← Authors

Tongshuang Wu

27 papers · 2019–2025 · 7 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (51) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (12) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (6) πŸ† Keyword Champion (2) 🧬 Topic Evolution πŸ”₯ Unstoppable (7) ⚑ Prolific Year (8) πŸ’Ž Century Club (27) ❓ The Questioner (2) πŸ—ƒοΈ Keyword Collector (118)

Conferences

ACL (11) EMNLP (8) IJCAI (2) IJCNLP (2) NAACL (2) AAAI (1) AACL (1)

Top co-authors

Vijay Viswanathan (6) Marco Tulio Ribeiro (5) Xinran Zhao (4) Graham Neubig (4) Daniel Weld (3) Diyi Yang (3) Jeffrey Heer (3) Chenyang Yang (3) Yuanchen Bai (2) Dakuo Wang (2)

Research topics

Education (1)

Keywords

large language model (6) data augmentation (4) model evaluation (4) question answering (4) language model (4) text perturbation (3) nlp model (3) sentiment analysis (3) information retrieval (3) question generation (3) counterfactual generation (2) natural language processing (2) human-ai interaction (2) retrieval-augmented generation (2) behavioral testing (2) human-computer interaction (2) synthetic data generation (2) software engineering (2) code generation (2) retrieval augmentation (2)

Papers

Evaluating Mathematical Reasoning Beyond Accuracy AAAI 2025
SPHERE: An Evaluation Card for Human-AI Systems ACL 2025
MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers EMNLP 2025
cAST: Enhancing Code Retrieval-Augmented Generation with Structural Chunking via Abstract Syntax Tree EMNLP 2025
How to Teach Programming in the AI Era? Using LLMs as a Teachable Agent for Debugging (Extended Abstract) IJCAI 2025
SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation NAACL 2025
Synthetic Multimodal Question Generation EMNLP 2024
Better Synthetic Data by Retrieving and Transforming Existing Datasets ACL 2024
Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models ACL 2024
Large Language Models Help Humans Verify Truthfulness – Except When They Are Convincingly Wrong NAACL 2024
Prompt2Model: Generating Deployable Models from Natural Language Instructions EMNLP 2023
NewsSense: Reference-free Verification via Cross-document Comparison EMNLP 2023
Beyond Testers’ Biases: Guiding Model Testing with Knowledge Bases using LLMs EMNLP 2023
BiasX: β€œThinking Slow” in Toxic Content Moderation with Explanations of Implied Social Biases EMNLP 2023
Designing, Evaluating, and Learning from Humans Interacting with NLP Models EMNLP 2023
Measuring Adversarial Datasets AACL 2023
Measuring Adversarial Datasets IJCNLP 2023
DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions ACL 2023
Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension ACL 2022
Tailor: Generating and Perturbing Text with Semantic Controls ACL 2022
Are Shortest Rationales the Best Explanations for Human Understanding? ACL 2022
It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books ACL 2022
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models IJCNLP 2021
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models ACL 2021
Beyond Accuracy: Behavioral Testing of NLP Models with Checklist (Extended Abstract) IJCAI 2021
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList ACL 2020
Errudite: Scalable, Reproducible, and Testable Error Analysis ACL 2019