Programming
Software development: programming languages, coding, libraries and frameworks, software engineering and architecture, source control, developer tools, databases, and infrastructure.
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Communicating Natural Programs to Humans and Machines proceedings.neurips.cc
NeurIPS'22, 2022. [All Versions]. While humans readily generate and interpret instructions in a general language, computer systems are shackled to a narrow domain-specific language that they can precisely execute. This makes building intelligent systems that can generalize to…
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A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation proceedings.neurips.cc
NeurIPS'19, 2019. [All Versions].
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Practical Bayesian Optimization of Machine Learning Algorithms proceedings.neurips.cc
NeurIPS'12, 2012. [All Versions]. The use of machine learning algorithms frequently involves careful tuning of learning parameters and model hyperparameters. Unfortunately, this tuning is often a “black art” requiring expert experience, rules of thumb, or sometimes brute-force…
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Testing a Bayesian Measure of Representativeness Using a Large Image Database proceedings.neurips.cc
NeurIPS'11, 2011. [All Versions].
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PAL: Program-aided Language Models proceedings.mlr.press
ICML'23, 2023. [All Versions]. Paper presenting an approach that uses the LLM to read natural language problems and generate programs as the intermediate reasoning steps, but offloads the solution step to a runtime such as a Python interpreter. With PAL, decomposing the natural…
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A Language for Counterfactual Generative Models proceedings.mlr.press
ICML'21, 2021. [All Versions]. [Project]. This paper presents Omega, a probabilistic programming language with support for counterfactual inference. This feature is accomplished by introducing a new operator to probabilistic programming akin to Pearl’s do.
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PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming proceedings.mlr.press
ICML'21, 2021. [All Versions]. This work presents PClean, a probabilistic programming language (PPL) for leveraging dataset-specific knowledge to automate Bayesian cleaning, automating Bayesian approaches given the diversity of real-world error patterns and the hardness of…
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Kinematic mental simulations in abduction and deduction pnas.org
Proceedings of the National Academy of Sciences, 2013. [All Versions]. This paper presents a theory, and its computer implementation, of how mental simulations underlie the abductions of informal algorithms and deductions from these algorithms. Three experiments tested the…
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HLSMAC: A New StarCraft Multi-Agent Challenge for High-Level Strategic Decision-Making openreview.net
AAMAS'26, 2026. [All Versions]. Benchmarks are crucial for assessing multi-agent reinforcement learning (MARL) algorithms. While StarCraft II-related environments have driven significant advances in MARL, existing benchmarks like SMAC focus primarily on micromanagement…
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Visual Programming: Compositional Visual Reasoning Without Training openaccess.thecvf.com
CVPR'23, 2023. [All Versions]. VISPROG, a neuro-symbolic approach to solving complex and compositional visual tasks given natural language instructions, using the in-context learning ability of large language models to generate python-like modular programs, which are then…
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Universal chemical programming language for robotic synthesis repeatability nature.com
Nature Synthesis, 2024. [All Versions]. [Preprint]. The amount of chemical synthesis literature is growing quickly; however, it takes a long time to share and evaluate new processes among laboratories. This paper presents an approach that uses a universal chemical programming…
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Meta-analysis of the functional neuroimaging literature with probabilistic logic programming nature.com
Scientific Reports, 2022. [All Versions]. Inferring reliable brain-behavior associations requires synthesizing evidence from thousands of functional neuroimaging studies through meta-analysis. However, existing meta-analysis tools are limited to investigating simple…
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Scientific Data, 2020. [All Versions]. [Project]. Advances in computer-assisted linguistic research have been greatly influential in reshaping linguistic research. With the increasing availability of interconnected datasets created and curated by researchers, more and more…
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Algorithm for optimized mRNA design improves stability and immunogenicity nature.com
Nature, 2023. [All Versions]. Messenger RNA (mRNA) vaccines are being used to combat the spread of COVID-19, but they still exhibit critical limitations caused by mRNA instability and degradation, which are major obstacles for the storage, distribution and efficacy of the…
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Human–machine collaboration for improving semiconductor process development nature.com
Nature, 2023. [All Versions]. [Nature News]. This work studies Bayesian optimization algorithms to investigate how artificial intelligence (AI) might decrease the cost of developing complex semiconductor chip processes. In particular, this work create a controlled virtual…
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An autonomous portable platform for universal chemical synthesis nature.com
Nature Chemistry, 2022. [All Versions]. [Preprint]. This paper presents a portable suitcase-sized chemical synthesis platform containing all the modules required for synthesis and purification. The system uses a chemical programming language coupled to a digital reactor…
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A human-machine interface for automatic exploration of chemical reaction networks nature.com
Nature Communications, 2024. [All Versions]. Autonomous reaction network exploration algorithms offer a systematic approach to explore mechanisms of complex chemical processes. However, the resulting reaction networks are so vast that an exploration of all potentially…
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Program Synthesis microsoft.com
Foundations and Trends in Programming Languages, 2017. [All Versions]. Sumit Gulwani's comprehensive review on program synthesis.
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What is Answer Set Programming? link.springer.com
Springer, 2008. [All Versions]. [Tutorial on AAAI]. Answer set programming (ASP) is a form of declarative programming oriented towards difficult search problems. As an outgrowth of research on the use of nonmonotonic reasoning in knowledge representation, it is particularly…
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Domain-Specific Modeling Languages: Requirements Analysis and Design Guidelines link.springer.com
Domain Engineering: Product Lines, Languages, and Conceptual Models, 2013. [All Versions]. In recent years, the development of domain-specific modeling languages has gained remarkable attention. This is for good reasons. A domain-specific modeling language incorporates concepts…
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LegalLanguage: A Domain-Specific Language for Legal Contexts link.springer.com
EEWC'19, 2019. [All Versions]. Nowadays legal ontologies have been used in the legal domain, however, being poorly explored in legislative and production processes. This paper analyses the adoption of legal ontologies as a tool to support these processes, in particular, related…
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Answer Set Programming link.springer.com
ICLPNR'99, 1999. [All Versions]. [Preprint]. The original paper on Answer Set Programming (ASP), a form of declarative programming oriented towards difficult search problems, on the use of nonmonotonic reasoning in knowledge representation. In ASP solutions to a problem are…
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Abduction in Logic Programming link.springer.com
Computational Logic, 2002. [All Versions]. [Preprint]. Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer…
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Action Languages, Answer Sets, and Planning link.springer.com
The Logic Programming Paradigms, 1999. [All Versions]. [Preprint]. This is a discussion of some of the achievements and challenges related to representing actions and the design of planners from the perspective of logic programming. The authors talk about recent work on action…
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Towards combining inductive logic programming with Bayesian networks link.springer.com
ILP'01, 2001. [All Versions].
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Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework link.springer.com
Machine Learning, 2022. [All Versions]. A neuro-symbolic framework that integrates meta-policy learning in inductive logic programming.
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Analysis of Langevin Monte Carlo via Convex Optimization jmlr.org
Journal of Machine Learning Research, 2019. [All Versions]. This paper provides new insights on the Unadjusted Langevin Algorithm. The authors show that this method can be formulated as the first order optimization algorithm for an objective functional defined on the…
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Biocoder: A programming language for standardizing and automating biology protocols jbioleng.biomedcentral.com
Journal of Biological Engineering, 2010. [All Versions]. [Project]. [Microsoft Page] This paper introduces BioCoder, a C++ library that enables biologists to express the exact steps needed to execute a protocol. In addition to being suitable for automation, BioCoder converts…
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Learning Explanatory Rules from Noisy Data jair.org
Journal of Artificial Intelligence Research, 2018. [All Versions]. The original paper for differential Inductive Logic Programming.
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Turning 30: New Ideas in Inductive Logic Programming ijcai.org
IJCAI'20, 2020. [All Versions].
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Neural Task Programming: Learning to Generalize Across Hierarchical Tasks ieeexplore.ieee.org
ICRA'18, 2018. [All Versions].
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Visual Concept Programming: A Visual Analytics Approach to Injecting Human Intelligence at Scale ieeexplore.ieee.org
IEEE Transactions on Visualization and Computer Graphics, 2023. [All Versions]. This paper presents Visual Concept Programming, a first-of-its-kind visual analytics approach of using visual concepts to program image data at scale while requiring a few human efforts.
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Domain Specific Language for Smart Contract Development ieeexplore.ieee.org
ICBC'20, 2020. [All Versions]. [Preprint]. This research addresses the understanding hardness raised from the conceptual discrepancy between contractual clauses and corresponding code of the Solidity programming language, by the design and study of a domain-specific smart…
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Taking the Human Out of the Loop: A Review of Bayesian Optimization ieeexplore.ieee.org
Proceedings of the IEEE, 2015. [All Versions]. [Preprint]. Big Data applications are typically associated with systems involving large numbers of users, massive complex software systems, and large-scale heterogeneous computing and storage architectures. The construction of such…
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Usability Evaluation of Domain-Specific Languages ieeexplore.ieee.org
ICQICT'12, 2012. [All Versions]. [Preprint]. The purpose of this proposal is to contribute to the systematic activity of Software Language Engineering by focusing on the issue of the Usability evaluation of DSLs. Usability evaluation is often skipped, relaxed, or at least…
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Product Line Engineering Using Domain-Specific Languages ieeexplore.ieee.org
ISPLC'11, 2011. [All Versions]. [Preprint]. This paper investigates the application of domain-specific languages in product line engineering (PLE). It starts by analyzing the limits of expressivity of feature models. Feature models correspond to context-free grammars without…
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LogSay: An Efficient Comprehension System for Log Numerical Reasoning ieeexplore.ieee.org
IEEE Transactions on Computers, 2024. [All Versions]. With the growth of smart systems and applications, high volume logs are generated that record important data for system maintenance. System developers are usually required to analyze logs to track the status of the system or…
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Comparison of multi-paradigm programming languages en.wikipedia.org
Wikipedia. Programming languages may support multiple programming paradigms. This Wikipedia encyclopedia entry lists a concise reference for the programming paradigms.
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Robotic search for optimal cell culture in regenerative medicine elifesciences.org
eLife, 2022. [All Versions]. This paper develops a robotic AI system with a batch Bayesian optimization algorithm that autonomously induces the differentiation of induced pluripotent stem cell-derived retinal pigment epithelial (iPSC-RPE) cells. From 200 million possible…
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Epigrams on programming dl.acm.org
ACM SIGPLAN Notices, 1982. [All Versions].
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On the Effectiveness of Large Language Models in Domain-Specific Code Generation dl.acm.org
ACM Transactions on Software Engineering and Methodology, 2025. [All Versions]. Large language models (LLMs) such as ChatGPT have shown remarkable capabilities in code generation. Despite significant achievements, they rely on enormous training data to acquire a broad spectrum…
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ACM Transactions on Software Engineering and Methodology, 2024. [All Versions]. Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents to software engineering researchers the six key challenges that a domain…
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"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output dl.acm.org
CHI EA'24, 2024. [All Versions]. [Preprint]. Large language models can produce creative and diverse responses. However, to integrate them into current developer workflows, it is essential to constrain their outputs to follow specific formats or standards. This work surveyed 51…
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CoLadder: Manipulating Code Generation via Multi-Level Blocks dl.acm.org
UIST'24, 2024. [All Versions]. This paper adopted an iterative design process to gain insights into programmers’ strategies when using LLMs for programming. The authors proposed CoLadder, a novel system that supports programmers by facilitating hierarchical task decomposition…
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How Domain Experts Use an Embedded DSL dl.acm.org
OOPSLA'23, 2023. [All Versions]. Programming tools are increasingly integral to research and analysis in myriad domains, including specialized areas with no formal relation to computer science. Embedded domain-specific languages (eDSLs) have the potential to serve these…
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GarmentCode: Programming Parametric Sewing Patterns dl.acm.org
ACM Transactions on Graphics, 2023. [All Versions]. Garment modeling is an essential task of the global apparel industry and a core part of digital human modeling. Realistic representation of garments with valid sewing patterns is key to their accurate digital simulation and…
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A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges dl.acm.org
ICSE'24, 2024. [All Versions]. A survey finding that developers are most motivated to use AI programming assistants because they help developers reduce key-strokes, finish programming tasks quickly, and recall syntax, but resonate less with using them to help brainstorm…
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Combining Functional and Automata Synthesis to Discover Causal Reactive Programs dl.acm.org
POPL'23, 2023. [All Versions]. A new algorithm that synthesizes functional reactive programs from observation data, which iterates between a functional synthesis step, which attempts to generate a transition function over observed states, and an automata synthesis step, which…
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Top-Down Synthesis for Library Learning dl.acm.org
POPL'23, 2023. [All Versions]. This paper introduces corpus-guided top-down synthesis as a mechanism for synthesizing library functions that capture common functionality from a corpus of programs in a domain specific language (DSL). The algorithm builds abstractions directly…
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babble: Learning Better Abstractions with E-Graphs and Anti-unification dl.acm.org
POPL'23, 2023. [All Versions]. This paper proposes library learning modulo theory (LLMT), a new library learning algorithm that additionally takes as input an equational theory for a given problem domain. LLMT uses e-graphs and equality saturation to compactly represent the…
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