Heng Ji
Professor
Studies natural language processing, including information extraction, knowledge-enhanced language models and multimedia multilingual understanding.
Heng Ji's lab at UIUC works on knowledge, QA & retrieval, large language models and data management & big data. 258 papers since 2023, 114 at top venues, mostly ACL and EMNLP. 17 PhD students. 135 alumni, most often to Meta and Amazon. Applications close .
At a glance
- papers, 2023–2026
- 67/ year
- at T1 venues
- 44%
- PhD students
- 17
- MS students
- 0
- alumni listed
- 135
Papers by yearfrom the lab homepage, 2023–2026
- 76 papers2026 · T1 34 · collecting
- 61 papers2025 · T1 35
- 59 papers2024 · T1 22
- 62 papers2023 · T1 23
T1 venuesOtherVenues: ACL, EMNLP, ICLR, TMLR, ICML
Research focuspaper titles that use each topic's words
- Large language models118 papers
- Knowledge, QA & retrieval30 papers
- Data management & big data12 papers
- information extraction3 papers
- knowledge-enhanced1 paper
Paper list
From the lab homepage.
202676 papers
- COLM2026A Rubric-Supervised Critic from Sparse Real-World Outcomes (opens in a new tab)
- Proc. COLM2026 Workshop on Agent BehaviorACCORD: Action-Conditioned Contextual Grounding for Language Agents (opens in a new tab)
- COLM2026AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints (opens in a new tab)
- NeurIPS (T1)Advancing Creative Physical Intelligence in Large Multimodal Models (opens in a new tab)
- Proc. ICML2026 Workshop on Failure Modes of Agentic AIAgentDebug: Where LLM Agents Fail and How They can Learn From Failures (opens in a new tab)
- Proc. The Conference on Empirical Methods in Natural Language Processing (EMNLP2026) Demo TrackAgentDebugX: An Open-Source Toolkit for Failure Observability, Attribution, and Recovery in LLM Agents (opens in a new tab)
- TMLR (T1)Agentic Reasoning for Large Language Models: A Survey (opens in a new tab)
- ACL (T1)Analyzing and Internalizing Complex Policy Documents for LLM Agents (opens in a new tab)
- Proc. ICML2026 Workshop on Human-AI Co-CreativityAssessing the Creativity of Large Language Models: Testing, Limits, and New Frontiers (opens in a new tab)
- Proc. Forty-Third International Conference on Machine Learning (ICML2026) SpotlightBeyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum (opens in a new tab)
- EMNLP (T1)Beyond Perfect APIs: A Comprehensive Evaluation of LLM Agents Under Real-World API Complexity (opens in a new tab)
- EACLBeyond Sample-Level Feedback: Using Reference-Level Feedback to Guide Data Synthesis (opens in a new tab)
202561 papers
- SIGIR (T1)A Large-Scale Study of Reranker Relevance Feedback at Inference (opens in a new tab)
- Proc. IEEE Conference on Artificial Intelligence Workshop on on Human Alignment in AI Decision-Making SystemsA Roadmap for Alignable Algorithmic Decision-Makers in the Medical Triage Domain (opens in a new tab)
- TMLR (T1)A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve (opens in a new tab)
- COLING (T1)Aligning LLMs with Individual Preferences via Interaction (opens in a new tab)
- Foundations and Trends in Machine LearningArtificial Intelligence Research for Accelerating Discoveries in Quantum, Atomistic, and Continuum Systems (opens in a new tab)
- IJCAI (T1)Automating Knowledge Discovery from Scientific Literature via LLMs: A Dual-Agent Approach with Progressive Ontology Prompting (opens in a new tab)
- Proc. The Annual Meeting of the Association for Computational Linguistics (ACL2025) FindingsBeyond Reactive Safety: Risk-Aware LLM Alignment via Long-Horizon Simulation (opens in a new tab)
- NAACL2025CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model (opens in a new tab)
- Proc. The Conference on Empirical Methods in Natural Language Processing (EMNLP2025) FindingsCan Language Models Follow Multiple Turns of Entangled Instructions? (opens in a new tab)
- ACL (T1)Computation Mechanism Behind LLM Position Generalization (opens in a new tab)
- ICML (T1)Contrastive Visual Data Augmentation (opens in a new tab)
- ICLR (T1)CORNSTACK: High-Quality Contrastive Data for Better Code Retrieval and Reranking (opens in a new tab)
202459 papers
- ACL (T1)ActionIE: Action Extraction from Scientific Literature with Programming Languages (opens in a new tab)
- COLING-LREC2024Agenda-Driven Question Generation: A Case Study in the Courtroom Domain (opens in a new tab)
- EMNLP (T1)AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings (opens in a new tab)
- EMNLP WorkshopARMADA: Attribute-Based Multimodal Data Augmentation (opens in a new tab)
- Proc. the International Joint Conference on Artificial Intelligence (IJCAI2024) TutorialBeyond Human Creativity: A Tutorial on Advancements in AI Generated Content
- EACLChem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction (opens in a new tab)
- ICML (T1)CHEMREASONER: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback (opens in a new tab)
- ICLR (T1)CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets (opens in a new tab)
- SigDial2024Dialog Flow Induction for Constrainable LLM-Based Chatbots (opens in a new tab)
- Proc. The Annual Meeting of the Association for Computational Linguistics (ACL2024) FindingsDo LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning (opens in a new tab)
- CVPR2024DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback (opens in a new tab)
- ICLR (T1)Enable Language Models to Implicitly Learn Self-Improvement From Data (opens in a new tab)
202362 papers
- ACL (T1)A Close Look into the Calibration of Pre-trained Language Models (opens in a new tab)
- Proc. The Annual Meeting of the Association for Computational Linguistics (ACL2023) FindingsA Language First Approach for Procedural Planning (opens in a new tab)
- AAAI (T1)ADEPT: A DEbiasing PrompT Framework (opens in a new tab)
- Proc. ACL2023 Workshop on Workshop on Trustworthy Natural Language ProcessingAdversarial Named-Entity Recognition with Word Attributions and Disentanglement (opens in a new tab)
- EMNLP (T1)Adversarial Robustness for Large Language NER models using Disentanglement and Word Attributions (opens in a new tab)
- ICLR (T1)Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation (opens in a new tab)
- EACLBridging the Gap between Native Text and Translated Text through Adversarial Learning: A Case Study on Cross-Lingual Event Extraction (opens in a new tab)
- Proc. ACL2023 Workshop on Document-grounded Dialogue and Conversational Question AnsweringC-PMI: Conditional Pointwise Mutual Information for Turn-level Dialogue Evaluation (opens in a new tab)
- ACL (T1)Code4Struct: Code Generation for Few-Shot Event Structure Prediction (opens in a new tab)
- Proc. The Conference on Empirical Methods in Natural Language Processing (EMNLP2023) FindingsCreator: Disentangling Abstract and Concrete Reasoning of Large Language Models through Tool Creation (opens in a new tab)
- EMNLP (T1)Decoding the Silent Majority: Inducing Belief Augmented Social Graph with Large Language Model for Response Forecasting (opens in a new tab)
- EACLDeepMaven: Deep Question Answering on Long-Distance Movie/TV Show Videos with Multimedia Knowledge Extraction and Synthesis (opens in a new tab)
Where alumni went135 listed, 38% to industry
Industry 31Academia 50
Most often to
- Meta
- Amazon
- Microsoft
Also to
- UIUC
- UCLA
- College of William&Mary
Apply to UIUCFall 2027
UIUC Siebel Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- optional
- English
- TOEFL iBT / IELTS
- Fee
- USD 90
Not yet confirmed for this intake.
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