Alejandro Velasco

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All published works

Action	Title	Year	Authors
+ PDF Chat	How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study	2024	Alejandro Velasco Daniel Rodríguez-Cárdenas David N. Palacio Luftar Rahman Alif Denys Poshyvanyk
+ PDF Chat	Measuring Emergent Capabilities of LLMs for Software Engineering: How Far Are We?	2024	Claire O’Brien Daniel Rodríguez-Cárdenas Alejandro Velasco David N. Palacio Denys Poshyvanyk
+ PDF Chat	Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanations	2024	David N. Palacio Daniel Rodríguez-Cárdenas Alejandro Velasco Dipin Khati Kevin Moran Denys Poshyvanyk
+	Which Syntactic Capabilities Are Statistically Learned by Masked Language Models for Code?	2024	Alejandro Velasco David N. Palacio Daniel Rodríguez-Cárdenas Denys Poshyvanyk
+ PDF Chat	Toward a Theory of Causation for Interpreting Neural Code Models	2024	David N. Palacio Alejandro Velasco Nathan Cooper Álvaro Rodríguez Kevin Moran Denys Poshyvanyk
+	Which Syntactic Capabilities Are Statistically Learned by Masked Language Models for Code?	2024	Alejandro Velasco David N. Palacio Daniel Rodríguez-Cárdenas Denys Poshyvanyk
+	Evaluating and Explaining Large Language Models for Code Using Syntactic Structures	2023	David N. Palacio Alejandro Velasco Daniel Rodríguez-Cárdenas Kevin Moran Denys Poshyvanyk

Common Coauthors

Coauthor	Papers Together
David N. Palacio	7
Daniel Rodríguez-Cárdenas	6
Denys Poshyvanyk	6
Kevin Moran	2
Dipin Khati	1
Álvaro Rodríguez	1
Nathan Cooper	1
Luftar Rahman Alif	1
Denys Poshyvanyk	1
Kevin Moran	1
Claire O’Brien	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair	2019	Zimin Chen Steve Kommrusch Michele Tufano Louis-Noël Pouchet Denys Poshyvanyk Martin Monperrus	3
+ PDF Chat	Benchmarking Causal Study to Interpret Large Language Models for Source Code	2023	Daniel Rodríguez-Cárdenas David N. Palacio Dipin Khati Henry Burke Denys Poshyvanyk	3
+ PDF Chat	On learning meaningful assert statements for unit test cases	2020	Cody Watson Michele Tufano Kevin Moran Gabriele Bavota Denys Poshyvanyk	3
+ PDF Chat	A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research	2022	Cody Watson Nathan Cooper David Nader Palacio Kevin Moran Denys Poshyvanyk	3
+ PDF Chat	Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks	2021	Antonio Mastropaolo Simone Scalabrino Nathan Cooper David N. Palacio Denys Poshyvanyk Rocco Oliveto Gabriele Bavota	3
+	An Empirical Study on the Usage of Transformer Models for Code Completion	2021	Matteo Ciniselli Nathan Cooper Luca Pascarella Antonio Mastropaolo Emad Aghajani Denys Poshyvanyk Massimiliano Di Penta Gabriele Bavota	3
+ PDF Chat	An Empirical Study on the Usage of BERT Models for Code Completion	2021	Matteo Ciniselli Nathan Cooper Luca Pascarella Denys Poshyvanyk Massimiliano Di Penta Gabriele Bavota	3
+	CodeBERT: A Pre-Trained Model for Programming and Natural Languages	2020	Zhangyin Feng Daya Guo Duyu Tang Nan Duan Xiaocheng Feng Ming Gong Linjun Shou Bing Qin Ting Liu Daxin Jiang	2
+	AST-Probe: Recovering abstract syntax trees from hidden representations of pre-trained language models	2022	José Antonio Hernández López Martin Weyssow Jesús Sánchez Cuadrado Houari Sahraoui	2
+	Toward a Theory of Causation for Interpreting Neural Code Models	2023	David N. Palacio Nathan Cooper Álvaro Rodríguez Kevin Moran Denys Poshyvanyk	2
+ PDF Chat	Pythia: AI-assisted Code Completion System	2019	Alexey Svyatkovskiy Ying Zhao Sheng‐Yu Fu Neel Sundaresan	2
+	Towards Understanding What Code Language Models Learned	2023	Toufique Ahmed Dian Yu Chengxuan Huang Cathy Wang Prémkumar Dévanbu Kenji Sagae	2
+	RoBERTa: A Robustly Optimized BERT Pretraining Approach	2019	Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy Mike Lewis Luke Zettlemoyer Veselin Stoyanov	2
+ PDF Chat	INSPECT: Intrinsic and Systematic Probing Evaluation for Code Transformers	2023	Anjan Karmakar Romain Robbes	2
+ PDF Chat	Towards Automating Code Review Activities	2021	Rosalia Tufano Luca Pascarella Michele Tufano Denys Poshyvanyk Gabriele Bavota	2
+	PyMT5: multi-mode translation of natural language and Python code with transformers	2020	Colin Clement Dawn Drain Jonathan Timcheck A. Svyatkovskiy Neel Sundaresan	2
+	CodeSearchNet Challenge: Evaluating the State of Semantic Code Search	2019	Hamel Husain Ho-Hsiang Wu Tiferet Gazit Miltiadis Allamanis Marc Brockschmidt	2
+	DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions	2021	Amit Sharma Vasilis Syrgkanis Cheng Zhang Emre Kıcıman	2
+ PDF Chat	IntelliCode compose: code generation using transformer	2020	Alexey Svyatkovskiy Shao Kun Deng Sheng‐Yu Fu Neel Sundaresan	2
+	What Do They Capture? -- A Structural Analysis of Pre-Trained Language Models for Source Code	2022	Yao Wan Wei Zhao Hongyu Zhang Yulei Sui Guandong Xu Hai Jin	2
+	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	2018	Jacob Devlin Ming‐Wei Chang Kenton Lee Kristina Toutanova	2
+	Explainable AI for Pre-Trained Code Models: What Do They Learn? When They Do Not Work?	2022	Ahmad Haji Mohammadkhani Chakkrit Tantithamthavorn Hadi Hemmati	2
+	Are Code Pre-trained Models Powerful to Learn Code Syntax and Semantics?	2022	Wei Ma Mengjie Zhao Xiaofei Xie Qiang Hu Shangqing Liu Jie Zhang Wenhan Wang Yang Liu	2
+ PDF Chat	Knowledge Neurons in Pretrained Transformers	2022	Damai Dai Li Dong Yaru Hao Zhifang Sui Baobao Chang Furu Wei	1
+ PDF Chat	Principles and Practice of Explainable Machine Learning	2021	Vaishak Belle Ioannis Papantonis	1
+	Evaluating Large Language Models Trained on Code	2021	Mark Chen Jerry Tworek Heewoo Jun Qiming Yuan Henrique Pondé de Oliveira Pinto Jared Kaplan Harrison Edwards Yuri Burda Nicholas Joseph Greg Brockman	1
+	To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation	2021	Tom Kocmi Christian Federmann Roman Grundkiewicz Marcin Junczys-Dowmunt Hitokazu Matsushita Arul Menezes	1
+	Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations	2022	Tessa Han Suraj Srinivas Himabindu Lakkaraju	1
+	On the Relationship Between Explanation and Prediction: A Causal View	2022	Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim	1
+	Counterfactual explanations for models of code	2022	Jürgen Cito Işıl Dillig Vijayaraghavan Murali Satish Chandra	1
+ PDF Chat	Holistic Evaluation of Language Models	2023	Rishi Bommasani Percy Liang Tong Lee	1
+	Visualizing and Understanding Recurrent Networks	2015	Andrej Karpathy Justin Johnson Li Fei-Fei	1
+	Large Language Models for Software Engineering: A Systematic Literature Review	2023	Xinyi Hou Yanjie Zhao Yue Liu Yang Zhou Kailong Wang Li Li Xiapu Luo David Lo John Grundy Haoyu Wang	1
+	From statistical to causal learning	2023	Bernhard Schölkopf Julius von Kügelgen	1
+ PDF Chat	On the Reliability and Explainability of Language Models for Program Generation	2024	Yue Liu Chakkrit Tantithamthavorn Yonghui Liu Li Li	1
+	Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmaps	2023	David Lo	1
+	Attention Is All You Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	1
+ PDF Chat	Transportability of Causal and Statistical Relations: A Formal Approach	2011	Judea Pearl Elias Bareinboim	1
+	TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems	2016	Martı́n Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Gregory S. Corrado Andy Davis Jay B. Dean Matthieu Devin	1
+	Towards A Rigorous Science of Interpretable Machine Learning	2017	Finale Doshi‐Velez Been Kim	1
+	Maybe Deep Neural Networks are the Best Choice for Modeling Source Code	2019	Rafael-Michael Karampatsis Charles Sutton	1
+ PDF Chat	BERT Rediscovers the Classical NLP Pipeline	2019	Ian Tenney Dipanjan Das Ellie Pavlick	1
+ PDF Chat	On Learning Meaningful Code Changes Via Neural Machine Translation	2019	Michele Tufano Jevgenija Pantiuchina Cody Watson Gabriele Bavota Denys Poshyvanyk	1
+ PDF Chat	Neural Machine Translation of Rare Words with Subword Units	2016	Rico Sennrich Barry Haddow Alexandra Birch	1
+	Know What You Don’t Know: Unanswerable Questions for SQuAD	2018	Pranav Rajpurkar Robin Jia Percy Liang	1
+ PDF Chat	Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context	2018	Urvashi Khandelwal He He Peng Qi Dan Jurafsky	1
+	On the Properties of Neural Machine Translation: Encoder–Decoder Approaches	2014	Kyunghyun Cho Bart van Merriënboer Dzmitry Bahdanau Yoshua Bengio	1
+ PDF Chat	An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation	2019	Michele Tufano Cody Watson Gabriele Bavota Massimiliano Di Penta Martin White Denys Poshyvanyk	1
+ PDF Chat	The adverse effects of code duplication in machine learning models of code	2019	Miltiadis Allamanis	1
+ PDF Chat	Learning How to Mutate Source Code from Bug-Fixes	2019	Michele Tufano Cody Watson Gabriele Bavota Massimiliano Di Penta Martin White Denys Poshyvanyk	1