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ORCIDMoa Johansson 0001
Person information
- affiliation: Chalmers University of Technology, Gothenburg, Sweden
- affiliation (PhD 2009): University of Edinburgh, School of Informatics, Edinburgh, UK
Other persons with the same name
- Moa Johansson 0002
![[0009-0007-4965-9243]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0009-0007-4965-9243")
— ShareMusic & Performing Arts, Gränna, Sweden
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2020 – today
- 2025
[c30]Denitsa Saynova, Lovisa Hagström, Moa Johansson, Richard Johansson, Marco Kuhlmann:
Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion. ACL (Findings) 2025: 18322-18349- [i18]Denitsa Saynova, Kajsa Hansson, Bastiaan Bruinsma, Annika Fredén, Moa Johansson:
Identifying Non-Replicable Social Science Studies with Language Models. CoRR abs/2503.10671 (2025) - [i17]Yousef Alhessi, Sólrún Halla Einarsdóttir, George Granberry, Emily First, Moa Johansson, Sorin Lerner, Nicholas Smallbone:
Lemmanaid: Neuro-Symbolic Lemma Conjecturing. CoRR abs/2504.04942 (2025) - [i16]George Granberry, Wolfgang Ahrendt, Moa Johansson:
Seeking Specifications: The Case for Neuro-Symbolic Specification Synthesis. CoRR abs/2504.21061 (2025) - [i15]Nicolas Audinet de Pieuchon, Adel Daoud, Connor T. Jerzak, Moa Johansson, Richard Johansson:
Benchmarking Debiasing Methods for LLM-based Parameter Estimates. CoRR abs/2506.09627 (2025) - 2024
- [c29]Bastiaan Bruinsma, Annika Fredén, Kajsa Hansson, Moa Johansson, Pasko Kisic-Merino, Denitsa Saynova:
Setting the AI Agenda - Evidence from Sweden in the ChatGPT Era. AEQUITAS@ECAI 2024 - [c28]George Granberry, Wolfgang Ahrendt, Moa Johansson:
Specify What? Enhancing Neural Specification Synthesis by Symbolic Methods. IFM 2024: 307-325 - [c27]Sólrún Halla Einarsdóttir, Márton Hajdú, Moa Johansson, Nicholas Smallbone, Martin Suda:
Lemma Discovery and Strategies for Automated Induction. IJCAR (1) 2024: 214-232 - [c26]George Granberry, Wolfgang Ahrendt, Moa Johansson:
Towards Integrating Copiloting and Formal Methods - Building Blocks, Architecture, and Challenges. ISoLA (3) 2024: 144-158 - [c25]Daniel Enström, Viktor Kjellberg, Moa Johansson:
Reasoning in Transformers - Mitigating Spurious Correlations and Reasoning Shortcuts. NeSy (2) 2024: 207-221 - [i14]Daniel Enström, Viktor Kjellberg, Moa Johansson:
Reasoning in Transformers - Mitigating Spurious Correlations and Reasoning Shortcuts. CoRR abs/2403.11314 (2024) - [i13]Nicolas Audinet de Pieuchon, Adel Daoud, Connor Thomas Jerzak, Moa Johansson, Richard Johansson:
Can Large Language Models (or Humans) Distill Text? CoRR abs/2403.16584 (2024) - [i12]George Granberry, Wolfgang Ahrendt, Moa Johansson:
Specify What? Enhancing Neural Specification Synthesis by Symbolic Methods. CoRR abs/2406.15540 (2024) - [i11]Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Emil Carlsson, Moa Johansson:
Learning Efficient Recursive Numeral Systems via Reinforcement Learning. CoRR abs/2409.07170 (2024) - [i10]Bastiaan Bruinsma, Annika Fredén, Kajsa Hansson, Moa Johansson, Pasko Kisic-Merino, Denitsa Saynova:
Setting the AI Agenda - Evidence from Sweden in the ChatGPT Era. CoRR abs/2409.16946 (2024) - [i9]Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Vikas Garg, Moa Johansson:
ACE: Abstractions for Communicating Efficiently. CoRR abs/2409.20120 (2024) - [i8]Denitsa Saynova, Lovisa Hagström, Moa Johansson, Richard Johansson, Marco Kuhlmann:
Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion. CoRR abs/2410.14405 (2024) - 2023
- [c24]Brian Bonafilia, Bastiaan Bruinsma, Denitsa Saynova, Moa Johansson:
Sudden Semantic Shifts in Swedish NATO discourse. ACL (student) 2023: 184-193 - [c23]Lovisa Hagström, Denitsa Saynova, Tobias Norlund, Moa Johansson, Richard Johansson:
The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models. EMNLP 2023: 5457-5476 - [c22]Moa Johansson, Nicholas Smallbone:
Exploring Mathematical Conjecturing with Large Language Models. NeSy 2023: 62-77 - [c21]Denitsa Saynova, Bastiaan Bruinsma, Moa Johansson, Richard Johansson:
Class Explanations: the Role of Domain-Specific Content and Stop Words. NoDaLiDa 2023: 103-112 - [c20]Moa Johansson:
What Can Large Language Models Do for Theorem Proving and Formal Methods? AISoLA 2023: 391-394 - [i7]Lovisa Hagström, Denitsa Saynova, Tobias Norlund, Moa Johansson, Richard Johansson:
The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models. CoRR abs/2311.01307 (2023) - 2022
- [c19]Erik Jergéus, Leo Karlsson Oinonen, Emil Carlsson, Moa Johansson:
Towards Learning Abstractions via Reinforcement Learning. AIC 2022: 120-126 - [c18]Wolfgang Ahrendt, Dilian Gurov, Moa Johansson, Philipp Rümmer:
TriCo - Triple Co-piloting of Implementation, Specification and Tests. ISoLA (1) 2022: 174-187 - [i6]Erik Jergéus, Leo Karlsson Oinonen, Emil Carlsson, Moa Johansson:
Towards Learning Abstractions via Reinforcement Learning. CoRR abs/2212.13980 (2022) - 2021
- [c17]Moa Johansson, Nicholas Smallbone:
Conjectures, Tests and Proofs: An Overview of Theory Exploration. VPT@ETAPS 2021: 1-16 - 2020
- [c16]Sólrún Halla Einarsdóttir, Nicholas Smallbone, Moa Johansson:
Template-based Theory Exploration: Discovering Properties of Functional Programs by Testing. IFL 2020: 67-78
2010 – 2019
- 2019
- [c15]Moa Johansson:
Lemma Discovery for Induction - A Survey. CICM 2019: 125-139 - [c14]Moa Johansson, Marie Korneliusson, Nickey Lizbat Lawrence:
Identifying Cross Country Skiing Techniques Using Power Meters in Ski Poles. NAIS 2019: 52-57 - [e2]José Júlio Alferes, Moa Johansson:
Practical Aspects of Declarative Languages - 21th International Symposium, PADL 2019, Lisbon, Portugal, January 14-15, 2019, Proceedings. Lecture Notes in Computer Science 11372, Springer 2019, ISBN 978-3-030-05997-2 [contents] - [i5]Moa Johansson, Marie Korneliusson, Nickey Lizbat Lawrence:
Identifying cross country skiing techniques using power meters in ski poles. CoRR abs/1904.10359 (2019) - 2018
- [c13]Sólrún Halla Einarsdóttir, Moa Johansson, Johannes Åman Pohjola:
Into the Infinite - Theory Exploration for Coinduction. AISC 2018: 70-86 - [i4]Agrin Hilmkil, Oscar Ivarsson, Moa Johansson, Dan Kuylenstierna, Teun van Erp:
Towards Machine Learning on data from Professional Cyclists. CoRR abs/1808.00198 (2018) - [i3]Andreas Arvidsson, Moa Johansson, Robin Touche:
Proving Type Class Laws for Haskell. CoRR abs/1808.05789 (2018) - 2017
- [j6]Nicholas Smallbone, Moa Johansson, Koen Claessen, Maximilian Algehed:
Quick specifications for the busy programmer. J. Funct. Program. 27: e18 (2017) - [c12]Maximilian Algehed, Koen Claessen, Moa Johansson, Nicholas Smallbone:
QuickSpec: a lightweight theory exploration tool for programmers (system demonstration). Haskell 2017: 38-39 - [c11]Moa Johansson:
Automated Theory Exploration for Interactive Theorem Proving: - An Introduction to the Hipster System. ITP 2017: 1-11 - 2016
- [c10]Andreas Arvidsson, Moa Johansson, Robin Touche:
Proving Type Class Laws for Haskell. TFP 2016: 61-74 - [e1]Michael Kohlhase, Moa Johansson, Bruce R. Miller, Leonardo de Moura, Frank Wm. Tompa:
Intelligent Computer Mathematics - 9th International Conference, CICM 2016, Bialystok, Poland, July 25-29, 2016, Proceedings. Lecture Notes in Computer Science 9791, Springer 2016, ISBN 978-3-319-42546-7 [contents] - 2015
- [j5]Irene Lobo Valbuena, Moa Johansson:
Conditional Lemma Discovery and Recursion Induction in Hipster. Electron. Commun. Eur. Assoc. Softw. Sci. Technol. 72 (2015) - [j4]Alan Bundy, Flaminia Cavallo, Lucas Dixon, Moa Johansson, Roy L. McCasland:
The Theory behind Theory Mine. IEEE Intell. Syst. 30(4): 64-69 (2015) - [j3]Maria Paola Bonacina, Moa Johansson:
On Interpolation in Automated Theorem Proving. J. Autom. Reason. 54(1): 69-97 (2015) - [j2]Maria Paola Bonacina, Moa Johansson:
Interpolation Systems for Ground Proofs in Automated Deduction: a Survey. J. Autom. Reason. 54(4): 353-390 (2015) - [c9]Koen Claessen, Moa Johansson, Dan Rosén, Nicholas Smallbone:
TIP: Tons of Inductive Problems. CICM 2015: 333-337 - 2014
- [c8]Moa Johansson, Dan Rosén, Nicholas Smallbone, Koen Claessen:
Hipster: Integrating Theory Exploration in a Proof Assistant. CICM 2014: 108-122 - [i2]Moa Johansson, Dan Rosén, Nicholas Smallbone, Koen Claessen:
Hipster: Integrating Theory Exploration in a Proof Assistant. CoRR abs/1405.3426 (2014) - 2013
- [c7]Koen Claessen, Moa Johansson, Dan Rosén, Nicholas Smallbone:
Automating Inductive Proofs Using Theory Exploration. CADE 2013: 392-406 - [c6]Jónathan Heras, Ekaterina Komendantskaya, Moa Johansson, Ewen Maclean:
Proof-Pattern Recognition and Lemma Discovery in ACL2. LPAR 2013: 389-406 - [i1]Jónathan Heras, Ekaterina Komendantskaya, Moa Johansson, Ewen Maclean:
Proof-Pattern Recognition in ACL2. CoRR abs/1308.1780 (2013) - 2012
- [c5]Koen Claessen, Moa Johansson, Dan Rosén, Nicholas Smallbone:
HipSpec: Automating Inductive Proofs of Program Properties. ATx/WInG@IJCAR 2012: 16-25 - 2011
- [j1]Moa Johansson, Lucas Dixon, Alan Bundy:
Conjecture Synthesis for Inductive Theories. J. Autom. Reason. 47(3): 251-289 (2011) - [c4]Maria Paola Bonacina, Moa Johansson:
On Interpolation in Decision Procedures. TABLEAUX 2011: 1-16 - 2010
- [c3]Moa Johansson, Lucas Dixon, Alan Bundy:
Dynamic Rippling, Middle-Out Reasoning and Lemma Discovery. Verification, Induction, Termination Analysis 2010: 102-116 - [c2]Moa Johansson, Lucas Dixon, Alan Bundy:
Case-Analysis for Rippling and Inductive Proof. ITP 2010: 291-306
2000 – 2009
- 2006
- [c1]Moa Johansson, Alan Bundy, Lucas Dixon:
Best-First Rippling. Reasoning, Action and Interaction in AI Theories and Systems 2006: 83-100
Coauthor Index
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last updated on 2025-11-08 01:11 CET by the dblp team
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