Logical Sequence

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

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Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (9 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.

• Why Not Use Your Textbook? Knowledge-Enhanced Procedure Planning of Instructional Videos
  5 Mar 2024 4 repositories listed Syntology ran 3 of 5 samples · 2 unverified · 5 pointer-only (licence)
  This knowledge, sourced from training procedure plans and structured as a directed weighted graph, equips the agent to better navigate the complexities of step sequencing and its potential variations.
• Scaling Language Models: Methods, Analysis & Insights from Training Gopher
  8 Dec 2021 3 repositories listed
  Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
• Training Compute-Optimal Large Language Models
  29 Mar 2022 2 repositories listed Syntology ran 8 of 11 samples · 3 unverified · 4 pointer-only (licence)
  We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget.
• Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles
  16 Sep 2024 1 repository listed Syntology ran 5 of 11 samples · 6 unverified
  We observe that Transformer models trained on this synthetic task can indeed learn to solve Sudokus (our model solves 94.
• Architecture and evolution of semantic networks in mathematics texts
  14 Aug 2019 1 repository listed
  Knowledge is a network of interconnected concepts.

Syntology lines on 3 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.