Theory
1,949 items in 14 lists
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What is consciousness, and could machines have it? doi.org
Science, 2017. [All Versions]. A perspective on the two levels of consciousness in machine intelligence.
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OpenLaw docs.openlaw.io
OpenLaw.io. It is now possible to model all or parts of legal agreements using code (smart contracts), decreasing the cost and friction of creating, securing, and generating binding legal agreements. Lawyers lack basic tools to build these dynamic, “smart” contracts in a way…
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Human Performance on Insight Problem Solving: A Review docs.lib.purdue.edu
The Journal of Problem Solving, 2011. [All Versions].
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Meta-interpretive learning: application to grammatical inference doc.ic.ac.uk
Machine Learning, 2014. [All Versions]. Stephen Muggleton's original paper on Meta-Interpretive Learning (MIL).
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Epigrams on programming dl.acm.org
ACM SIGPLAN Notices, 1982. [All Versions].
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The Seven Tools of Causal Inference, with Reflections on Machine Learning dl.acm.org
Communications of the ACM, 2019. [All Versions]. Judea Pearl's review on causal inference in probabilistic graph models.
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Apprenticeship Learning via Inverse Reinforcement Learning dl.acm.org
ICML'04, 2004. [All Versions]. Pieter Abbeel and Andrew Ng's original paper on inverse reinforcement learning (IRL).
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Designing games with a purpose dl.acm.org
Communications of the ACM, 2008. [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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PhotoScout: Synthesis-Powered Multi-Modal Image Search dl.acm.org
ACM SIGCHI'24, 2024. [All Versions]. This paper explores a new multi-modal image search approach that allows users to conveniently specify and perform semantic image search tasks. With the tool, PhotoScout, the user interactively provides natural language descriptions, positive…
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Building an Open Representation for Biological Protocols dl.acm.org
ACM Journal on Emerging Technologies in Computing Systems, 2023. [All Versions]. Laboratory protocols are critical to biological research and development, yet difficult to communicate and reproduce across projects, investigators, and organizations. While many attempts have been…
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Automatic curriculum learning for deep RL: a short survey dl.acm.org
IJCAI'20, 2020. [All Versions].
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Finbert: A pre-trained financial language representation model for financial text mining dl.acm.org
IJCAI'20, 2020. [All Versions]. Predicting stock market trends, analyzing financial documents, and generating summaries of economic news articles, helping to disseminate financial knowledge.
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Infinite Hidden Relational Models dl.acm.org
UAI'06, 2006. [All Versions]. [Preprint]. Relational learning analyzes the probabilistic constraints between the attributes of entities and relationships. This work extends the expressiveness of relational models by introducing for each entity (or object) an…
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Nonparametric Bayesian Logic dl.acm.org
UAI'05, 2005. [All Versions]. [Preprint]. The Bayesian Logic (BLOG) language was recently developed for defining first-order probability models over worlds with unknown numbers of objects. It handles important problems in AI, including data association and population…
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Bayesian Abductive Logic Programs: A Probabilistic Logic for Abductive Reasoning dl.acm.org
IJCAI'11, 2011. [All Versions]. [Preprint]. This work introduces Bayesian Abductive Logic Programs (BALP), a probabilistic logic that adapts Bayesian Logic Programs (BLPs) for abductive reasoning. Like BLPs, BALPs also combine first-order logic and Bayes nets. However, unlike…
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What's the Game, then? Opportunities and Challenges for Runtime Behavior Generation dl.acm.org
UIST'24, 2024. [All Versions]. Procedural content generation (PCG), the process of algorithmically creating game components instead of manually, has been a common tool of game development for decades. Recent advances in large language models (LLMs) enable the generation of game…
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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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ACM SIGGRAPH Asia'23, 2023. [All Versions]. By continually observing their environment and communicating, AI agents trained in the Chinese dictionary and the Nüshu corpus collaborate towards creating a standard writing system to encode Chinese.
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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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ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives dl.acm.org
ACM Transactions on Graphics, 2023. [All Versions]. This work introduces ShapeCoder, the first system capable of taking a dataset of shapes, represented with unstructured primitives, and jointly discovering (i) useful abstraction functions and (ii) programs that use these…
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KnitScript: A Domain-Specific Scripting Language for Advanced Machine Knitting dl.acm.org
UIST'23, 2023. [All Versions]. [Project]. This paper presents KnitScript, a domain-specific machine knitting scripting language that supports computationally driven knitting designs. KnitScript provides a comprehensive virtual model of knitting machines, giving access to…
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A Computational Inflection for Scientific Discovery dl.acm.org
Communications of the ACM, 2023. [All Versions].
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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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Free2CAD: parsing freehand drawings into CAD commands dl.acm.org
ACM Transactions on Graphics, 2022. [All Versions]. CAD modeling, despite being the industry-standard, remains restricted to usage by skilled practitioners due to two key barriers. First, the user must be able to mentally parse a final shape into a valid sequence of supported…
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Domain-specific languages: an annotated bibliography dl.acm.org
ACM SIGPLAN Notices, 2000. [All Versions]. A survey on the topic of domain-specific languages as used for the construction and maintenance of software systems. The survey lists a selection of 75 key publications in the area, and provides a summary for each of the papers…
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PLIERS: A Process that Integrates User-Centered Methods into Programming Language Design dl.acm.org
ACM Transactions on Computer-Human Interaction, 2021. [All Versions]. Programming language design requires making many usability-related design decisions. However, existing HCI methods can be impractical to apply to programming languages: languages have high iteration costs…
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ShapeMOD: macro operation discovery for 3D shape programs dl.acm.org
ACM Transactions on Graphics, 2021. [All Versions]. A popular way to create detailed yet easily controllable 3D shapes is via procedural modeling, i.e. generating geometry using programs. Such programs consist of a series of instructions along with their associated parameter…
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RoboGrammar: graph grammar for terrain-optimized robot design dl.acm.org
ACM Transactions on Graphics, 2020. [All Versions]. This work presents RoboGrammar, a fully automated approach for generating optimized robot structures to traverse given terrains. This framework represents each robot design as a graph, and uses a graph grammar to express…
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ShapeAssembly: learning to generate programs for 3D shape structure synthesis dl.acm.org
ACM Transactions on Graphics, 2020. [All Versions]. Manually authoring 3D shapes is difficult and time consuming; generative models of 3D shapes offer compelling alternatives. Procedural representations are one such possibility: they offer high-quality and editable results but…
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Penrose: from mathematical notation to beautiful diagrams dl.acm.org
ACM Transactions on Graphics, 2020. [All Versions]. This work introduces a system called Penrose for creating mathematical diagrams. Its basic functionality is to translate abstract statements written in familiar math-like notation into one or more possible visual…
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Synthesis of Incremental Linear Algebra Programs dl.acm.org
ACM Transactions on Database Systems, 2020. [All Versions]. This article targets the Incremental View Maintenance (IVM) of sophisticated analytics (such as statistical models, machine learning programs, and graph algorithms) expressed as linear algebra programs. This work…
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InverseCSG: automatic conversion of 3D models to CSG trees dl.acm.org
ACM Transactions on Graphics, 2018. [All Versions]. While computer-aided design is a major part of many modern manufacturing pipelines, the design files typically generated describe raw geometry. Lost in this representation is the procedure by which these designs were…
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pix2code: Generating Code from a Graphical User Interface Screenshot dl.acm.org
ACM SIGCHI Symposium on Engineering Interactive Computing Systems, 2018. [All Versions]. [Code]. [Website]. This paper shows that deep learning methods can be leveraged to train a model end-to-end to automatically reverse engineer user interfaces and generate code from a single…
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Agent: automatic generation of experimental protocol runtime dl.acm.org
VRST'17, 2017. [All Versions]. This paper proposes the use of Domain-Specific Languages (DSLs) to ease the description and generation of VR experiments, thus letting experiment designers focus on their core tasks: designing, conducting, and reporting experiments.
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A Taxonomy of Domain-Specific Aspect Languages dl.acm.org
ACM Computing Surveys, 2015. [All Versions]. Domain-Specific Aspect Languages (DSALs) are Domain-Specific Languages (DSLs) designed to express crosscutting concerns. Compared to DSLs, their aspectual nature greatly amplifies the language design space. This survey structures…
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The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies dl.acm.org
Journal of the ACM, 2010. [All Versions].
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When and How to Develop Domain-Specific Languages dl.acm.org
ACM Computing Surveys, 2005. [All Versions]. [Preprint]. Domain-specific languages (DSLs) are languages tailored to a specific application domain. They offer substantial gains in expressiveness and ease of use compared with general-purpose programming languages in their domain…
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HCI Research as Problem-Solving dl.acm.org
ACM SIGCHI'16, 2016. [All Versions]. This essay contributes a meta-scientific account of human-computer interaction (HCI) research as problem-solving. We build on the philosophy of Larry Laudan, who develops problem and solution as the foundational concepts of science. We argue…
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Zoom In: An Introduction to Circuits distill.pub
Distill, 2020. [All Versions]. A perspective on treating neural networks as circuits.
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Science of Science ctbergstrom.com
Science, 2018. [All Versions]. A comprehensive large-scale review on the science of science.
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A Mathematical Theory of Communication cs.yale.edu
The Bell System Technical Journal, 1948. [All Versions]. Shannon's original paper on Information Theory.
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Commonsense reasoning and commonsense knowledge in artificial intelligence cs.wellesley.edu
Communications of the ACM, 2015. [All Versions]. Gary Marcus's review on commonsense knowledge in AI.
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Abductive Plan Recognition by Extending Bayesian Logic Programs cs.utexas.edu
ECML'11, 2011. [All Versions]. Plan recognition is the task of predicting an agent’s top-level plans based on its observed actions. It is an abductive reasoning task that involves inferring cause from effect. Most existing approaches to plan recognition use either first-order…
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