Jordan Boyd-Graber
Professor
Works on evaluating language models and building interactive AI, including question answering and human-AI collaboration.
Jordan Boyd-Graber's lab at NTU works on large language models, knowledge, QA & retrieval and human-AI collaboration & trust. 49 papers since 2023, 27 at top venues, mostly EMNLP and ACL. 12 PhD students. 33 alumni.
At a glance
- papers, 2023–2026
- 13/ year
- at T1 venues
- 55%
- PhD students
- 12
- MS students
- 0
- alumni listed
- 33
Papers by yearfrom the lab homepage, 2023–2026
- 13 papers2026 · T1 7 · collecting
- 15 papers2025 · T1 10
- 14 papers2024 · T1 5
- 7 papers2023 · T1 5
T1 venuesOtherVenues: EMNLP, ACL, ICLR, NeurIPS
Research focuspaper titles that use each topic's words
- Large language models18 papers
- Knowledge, QA & retrieval9 papers
- Human-AI collaboration & trust8 papers
- evaluating4 papers
- human-ai collaboration0 papers
Paper list
From the lab homepage.
202613 papers
- Findings of the Association for Computational LinguisticsAI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering? (opens in a new tab)
- Findings of the Association for Computational LinguisticsAUDITA: A New Dataset to Audit Whether Humans or AI are Better at Audio QA (opens in a new tab)
- ACL (T1)BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks (opens in a new tab)
- Findings of Empirical Methods in Natural Language ProcessingCANVAS: Continuity-Aware Narrative Generation via Visual Agentic Storyboarding (opens in a new tab)
- EMNLP (T1)Check The Scoreboard: An Analysis of Scoring Schemes on Multiple-Choice Evaluation (opens in a new tab)
- EMNLP (T1)DiscoTrace: Representing and Comparing Answering Strategies of Humans and LLMs in Information-Seeking Question Answering (opens in a new tab)
- EMNLP (T1)Helping Figures Tell their Story! Paper-Grounded Video Generation Explaining Complex Scientific Figures (opens in a new tab)
- ACL (T1)Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users (opens in a new tab)
- Findings of the Association for Computational LinguisticsLarge Language Models Are Effective Human Annotation Assistants, But Not Good Independent Annotators (opens in a new tab)
- ACL (T1)Measuring User's Mental Models of Speech Translation in Human-MT Collaboration (opens in a new tab)
- ICLR (T1)Self-Rewarding Vision-Language Model via Reasoning Decomposition
- European Association for Computational LinguisticsSMART-Editor: A Multi-Agent Framework for Human-Like Design Editing with Structural Integrity
202515 papers
- EMNLP (T1)A Good Plan is Hard to Find: Aligning Models with Preferences is Misaligned with What Helps Users (opens in a new tab)
- North American Association for Computational LinguisticsADVSCORE: A Metric for the Evaluation and Creation of Adversarial Benchmarks (opens in a new tab)
- EMNLP (T1)Discrepancy Detection at the Data Level: Toward Consistent Multilingual Question Answering (opens in a new tab)
- ACL (T1)GRACE: A Granular Benchmark for Evaluating Model Calibration against Human Calibration (opens in a new tab)
- EMNLP (T1)Group Preference Alignment: Customizing LLM Responses from In-Situ Conversations Only When Needed (opens in a new tab)
- ACL (T1)LLMs Struggle to Describe the Haystack without Human Help: A Social Science-Inspired Evaluation of Topic Models (opens in a new tab)
- Annual Conference of the Nations of the Americas Chapter of the Association for Computational LinguisticsMoDS: Moderating a Mixture of Document Speakers to Summarize Debatable Queries in Document Collections (opens in a new tab)
- ACL (T1)No Questions are Stupid and but some are Poorly Posed: Understanding Poorly-Posed Information-Seeking Questions (opens in a new tab)
- Annual Conference of the Nations of the Americas Chapter of the Association for Computational LinguisticsPersonalized Help for Optimizing Low-Skilled Users' Strategy (opens in a new tab)
- ACL (T1)ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering (opens in a new tab)
- Annual Conference of the Nations of the Americas Chapter of the Association for Computational LinguisticsReverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer? (opens in a new tab)
- Findings of the Association for Computational LinguisticsShould I Trust You? Detecting Deception in Negotiations using Counterfactual RL (opens in a new tab)
202414 papers
- EMNLP (T1)A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick (opens in a new tab)
- Findings of the Empirical Methods in Natural Language ProcessingAUTOHALLUSION: Automatic Generation of Hallucination Benchmarks for Vision-Language Models (opens in a new tab)
- EMNLP (T1)Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA (opens in a new tab)
- EMNLP (T1)KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students (opens in a new tab)
- North American Association for Computational LinguisticsLarge Language Models Help Humans Verify Truthfulness---Except When They Are Convincingly Wrong (opens in a new tab)
- ACL (T1)More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play (opens in a new tab)
- Findings of the Empirical Methods in Natural Language ProcessingPEDANTS (Precise Evaluations of Diverse Answer Nominee Text for Skinflints): Use Evaluation Metrics Wisely---Efficient Evaluation Analysis and Benchmarking for Open-Domain Question Answering (opens in a new tab)
- North American Association for Computational LinguisticsPregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering (opens in a new tab)
- European Association for Computational LinguisticsPresentations by the People, for the People: Harnessing LLMs for Generating Persona-Aware Slides from Documents (opens in a new tab)
- Journal of Medical Internet Research: Journal of Formative ResearchRandomized Pilot of Rosie, a Health Education Question-and-Answer Chatbot for New Mothers (opens in a new tab)
- Linguistic Resources and Evaluation ConferenceRapidly Piloting Real-time Linguistic Assistance for Simultaneous Interpreters with Untrained Bilingual Surrogates (opens in a new tab)
- Findings of the Empirical Methods in Natural Language ProcessingSciDoc2Diagrammer-MAF: Towards Generation of Scientific Diagrams from Documents guided by Multi-Aspect Feedback Refinement (opens in a new tab)
20237 papers
- EMNLP (T1)Automatic Explicitation to Bridge the Background Knowledge Gap in Translation and its Evaluation with Multilingual QA (opens in a new tab)
- Findings of Empirical Methods in Natural Language ProcessingGetting \underlineMoRE out of \underlineMixture \underlineof Language Model \underlineReasoning \underlineExperts (opens in a new tab)
- EMNLP (T1)Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition (opens in a new tab)
- EMNLP (T1)Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines (opens in a new tab)
- Journal of Public Health Management and PracticePractical Guidance for the Development of Rosie, a Health Education Question-and-Answer Chatbot for New Mothers (opens in a new tab)
- ACL (T1)Program Chairs' Report on Peer Review at ACL 2023 (opens in a new tab)
- ICLR (T1)Prompting GPT-3 To Be Reliable (opens in a new tab)
Where alumni went33 listed
Apply to NTUFall 2027
Not announced yet
Computing and Data Science PhD
- Round
- Main
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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