Bin Xu
Professor
Works on knowledge engineering with large language models and knowledge graphs, contributes to the GLM model series, and applies large models to education and other industries.
Bin Xu's lab at Tsinghua works on large language models, knowledge, QA & retrieval and graph mining & networks. 28 papers since 2023, 22 at top venues, mostly CIKM and EMNLP. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 79%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 5 papers2026 · T1 4 · collecting
- 12 papers2025 · T1 11
- 7 papers2024 · T1 4
- 4 papers2023 · T1 3
T1 venuesOtherVenues: CIKM, EMNLP, ICLR, ACL, Findings of EMNLP
Research focuspaper titles that use each topic's words
- Large language models15 papers
- Knowledge, QA & retrieval5 papers
- knowledge4 papers
- Graph mining & networks0 papers
- knowledge engineering0 papers
Paper list
From the lab homepage.
20265 papers
- ACL (T1)From Knowing to Teaching: Scaffolding Pedagogical Decisions for LLM Agent
- Journal of Computer Science and Technology, 41(1): 394-414From MOOC to MAIC: Reimagine Online Teaching and Learning Through LLM-Driven Agents
- WWW (T1)Personalized Learning Path Planning through Goal-Driven Learner State Modeling
- ACL (T1)SimPBL: A Multi-Agent Framework for Project-Based Learning
- ICLR (T1)StoryAlign: Evaluating and Training Reward Models for Story Generation
202512 papers
- ACL (T1)Agentic reward modeling: Integrating human preferences with verifiable correctness signals for reliable reward systems
- NeurIPS (T1)AGENTIF: Benchmarking instruction following of large language models in agentic scenarios
- ICLR (T1)Cogcom: A Visual Language Model with Chain-of-Manipulations Reasoning
- ICLR (T1)CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
- CIKM (T1)Constraint back-translation improves complex instruction following of large language models
- CIKM (T1)EduCraft: A System for Generating Pedagogical Lecture Scripts from Long-Context Multimodal Presentations
- CIKM (T1)LLMAEL: Large Language Models are Good Context Augmenters for Entity Linking
- ACM MMLongWriter-V: Enabling Ultra-Long and High-Fidelity Generation in Vision-Language Models
- EMNLP (T1)LoSiA: Efficient High-Rank Fine-Tuning via Subnet Localization and Optimization
- ICCV (T1)Lvbench: An extreme long video understanding benchmark
- CIKM (T1)StoryWriter: A Multi-Agent Framework for Long Story Generation
- EMNLP (T1)VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
20247 papers
- EMNLP (T1)ADELIE: Aligning Large Language Models on Information Extraction
- NeurIPS (T1)CogVLM: Visual expert for pretrained language models
- Findings of EMNLPDocEE-zh: A Fine-grained Benchmark for Chinese Document-level Event Extraction
- TPAMI (T1)Does Negative Sampling Matter? A Review with Insights into its Theory and Applications
- ICLR (T1)KoLA: Carefully Benchmarking World Knowledge of Large Language Models
- EMNLP System DemonstrationsLM-Interview: An Easy-to-use Smart Interviewer System via Knowledge-guided Language Model Exploitation
- Findings of EMNLPMAVEN-FACT: A Large-scale Event Factuality Detection Dataset
20234 papers
- APWeb-WAIMExploring the Effectiveness of Student Behavior in Prerequisite Relation Discovery for Concepts
- CIKM (T1)GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation
- EMNLP (T1)Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction
- ICCV (T1)ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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Data
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- The alumni list could not be found on the lab site.
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- The lab homepage
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