mlsanityData to 7 Oct 2026

What GPT Knows About Who is Who

arXiv 2205.07407 ↗First posted 16 May 2022cs.CL cs.LGcited by 7

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Abstract (arXiv)

Coreference resolution -- which is a crucial task for understanding discourse and language at large -- has yet to witness widespread benefits from large language models (LLMs). Moreover, coreference resolution systems largely rely on supervised labels, which are highly expensive and difficult to annotate, thus making it ripe for prompt engineering. In this paper, we introduce a QA-based prompt-engineering method and discern textitgenerative, pre-trained LLMs' abilities and limitations toward the task of coreference resolution. Our experiments show that GPT-2 and GPT-Neo can return valid answers, but that their capabilities to identify coreferent mentions are limited and prompt-sensitive, leading to inconsistent results.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 17 of its 22 references that are in the map. First posted on arXiv 16 May 2022.

Builds on

17 of 22 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  5. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  6. 2020The Pile: An 800GB Dataset of Diverse Text for Language Modelingcited by 2,346
  7. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  8. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
  9. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
  10. 2021Multimodal Few-Shot Learning with Frozen Language Modelscited by 657
  11. 2018AllenNLP: A Deep Semantic Natural Language Processing Platformcited by 347
  12. 2021True Few-Shot Learning with Language Modelscited by 343
5 more
  1. 2021Surface Form Competition: Why the Highest Probability Answer Isn't Always Rightcited by 256
  2. 2017End-to-end Neural Coreference Resolutioncited by 240
  3. 2021Improving and Simplifying Pattern Exploiting Trainingcited by 97
  4. 2017Few-Shot Learning Through an Information Retrieval Lenscited by 51
  5. 2020Streamlining Cross-Document Coreference Resolution: Evaluation and Modelingcited by 16

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Cited by year

Citing papers per year: 2022: 2; 2023: 2; 2024: 2; 2025: 1.

7 papers.

  1. 2022Large Language Models are Few-Shot Clinical Information Extractorscited by 206
  2. 2023What happens before and after: Multi-Event Commonsense in Event Coreference Resolutioncited by 12
  3. 2022Few-Shot Anaphora Resolution in Scientific Protocols via Mixtures of In-Context Expertscited by 10
  4. 2024GAMedX: Generative AI-based Medical Entity Data Extractor Using Large Language Modelscited by 5
  5. 2024Inferring Scientific Cross-Document Coreference and Hierarchy with Definition-Augmented Relational Reasoningcited by 2
  6. 2023An Empirical Study of Benchmarking Chinese Aspect Sentiment Quad Predictioncited by 0
  7. 2025CorefInst: Leveraging LLMs for Multilingual Coreference Resolutioncited by 0