---
title: "Who cites Marc Brockschmidt — 576 papers of our library"
description: "576 papers of the Elamur Research library cite the works of Marc Brockschmidt, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/marc-brockschmidt/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/marc-brockschmidt/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Marc Brockschmidt](https://md.research.elamur.ai/free/en/authors/marc-brockschmidt/) / cited by

# Who cites Marc Brockschmidt

642 citations of their works from 576 papers of our library (of the 149,439 whose bibliographies we read) · 95 with a page here, the most cited first · [← Marc Brockschmidt](https://md.research.elamur.ai/free/en/authors/marc-brockschmidt/)

1. **[A Comprehensive Survey on Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/) [IEEE Transactions on Neural Networks and Learning Systems](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-neural-networks-and-learning-systems/)**Zonghan Wu, Shirui Pan, Fengwen Chen, et al.*2019 · 10,312 citations*
2. [**Graph Attention Networks arXiv:1710.10903**Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al.*2017 · 9,035 citations*](https://md.research.elamur.ai/free/en/papers/veli-vckovic-2017-graph-attention-networks/)
3. [**Semi-Supervised Classification with Graph Convolutional Networks arXiv:1609.02907**Thomas N. Kipf, Max Welling*2016 · 9,023 citations*](https://md.research.elamur.ai/free/en/papers/kipf-2016-semi-supervised-classification-graph-convolutional/)
4. [**Inductive Representation Learning on Large Graphs arXiv:1706.02216**William L. Hamilton, Rex Ying, Jure Leskovec*2017 · 4,795 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2017-inductive-representation-learning-large-graphs/)
5. [**Neural Message Passing for Quantum Chemistry arXiv:1704.01212**Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, et al.*2017 · 3,793 citations*](https://md.research.elamur.ai/free/en/papers/gilmer-2017-neural-message-passing-quantum-chemistry/)
6. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,967 citations*
7. [**Evaluating Large Language Models Trained on Code arXiv:2107.03374**Mark Chen, Jerry Tworek, Heewoo Jun, et al.*2021 · 2,659 citations*](https://md.research.elamur.ai/free/en/papers/chen-2021-evaluating-large-language-models-trained/)
8. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,335 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
9. **[Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering](https://md.research.elamur.ai/free/en/papers/defferrard-2016-convolutional-neural-networks-graphs-fast/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Defferrard, Xavier Bresson, Pierre Vandergheynst*2016 · 1,861 citations*
10. [**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/)
11. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,663 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
12. **[Competition-Level Code Generation with AlphaCode](https://md.research.elamur.ai/free/en/papers/li-2022-competition-level-code-generation-alphacode/) [Science](https://md.research.elamur.ai/free/en/venues/science/)**Yujia Li, David Choi, Junyoung Chung, et al.*2022 · 1,564 citations*
13. [**Fast Graph Representation Learning with PyTorch Geometric arXiv:1903.02428**Matthias Fey, Jan Eric Lenssen*2019 · 1,440 citations*](https://md.research.elamur.ai/free/en/papers/fey-2019-fast-graph-representation-learning-pytorch/)
14. [**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/)
15. **[Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/marcheggiani-2017-encoding-sentences-graph-convolutional-networks/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Diego Marcheggiani, Ivan Titov*2017 · 1,106 citations*
16. **[MTEB: Massive Text Embedding Benchmark](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-mteb-massive-text-embedding-benchmark/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.*2022 · 1,032 citations*
17. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2021 · 750 citations*
18. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues? arXiv:2310.06770**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 704 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/)
19. [**How Powerful are Graph Neural Networks? arXiv:1810.00826**Keyulu Xu, Weihua Hu, Jure Leskovec, et al.*2018 · 655 citations*](https://md.research.elamur.ai/free/en/papers/xu-2018-powerful-graph-neural-networks/)
20. [**A simple neural network module for relational reasoning arXiv:1706.01427**Adam Santoro, David Raposo, David G. T. Barrett, et al.*2017 · 632 citations*](https://md.research.elamur.ai/free/en/papers/santoro-2017-simple-neural-network-module-relational/)
21. **[Cross-Sentence N-ary Relation Extraction with Graph LSTMs](https://md.research.elamur.ai/free/en/papers/peng-2017-cross-sentence-n-ary-relation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nanyun Peng, Hoifung Poon, Chris Quirk, et al.*2017 · 557 citations*
22. **[Inferring and Executing Programs for Visual Reasoning](https://md.research.elamur.ai/free/en/papers/johnson-2017-inferring-executing-programs-visual-reasoning/) [IEEE International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-computer-vision-iccv/)**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2017 · 557 citations*
23. [**Show your work: Scratchpads for intermediate computation with language models***2021 · 473 citations*](https://md.research.elamur.ai/free/en/papers/al-2021-show-your-work-scratchpads-intermediate/)
24. **[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/beck-2018-graph-sequence-learning-gated-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Beck, Gholamreza Haffari, Trevor Cohn*2018 · 459 citations*
25. [**Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding arXiv:1810.02338**Kexin Yi, Jiajun Wu, Chuang Gan, et al.*2018 · 407 citations*](https://md.research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/)
26. [**Towards General Text Embeddings with Multi-stage Contrastive Learning arXiv:2308.03281**Zehan Li, Xin Zhang, Yanzhao Zhang, et al.*2023 · 384 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-towards-general-text-embeddings-multi/)
27. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
28. [**Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference arXiv:2412.13663**Benjamin Warner, Antoine Chaffin, Benjamin Clavié, et al.*2024 · 358 citations*](https://md.research.elamur.ai/free/en/papers/warner-2024-smarter-better-faster-longer-modern/)
29. [**GraphCodeBERT: Pre-training Code Representations with Data Flow arXiv:2009.08366**Daya Guo, Shuo Ren, Shuai Lu, et al.*2021 · 332 citations*](https://md.research.elamur.ai/free/en/papers/guo-2021-graphcodebert-pre-training-code-representations/)
30. [**Text and Code Embeddings by Contrastive Pre-Training arXiv:2201.10005**Arvind Neelakantan, Tao Xu, Raul Puri, et al.*2022 · 323 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2022-text-code-embeddings-contrastive-pre/)
31. [**The Adverse Effects of Code Duplication in Machine Learning Models of Code arXiv:1812.06469**Miltiadis Allamanis*2018 · 319 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2018-adverse-effects-code-duplication-machine/)
32. **[CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/le-2022-coderl-mastering-code-generation-through/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.*2022 · 297 citations*
33. **[Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing](https://md.research.elamur.ai/free/en/papers/bogin-2019-representing-schema-structure-graph-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ben Bogin, Jonathan Berant, Matt Gardner*2019 · 272 citations*
34. [**Learning to Optimize Tensor Programs arXiv:1805.08166**Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.*2019 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-learning-optimize-tensor-programs/)
35. [**Learning a SAT Solver from Single-Bit Supervision arXiv:1802.03685**Daniel Selsam, Matthew Lamm, Benedikt Bünz, et al.*2018 · 232 citations*](https://md.research.elamur.ai/free/en/papers/selsam-2018-learning-sat-solver-single-bit/)
36. **[Tracking the World State with Recurrent Entity Networks](https://md.research.elamur.ai/free/en/papers/henaff-2016-tracking-world-state-recurrent-entity/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Mikael Henaff, Jason Weston, Arthur Szlam, et al.*2016 · 228 citations*
37. **[Retrieval Augmented Code Generation and Summarization](https://md.research.elamur.ai/free/en/papers/parvez-2021-retrieval-augmented-code-generation-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.*2021 · 193 citations*
38. **[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://md.research.elamur.ai/free/en/papers/guo-2019-densely-connected-graph-convolutional-networks/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Yan Zhang, Zhiyang Teng, et al.*2019 · 193 citations*
39. **[Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions](https://md.research.elamur.ai/free/en/papers/zhang-2019-editing-based-sql-query-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rui Zhang, Tao Yu, Heyang Er, et al.*2019 · 177 citations*
40. **[KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation](https://md.research.elamur.ai/free/en/papers/chen-2020-kgpt-knowledge-grounded-pre-training/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhu Chen, Yu Su, Xifeng Yan, et al.*2020 · 174 citations*
41. [**SantaCoder: don't reach for the stars! arXiv:2301.03988**Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.*2023 · 167 citations*](https://md.research.elamur.ai/free/en/papers/allal-2023-santacoder-don-t-reach-stars/)
42. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations*
43. [**Semantic Neural Machine Translation Using AMR**Linfeng Song, Daniel Gildea, Yue Zhang, et al.*2019 · 159 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-semantic-neural-machine-translation-amr/)
44. **[PyMT5: multi-mode translation of natural language and Python code with transformers](https://md.research.elamur.ai/free/en/papers/clement-2020-pymt5-multi-mode-translation-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Colin Clement, Dawn Drain, Jonathan Timcheck, et al.*2020 · 158 citations*
45. [**CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks arXiv:2105.12655**Ruchir Puri, David S. Kung, Geert Janssen, et al.*2021 · 141 citations*](https://md.research.elamur.ai/free/en/papers/puri-2021-codenet-large-scale-ai-code/)
46. [**Token-Budget-Aware LLM Reasoning arXiv:2412.18547**Tingxu Han, Zhenting Wang, Chunrong Fang, et al.*2024 · 136 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-token-budget-aware-llm-reasoning/)
47. **[Semantic Graphs for Generating Deep Questions](https://md.research.elamur.ai/free/en/papers/pan-2020-semantic-graphs-generating-deep-questions/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liangming Pan, Yuxi Xie, Yansong Feng, et al.*2020 · 134 citations*
48. **[Task-aware Retrieval with Instructions](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 132 citations*
49. [**Learning to Represent Programs with Graphs arXiv:1711.00740**Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi*2017 · 127 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2017-learning-represent-programs-graphs/)
50. [**Nomic Embed: Training a Reproducible Long Context Text Embedder arXiv:2402.01613**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 126 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)
51. [**A Systematic Evaluation of Large Language Models of Code arXiv:2202.13169**Frank F. Xu, Uri Alon, Graham Neubig, et al.*2022 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xu-2022-systematic-evaluation-large-language-models/)
52. **[ReACC: A Retrieval-Augmented Code Completion Framework](https://md.research.elamur.ai/free/en/papers/lu-2022-reacc-retrieval-augmented-code-completion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuai Lu, Nan Duan, Hojae Han, et al.*2022 · 125 citations*
53. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
54. [**Parallel Iterative Edit Models for Local Sequence Transduction arXiv:1910.02893**Abhijeet Awasthi, Sunita Sarawagi, Rasna Goyal, et al.*2019 · 112 citations*](https://md.research.elamur.ai/free/en/papers/awasthi-2019-parallel-iterative-edit-models-local/)
55. **[AMR-To-Text Generation with Graph Transformer](https://md.research.elamur.ai/free/en/papers/wang-2020-amr-text-generation-graph-transformer/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tianming Wang, Xiaojun Wan, Hanqi Jin*2020 · 108 citations*
56. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
57. **[Who Wrote this Code? Watermarking for Code Generation](https://md.research.elamur.ai/free/en/papers/lee-2024-who-wrote-this-code-watermarking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taehyun Lee, Seokhee Hong, Jaewoo Ahn, et al.*2024 · 103 citations*
58. [**SPoC: Search-based Pseudocode to Code arXiv:1906.04908**Sumith Kulal, Panupong Pasupat, Kartik Chandra, et al.*2019 · 96 citations*](https://md.research.elamur.ai/free/en/papers/kulal-2019-spoc-search-based-pseudocode-code/)
59. **[InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback](https://md.research.elamur.ai/free/en/papers/yang-2023-intercode-standardizing-benchmarking-interactive-coding/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.*2023 · 95 citations*
60. [**Learning to Prove Theorems via Interacting with Proof Assistants arXiv:1905.09381**Kaiyu Yang, Jia Deng*2019 · 90 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-learning-prove-theorems-interacting-proof/)
61. [**Multi-lingual Evaluation of Code Generation Models arXiv:2210.14868**Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, et al.*2022 · 86 citations*](https://md.research.elamur.ai/free/en/papers/athiwaratkun-2022-multi-lingual-evaluation-code-generation/)
62. **[OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-opencoder-open-cookbook-top-tier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.*2025 · 81 citations*
63. [**BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval arXiv:2407.12883**Hongjin Su, Howard Yen, Mengzhou Xia, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/)
64. **[JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation](https://md.research.elamur.ai/free/en/papers/agashe-2019-juice-large-scale-distantly-supervised/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer*2019 · 75 citations*
65. [**code2seq: Generating Sequences from Structured Representations of Code arXiv:1808.01400**Uri Alon, Shaked Brody, Omer Levy, et al.*2018 · 72 citations*](https://md.research.elamur.ai/free/en/papers/alon-2018-code2seq-generating-sequences-structured-representations/)
66. [**Program Synthesis Foundations and Trends in Programming Languages 4(1-2)**Sumit Gulwani, Oleksandr Polozov, Rishabh Singh*2017 · 63 citations*](https://md.research.elamur.ai/free/en/papers/gulwani-2017-program-synthesis/)
67. **[XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2024 · 51 citations*
68. [**PanGu-Coder: Program Synthesis with Function-Level Language Modeling arXiv:2207.11280**Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.*2022 · 49 citations*](https://md.research.elamur.ai/free/en/papers/christopoulou-2022-pangu-coder-program-synthesis/)
69. **[CoCoMIC: Code Completion by Jointly Modeling In-file and Cross-file Context](https://md.research.elamur.ai/free/en/papers/ding-2024-cocomic-code-completion-jointly-modeling/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yangruibo Ding, Zijian Wang, Wasi Ahmad, et al.*2024 · 45 citations*
70. [**xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval arXiv:2303.03004**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/khan-2023-xcodeeval-large-scale-multilingual-multitask/)
71. [**EuroBERT: Scaling Multilingual Encoders for European Languages arXiv:2503.05500**Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2025-eurobert-scaling-multilingual-encoders-european/)
72. [**ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages arXiv:2212.06742**Yekun Chai, Shuohuan Wang, Chao Pang, et al.*2022 · 32 citations*](https://md.research.elamur.ai/free/en/papers/chai-2022-ernie-code-english-centric/)
73. **[CoIR: A Comprehensive Benchmark for Code Information Retrieval Models](https://md.research.elamur.ai/free/en/papers/li-2025-coir-comprehensive-benchmark-code-information/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyang Li, Kuicai Dong, Yi Quan Lee, et al.*2025 · 29 citations*
74. **[L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2024-l2ceval-evaluating-language-code-generation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.*2024 · 27 citations*
75. **[MdEval: Massively Multilingual Code Debugging](https://md.research.elamur.ai/free/en/papers/liu-2026-mdeval-massively-multilingual-code-debugging/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shukai Liu, Linzheng Chai, Jian Yang, et al.*2026 · 12 citations*
76. [**Stable Code Technical Report arXiv:2404.01226**Nikhil Pinnaparaju, Reshinth Adithyan, Duy Phung, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/pinnaparaju-2024-stable-code-technical-report/)
77. **[Case2Code: Scalable Synthetic Data for Code Generation](https://md.research.elamur.ai/free/en/papers/shao-2025-case2code-scalable-synthetic-data-code/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yunfan Shao, Linyang Li, Yichuan Ma, et al.*2025 · 7 citations*
78. [**From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey arXiv:2108.11451**Giuseppe Marra, Sebastijan Dumančić, Robin Manhaeve, et al.*2021 · 3 citations*](https://md.research.elamur.ai/free/en/papers/marra-2021-statistical-relational-neurosymbolic-artificial/)
79. **[XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants](https://md.research.elamur.ai/free/en/papers/storek-2026-xoxo-stealthy-cross-origin-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adam Štorek, Mukur Gupta, Noopur Bhatt, et al.*2026 · 2 citations*
80. **[PBEBench: A Multi-Step Programming by Examples Reasoning Benchmark inspired by Historical Linguistics](https://md.research.elamur.ai/free/en/papers/naik-2026-pbebench-multi-step-programming-examples/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Atharva Naik, Darsh Agrawal, Prakam, et al.*2026 · 1 citation*
81. **[TransformerTrio at SemEval-2026 Task 13: Navigating Domain Shift and Representation Instability in Machine-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/patel-2026-transformertrio-semeval-2026-task-13/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Avi Patel, Manthan Laddha, Pushti Sapovadiya, et al.*2026 · 1 citation*
82. **[A Survey of Reasoning-Intensive Retrieval: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/wei-2026-survey-reasoning-intensive-retrieval-progress/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyang Wei, Tingyu Song, Siyue Zhang, et al.*2026*
83. **[FlowHN: Adaptive Token Routing for Efficient Parallel Hybrid Networks](https://md.research.elamur.ai/free/en/papers/moradi-2026-flowhn-adaptive-token-routing-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Mahdi Moradi, Walid Ahmed, Shuangyue Wen, et al.*2026*
84. **[From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code Completion](https://md.research.elamur.ai/free/en/papers/wang-2026-logical-computational-sparsity-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanli Wang, Yanlin Wang, Bowen Zhang, et al.*2026*
85. **[HybridCodeAuthorship: A Benchmark Dataset for Line-Level Code Authorship Detection](https://md.research.elamur.ai/free/en/papers/patterson-2026-hybridcodeauthorship-benchmark-dataset-line-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Luke S. Patterson, Li Wang, Adam Faulkner*2026*
86. **[LEDGER: Scaling Agentic Document Editing with Dependency-aware Graph Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2026-ledger-scaling-agentic-document-editing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hang Wang, Utkarsh Garg, Reza Davari, et al.*2026*
87. **[Let Retrievers Think Before Action: Thought-Augmented Embedding for Dense Retrieval](https://md.research.elamur.ai/free/en/papers/yan-2026-let-retrievers-think-before-action/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruiran Yan, Wen Xiong, Ze Liu, et al.*2026*
88. **[Peek2: Regex-free Byte-level Byte-Pair Encoding Pretokenizer for LLM Inference on Edge Devices](https://md.research.elamur.ai/free/en/papers/zai-2026-peek2-regex-free-byte-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liu Zai, Iraklis A. Klampanos*2026*
89. **[Segmentation Fault at SemEval-2026 Task 13: A Regularization-First Approach with Generator-Based Out-of-Distribution Splits for Detecting AI-Generated Code](https://md.research.elamur.ai/free/en/papers/rao-2026-segmentation-fault-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Lakshmi Priya Swaminatha Rao, Dhannya Santhakumari Madhavan, Sreya Kodeswaran, et al.*2026*
90. **[SemEval-2026 Task 13: Fine-tuned CodeBERT with Stratified Balancing, Dynamic Threshold Optimization, and Logit Bias Correction for Robust Multi-Language AI Code Detection](https://md.research.elamur.ai/free/en/papers/s-2026-semeval-2026-task-13-fine/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Udaythalavesh S, Rajalakshmi Sivanaiah, Angel Deborah S*2026*
91. **[Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding](https://md.research.elamur.ai/free/en/papers/storek-2026-sense-sensitivity-examining-influence-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adam Štorek, Mukur Gupta, Samira Hajizadeh, et al.*2026*
92. **[SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair](https://md.research.elamur.ai/free/en/papers/zhang-2026-synthfix-adaptive-neuro-symbolic-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Zhang, Jieyu Li, Kexin Pei, et al.*2026*
93. **[The Challenge of Identifying the Origin of Black-Box Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-challenge-identifying-origin-black-box/) [Workshop on Privacy in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/privatenlp/)**Ziqing Yang, Yixin Wu, Yun Shen, et al.*2026*
94. **[Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code Datasets](https://md.research.elamur.ai/free/en/papers/xiao-2026-train-vain-functionality-preserving-poisoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Xiao, Jiaming Wang, Yuchen Chen, et al.*2026*
95. **[Review and Performance Comparison of Deep Knowledge Tracing Models (深度知识追踪模型综述和性能比较)](https://md.research.elamur.ai/free/en/papers/wang-2022-performance-comparison-deep/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yu Wang (王宇), Mengxia Zhu (朱梦霞), Shanghui Yang (杨尚辉), et al.*2022*

481 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/marc-brockschmidt/) — Marc Brockschmidt