Zhifang Sui
Professor
Researches natural language processing, text mining and language knowledge engineering.
Zhifang Sui's lab at Peking works on knowledge, QA & retrieval. 47 papers since 2023, 20 at top venues, mostly Findings of EMNLP and Findings of ACL. Applications close .
At a glance
- papers, 2023–2026
- 12/ year
- at T1 venues
- 43%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 9 papers2026 · T1 6 · collecting
- 11 papers2025 · T1 7
- 12 papers2024 · T1 5
- 15 papers2023 · T1 2
T1 venuesOtherVenues: Findings of EMNLP, Findings of ACL, ACL, AAAI, EMNLP
Research focuspaper titles that use each topic's words
- Knowledge, QA & retrieval4 papers
- text1 paper
- knowledge engineering0 papers
- text mining0 papers
- researches natural0 papers
Paper list
From DBLP.
20269 papers
- AAAI (T1)From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling (opens in a new tab)
- CVPR (T1)GroundingME: Exposing the Visual Grounding Gap in MLLMs through Multi-Dimensional Evaluation (opens in a new tab)
- Findings of ACLHAUNTATTACK: When Attack Follows Reasoning as a Shadow (opens in a new tab)
- ACL (T1)HistLens: Mapping Idea Change across Concepts and Corpora (opens in a new tab)
- AAAI (T1)Large Language Models Struggle with Unreasonability in Math Problems (opens in a new tab)
- AAAI (T1)RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection (opens in a new tab)
- Findings of ACLSelfBudgeter: Adaptive Token Allocation for Efficient LLM Reasoning (opens in a new tab)
- Findings of ACLSenseJudge: Human-Centric Preference-Driven Judgment Framework (opens in a new tab)
- ACL (T1)Towards Stable and Effective Reinforcement Learning for Mixture-of-Experts (opens in a new tab)
202511 papers
- EMNLP (T1)A Probabilistic Inference Scaling Theory for LLM Self-Correction (opens in a new tab)
- CVPR (T1)AdaMMS: Model Merging for Heterogeneous Multimodal Large Language Models with Unsupervised Coefficient Optimization (opens in a new tab)
- Findings of EMNLPBeyond Single Frames: Can LMMs Comprehend Implicit Narratives in Comic Strip? (opens in a new tab)
- ACL (T1)Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMs (opens in a new tab)
- AAAI (T1)Exploring Activation Patterns of Parameters in Language Models (opens in a new tab)
- Findings of ACLHow Far are LLMs from Being Our Digital Twins? A Benchmark for Persona-Based Behavior Chain Simulation (opens in a new tab)
- COLING (T1)Language Models Encode the Value of Numbers Linearly (opens in a new tab)
- ICLR (T1)Self-Boosting Large Language Models with Synthetic Preference Data (opens in a new tab)
- Findings of NAACLSG-FSM: A Self-Guiding Zero-Shot Prompting Paradigm for Multi-Hop Question Answering Based on Finite State Machine (opens in a new tab)
- Trans. Mach. Learn. Res.Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models (opens in a new tab)
- ACL (T1)Towards Harmonized Uncertainty Estimation for Large Language Models (opens in a new tab)
202412 papers
- EMNLP (T1)A Survey on In-context Learning (opens in a new tab)
- Findings of ACLAchilles-Bench: A Challenging Benchmark for Low-Resource Evaluation (opens in a new tab)
- Findings of EMNLPBe a Multitude to Itself: A Prompt Evolution Framework for Red Teaming (opens in a new tab)
- EMNLP (T1)Can Large Language Models Always Solve Easy Problems if They Can Solve Harder Ones? (opens in a new tab)
- Findings of ACLCan Large Multimodal Models Uncover Deep Semantics Behind Images? (opens in a new tab)
- ACL (T1)DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models (opens in a new tab)
- LREC/COLINGFaGANet: An Evidence-Based Fact-Checking Model with Integrated Encoder Leveraging Contextual Information (opens in a new tab)
- ACL (T1)Large Language Models are not Fair Evaluators (opens in a new tab)
- ACL (T1)Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations (opens in a new tab)
- Findings of EMNLPShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors (opens in a new tab)
- Findings of EMNLPTaking a Deep Breath: Enhancing Language Modeling of Large Language Models with Sentinel Tokens (opens in a new tab)
- Findings of ACLUnlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding (opens in a new tab)
202315 papers
- Findings of EMNLPBi-Drop: Enhancing Fine-tuning Generalization via Synchronous sub-net Estimation and Optimization (opens in a new tab)
- NLPCCCoarse-to-Fine Entity Representations for Document-Level Relation Extraction (opens in a new tab)
- ACL (T1)Denoising Bottleneck with Mutual Information Maximization for Video Multimodal Fusion (opens in a new tab)
- Findings of EMNLPDialogQAE: N-to-N Question Answer Pair Extraction from Customer Service Chatlog (opens in a new tab)
- Findings of ACLEnhancing Continual Relation Extraction via Classifier Decomposition (opens in a new tab)
- Findings of EMNLPGuiding AMR Parsing with Reverse Graph Linearization (opens in a new tab)
- Findings of EMNLPImageNetVC: Zero- and Few-Shot Visual Commonsense Evaluation on 1000 ImageNet Categories (opens in a new tab)
- Findings of EMNLPInfoCL: Alleviating Catastrophic Forgetting in Continual Text Classification from An Information Theoretic Perspective (opens in a new tab)
- Findings of ACLLearn to Not Link: Exploring NIL Prediction in Entity Linking (opens in a new tab)
- NLPCCMixture-of-Experts for Biomedical Question Answering (opens in a new tab)
- NLPCCNeural Knowledge Bank for Pretrained Transformers (opens in a new tab)
- Findings of EMNLPNot All Demonstration Examples are Equally Beneficial: Reweighting Demonstration Examples for In-Context Learning (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to PekingFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
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- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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