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Andres Codas

Andres Codas has 3 papers in our library, in 2022–2024, most of them on Language models & pretraining, Reasoning; often with Arindam Mitra, Guoqing Zheng, Luciano Del Corro.

3 papers in our library · 2022–2024

OpenAlex · ORCID · h-index 10 · 38 works · 296 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 195 times in our library · ⭐ Paper Stars ranking: #6253

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢MicrosoftRedmond · United States2022–2024 · 7 paperscurrent🎓Norwegian University of Science and TechnologyTrondheim · Norway2012–2020 · 8 papersEducation 2012–2015 · Ph.D, Engineering Cybernetics🎓Universidade Federal de Santa CatarinaFlorianópolis · Brazil2008–2012 · 7 papers🔬IBM Research - BrazilRio de Janeiro · Brazil2016–2021 · 4 papersEmployment since 2016 · Research Staff Member🏢IBMArmonk · United States2017–2021 · 3 papers🏢IBMSão Paulo · Brazil2020–2021 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 2 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 workSoftware · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20241 paper20231 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Orca 2: Teaching Small Language Models How to Reason (2023 · 162 citations)
    Small language models (below roughly 10B parameters) typically trail frontier LLMs in zero-shot reasoning.
  2. AgentInstruct: Toward Generative Teaching with Agentic Flows (2024 · 42 citations)
    Post-training language models on synthetic data is appealing, but such data often lacks quality and variety.
  3. Fault-Aware Neural Code Rankers (2022 · 39 citations)
    Large code-generation models often produce a correct Python program somewhere among many samples, but the first sample is frequently wrong.

 Co-authors here

12 of 16 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 195 times (of the 149,439 papers whose bibliographies we read); 54 citing papers with a page here →.

Updated

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