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Papers Program induction

“Program induction” 태그가 달린 논문 67편 · 필터 해제

LLM-Guided Probabilistic Program Induction for POMDP Model Estimation

2025-05-04 · Aidan Curtis, Hao Tang, Thiago Veloso, Kevin Ellis 외

Partially Observable Markov Decision Processes (POMDPs) model decision making under uncertainty. While there are many approaches to approximately solving POMDPs, we aim to address the problem of learning such models. In …

Decision MakingDecision Making Under UncertaintyProgram induction

Learning Object Placement Programs for Indoor Scene Synthesis with Iterative Self Training

2025-03-06 · Adrian Chang, Kai Wang, Yuanbo Li, Manolis Savva 외

Data driven and autoregressive indoor scene synthesis systems generate indoor scenes automatically by suggesting and then placing objects one at a time. Empirical observations show that current systems tend to produce in…

Indoor Scene SynthesisObjectProgram induction

Searching Latent Program Spaces

2024-11-13 · Clément Bonnet, Matthew V Macfarlane

Program synthesis methods aim to automatically generate programs restricted to a language that can explain a given specification of input-output pairs. While purely symbolic approaches suffer from a combinatorial search …

ARCProgram inductionProgram SynthesisTest-time Adaptation

Towards Efficient Neurally-Guided Program Induction for ARC-AGI

2024-11-13 · Simon Ouellette

ARC-AGI is an open-world problem domain in which the ability to generalize out-of-distribution is a crucial quality. Under the program induction paradigm, we present a series of experiments that reveal the efficiency and…

ARCProgram induction

Harmonizing Program Induction with Rate-Distortion Theory

2024-05-08 · Hanqi Zhou, David G. Nagy, Charley M. Wu

Many aspects of human learning have been proposed as a process of constructing mental programs: from acquiring symbolic number representations to intuitive theories about the world. In parallel, there is a long-tradition…

Program induction

LLM-SR: Scientific Equation Discovery via Programming with Large Language Models

2024-04-29 · Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani 외

Mathematical equations have been unreasonably effective in describing complex natural phenomena across various scientific disciplines. However, discovering such insightful equations from data presents significant challen…

Equation DiscoveryInterpretable Machine LearningLarge Language ModelProgram induction+3

Program-Based Strategy Induction for Reinforcement Learning

2024-02-26 · Carlos G. Correa, Thomas L. Griffiths, Nathaniel D. Daw

Typical models of learning assume incremental estimation of continuously-varying decision variables like expected rewards. However, this class of models fails to capture more idiosyncratic, discrete heuristics and strate…

Incremental LearningProgram inductionreinforcement-learningReinforcement Learning

Guided Sketch-Based Program Induction by Search Gradients

2024-02-10 · Ahmad Ayaz Amin

Many tasks can be easily solved using machine learning techniques. However, some tasks cannot readily be solved using statistical models, requiring a symbolic approach instead. Program induction is one of the ways that s…

Program induction

KB-Plugin: A Plug-and-play Framework for Large Language Models to Induce Programs over Low-resourced Knowledge Bases

2024-02-02 · Jiajie Zhang, Shulin Cao, Linmei Hu, Ling Feng 외

Program induction (PI) has become a promising paradigm for using knowledge bases (KBs) to help large language models (LLMs) answer complex knowledge-intensive questions. Nonetheless, PI typically relies on a large number…

Program inductionSelf-Supervised Learning

LLMs for Relational Reasoning: How Far are We?

2024-01-17 · Zhiming Li, Yushi Cao, Xiufeng Xu, Junzhe Jiang 외

Large language models (LLMs) have revolutionized many areas (e.g. natural language processing, software engineering, etc.) by achieving state-of-the-art performance on extensive downstream tasks. Aiming to achieve robust…

Common Sense ReasoningDecision MakingInductive logic programmingProgram induction+2

Modeling infant object perception as program induction

2023-08-28 · Jan-Philipp Fränken, Christopher G. Lucas, Neil R. Bramley, Steven T. Piantadosi

Infants expect physical objects to be rigid and persist through space and time and in spite of occlusion. Developmentists frequently attribute these expectations to a "core system" for object recognition. However, it is …

AttributeInductive LearningObjectObject Recognition+1

VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering

2023-07-06 · Zijun Yao, Yuanyong Chen, Xin Lv, Shulin Cao 외

We present Visual Knowledge oriented Programming platform (VisKoP), a knowledge base question answering (KBQA) system that integrates human into the loop to edit and debug the knowledge base (KB) queries. VisKoP not only…

Knowledge Base Question AnsweringProgram inductionQuestion Answeringslot-filling+1

Learning Differentiable Logic Programs for Abstract Visual Reasoning

2023-07-03 · Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting

Visual reasoning is essential for building intelligent agents that understand the world and perform problem-solving beyond perception. Differentiable forward reasoning has been developed to integrate reasoning with gradi…

Program inductionVisual Reasoning

Bayesian Program Learning by Decompiling Amortized Knowledge

2023-06-13 · Alessandro B. Palmarini, Christopher G. Lucas, N. Siddharth

DreamCoder is an inductive program synthesis system that, whilst solving problems, learns to simplify search in an iterative wake-sleep procedure. The cost of search is amortized by training a neural search policy, reduc…

Program inductionProgram Synthesis

Compositional diversity in visual concept learning

2023-05-30 · Yanli Zhou, Reuben Feinman, Brenden M. Lake

Humans leverage compositionality to efficiently learn new concepts, understanding how familiar parts can combine together to form novel objects. In contrast, popular computer vision models struggle to make the same types…

DiversityProgram induction

Neuro-symbolic Meta Reinforcement Learning for Trading

2023-01-15 · S I Harini, Gautam Shroff, Ashwin Srinivasan, Prayushi Faldu 외

We model short-duration (e.g. day) trading in financial markets as a sequential decision-making problem under uncertainty, with the added complication of continual concept-drift. We, therefore, employ meta reinforcement …

Decision MakingMeta Reinforcement LearningProgram inductionreinforcement-learning+3

Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines

2022-05-23 · Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh 외

Strong inductive biases give humans the ability to quickly learn to perform a variety of tasks. Although meta-learning is a method to endow neural networks with useful inductive biases, agents trained by meta-learning ma…

Meta-LearningMeta Reinforcement LearningProgram inductionReinforcement Learning (RL)

ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering

2022-04-17 · COLING 2022 10 · Yu Gu, Yu Su

Question answering on knowledge bases (KBQA) poses a unique challenge for semantic parsing research due to two intertwined challenges: large search space and ambiguities in schema linking. Conventional ranking-based KBQA…

Knowledge Base Question AnsweringProgram inductionQuestion AnsweringSemantic Parsing

Think Big, Teach Small: Do Language Models Distil Occam’s Razor?

2021-12-01 · NeurIPS 2021 12 · Gonzalo Jaimovitch-Lopez, David Castellano Falcón, Cesar Ferri, José Hernández-Orallo

Large language models have recently shown a remarkable ability for few-shot learning, including patterns of algorithmic nature. However, it is still an open question to determine what kind of patterns these models can ca…

Few-Shot LearningOpen-Ended Question AnsweringProgram induction

Program Transfer for Answering Complex Questions over Knowledge Bases

2021-11-16 · ACL ARR November 2021 11 · Anonymous

Program induction for answering complex questions over knowledge bases (KBs) aims to decompose a question into a multi-step program, whose execution against the KB produces the final answer. Learning to induce programs …

Program induction
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