Opportunities and Challenges in Neural Dialog Tutoring
EACL 2023
Strategize Before Teaching: A Conversational Tutoring System with Pedagogy Self-Distillation
EACL 2023
Learning When and What to Quote: A Quotation Recommender System with Mutual Promotion of Recommendation and Generation
EMNLP 2022
RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Models
AACL 2022
Quotation Recommendation and Interpretation Based on Transformation from Queries to Quotations
ACL 2021
Re-entry Prediction for Online Conversations via Self-Supervised Learning
EMNLP 2021
Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversations
EMNLP 2020
Coupling Global and Local Context for Unsupervised Aspect Extraction
EMNLP 2019