--- title: "Who cites Catherine Wong — 38 papers of our library" description: "38 papers of the Elamur Research library cite the works of Catherine Wong, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/catherine-wong/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/catherine-wong/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Catherine Wong](https://md.research.elamur.ai/free/en/authors/catherine-wong/) / cited by # Who cites Catherine Wong 40 citations of their works from 38 papers of our library (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← Catherine Wong](https://md.research.elamur.ai/free/en/authors/catherine-wong/) 1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/) 2. [**Program Synthesis with Large Language Models arXiv:2108.07732**Jacob Austin, Augustus Odena, Maxwell Nye, et al.*2021 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-program-synthesis-large-language-models/) 3. [**Abstraction and analogy-making in artificial intelligence**Melanie Mitchell*2021 · 161 citations*](https://md.research.elamur.ai/free/en/papers/mitchell-2021-abstraction-analogy-making-artificial-intelligence/) 4. **[Large Language Model Instruction Following: A Survey of Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/lou-2024-large-language-model-instruction-following/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Renze Lou, Kai Zhang, Wenpeng Yin*2024 · 83 citations* 5. [**Hypothesis Generation with Large Language Models arXiv:2404.04326**Yangqiaoyu Zhou; Haokun Liu; Tejes Srivastava; Hongyuan Mei;, Chenhao Tan*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-hypothesis-generation-large-language/) 6. [**Large Language Models Are Not Strong Abstract Reasoners arXiv:2305.19555**Gael Gendron, Qiming Bao, Michael Witbrock, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/gendron-2023-large-language-models-strong-abstract/) 7. **[Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions](https://md.research.elamur.ai/free/en/papers/zelikman-2023-parsel-algorithmic-reasoning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Eric Zelikman, Qian Huang, Gabriel Poesia, et al.*2023 · 56 citations* 8. **[Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus](https://md.research.elamur.ai/free/en/papers/lee-2024-reasoning-abilities-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Seungpil Lee, Woochang Sim, Donghyeon Shin, et al.*2024 · 38 citations* 9. [**The Surprising Effectiveness of Test-Time Training for Few-Shot Learning arXiv:2411.07279**Ekin Akyürek, Mehul Damani, Adam Zweiger, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/akyurek-2024-surprising-effectiveness-test-time-training/) 10. [**LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations arXiv:2305.18354**Yudong Xu, Wenhao Li, Pashootan Vaezipoor, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-llms-abstraction-reasoning-corpus-successes/) 11. **[Symbolic Regression with a Learned Concept Library](https://md.research.elamur.ai/free/en/papers/grayeli-2024-symbolic-regression-learned-concept-library/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, et al.*2024 · 23 citations* 12. **[Communicating Natural Programs to Humans and Machines](https://md.research.elamur.ai/free/en/papers/acquaviva-2021-communicating-natural-programs-humans-machines/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Samuel Acquaviva, Yewen Pu, Marta Kryven, et al.*2021 · 22 citations* 13. [**Evaluating statistical language models as pragmatic reasoners arXiv:2305.01020**Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lipkin-2023-evaluating-statistical-language-models-pragmatic/) 14. [**Data-driven Discovery with Large Generative Models arXiv:2402.13610**Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/majumder-2024-data-driven-discovery-large-generative/) 15. [**H-ARC: A Robust Estimate of Human Performance on the Abstraction and Reasoning Corpus Benchmark arXiv:2409.01374**Solim LeGris, Wai Keen Vong, Brenden M. Lake, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/legris-2024-h-arc-robust-estimate-human/) 23 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/catherine-wong/) — Catherine Wong