Inductive logic programming

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

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Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 54 papers with code (153 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
  16 Aug 2019 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  The recent success of natural language understanding (NLU) systems has been troubled by results highlighting the failure of these models to generalize in a systematic and robust way.
• Inductive logic programming at 30: a new introduction
  18 Aug 2020 3 repositories listed
  Inductive logic programming (ILP) is a form of machine learning.
• Learning Explanatory Rules from Noisy Data
  13 Nov 2017 3 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Artificial Neural Networks are powerful function approximators capable of modelling solutions to a wide variety of problems, both supervised and unsupervised.
• Differentiable Inductive Logic Programming in High-Dimensional Space
  13 Aug 2022 2 repositories listed
  Synthesizing large logic programs through symbolic Inductive Logic Programming (ILP) typically requires intermediate definitions.
• Learning programs with magic values
  5 Aug 2022 2 repositories listed
  A magic value in a program is a constant symbol that is essential for the execution of the program but has no clear explanation for its choice.
• Incorporating Symbolic Domain Knowledge into Graph Neural Networks
  23 Oct 2020 2 repositories listed
  These kinds of problems have been addressed effectively in the past by Inductive Logic Programming (ILP), by virtue of 2 important characteristics: (a) The use of a representation language that easily captures the…
• Forgetting to learn logic programs
  15 Nov 2019 2 repositories listed
  To improve learning performance, we explore the idea of forgetting, where a learner can additionally remove programs from its BK.
• Learning higher-order logic programs
  25 Jul 2019 2 repositories listed
  Our theoretical results show that learning higher-order programs, rather than first-order programs, can reduce the textual complexity required to express programs which in turn reduces the size of the hypothesis space…
• Inductive general game playing
  23 Jun 2019 2 repositories listed
  This problem is central to inductive general game playing (IGGP).
• Neural Logic Machines
  26 Apr 2019 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  We propose the Neural Logic Machine (NLM), a neural-symbolic architecture for both inductive learning and logic reasoning.
• Inductive Learning of Robot Task Knowledge from Raw Data and Online Expert Feedback
  13 Jan 2025 1 repository listed
  In this paper, we propose an offline algorithm based on inductive logic programming from noisy examples to extract task specifications (i.
• Learning Rules Explaining Interactive Theorem Proving Tactic Prediction
  2 Nov 2024 1 repository listed
  Formally verifying the correctness of mathematical proofs is more accessible than ever, however, the learning curve remains steep for many of the state-of-the-art interactive theorem provers (ITP).
• Learning Robust Reward Machines from Noisy Labels
  27 Aug 2024 1 repository listed Syntology ran 3 of 4 samples · 1 unverified
  This paper presents PROB-IRM, an approach that learns robust reward machines (RMs) for reinforcement learning (RL) agents from noisy execution traces.
• Relational decomposition for program synthesis
  22 Aug 2024 1 repository listed Syntology ran 11 of 14 samples · 3 unverified · 14 pointer-only (licence)
  We introduce a novel approach to program synthesis that decomposes complex functional tasks into simpler relational synthesis sub-tasks.
• AutoCoder: Enhancing Code Large Language Model with \textsc{AIEV-Instruct}
  23 May 2024 1 repository listed
  We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo (April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test (90.
• Learning big logical rules by joining small rules
  29 Jan 2024 1 repository listed Syntology ran 13 of 17 samples · 4 unverified · 17 pointer-only (licence)
  A major challenge in inductive logic programming is learning big rules.
• Towards One-Shot Learning for Text Classification using Inductive Logic Programming
  30 Aug 2023 1 repository listed
  With the ever-increasing potential of AI to perform personalised tasks, it is becoming essential to develop new machine learning techniques which are data-efficient and do not require hundreds or thousands of training…
• Learning MDL logic programs from noisy data
  18 Aug 2023 1 repository listed Syntology ran 13 of 16 samples · 3 unverified · 16 pointer-only (licence)
  Many inductive logic programming approaches struggle to learn programs from noisy data.
• Learning logic programs by discovering higher-order abstractions
  16 Aug 2023 1 repository listed
  We introduce the higher-order refactoring problem, where the goal is to compress a logic program by discovering higher-order abstractions, such as map, filter, and fold.
• Learning Logic Specifications for Soft Policy Guidance in POMCP
  16 Mar 2023 1 repository listed
  In this paper, we use inductive logic programming to learn logic specifications from traces of POMCP executions, i.
• Generalisation Through Negation and Predicate Invention
  18 Jan 2023 1 repository listed
  The ability to generalise from a small number of examples is a fundamental challenge in machine learning.
• A Model for Intelligible Interaction Between Agents That Predict and Explain
  4 Jan 2023 1 repository listed
  Machine Learning (ML) has emerged as a powerful form of data modelling with widespread applicability beyond its roots in the design of autonomous agents.
• Relational program synthesis with numerical reasoning
  3 Oct 2022 1 repository listed
  Our approach can identify numerical values in linear arithmetic fragments, such as real difference logic, and from infinite domains, such as real numbers or integers.
• Temporal Inductive Logic Reasoning over Hypergraphs
  9 Jun 2022 1 repository listed
  Inductive logic reasoning is a fundamental task in graph analysis, which aims to generalize patterns from data.
• Composition of Relational Features with an Application to Explaining Black-Box Predictors
  1 Jun 2022 1 repository listed
  Using a notion of explanations based on the compositional structure of features in a CRM, we provide empirical evidence on synthetic data of the ability to identify appropriate explanations; and demonstrate the use of…
• Learning logic programs by combining programs
  1 Jun 2022 1 repository listed
  The goal of inductive logic programming is to induce a logic program (a set of logical rules) that generalises training examples.
• Explanatory machine learning for sequential human teaching
  20 May 2022 1 repository listed
  We propose a framework for the effects of sequential teaching on comprehension based on an existing definition of comprehensibility and provide evidence for support from data collected in human trials.
• Efficient lifting of symmetry breaking constraints for complex combinatorial problems
  14 May 2022 1 repository listed
  Many industrial applications require finding solutions to challenging combinatorial problems.
• Learning logic programs by discovering where not to search
  20 Feb 2022 1 repository listed
  We use the constraints to bootstrap a constraint-driven ILP system.
• Lifting Symmetry Breaking Constraints with Inductive Logic Programming
  22 Dec 2021 1 repository listed
  Efficient omission of symmetric solution candidates is essential for combinatorial problem-solving.

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.