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get_state

Syntologyentry name in harvested coderead from the graph 2026-09-24

get_state appears in the code Syntology harvested for 13 papers, as 11 distinct code bodies found in 13 places (a place is one code body under one paper). At least one of them ran in 7 of the papers; 0 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named get_state do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 5 of the 11 distinct code bodies named get_state; 6 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
3ran · our draft was wrong
1ran · fixture could not drive it
1ran
6unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 6 of the 13 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

13 papers shown of 13, newest first; 13 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 1 papers added by Syntology. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
DYNAACT: Large Language Model Reasoning with Dynamic Action Spaces added by Syntology 2025-11 (from id) zhaoxlpku/DynaAct/utils.py 5e1f27c865cc2cc2 unverified no licence file found · pointer only
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies 14 Apr 2024 bbartoldson/adversarial-robustness-limits/submit.py 4fc810a6b13b1408 ran · our draft was wrong MIT (permissive)
Open-World Lifelong Graph Learning 19 Oct 2023 bobowner/open-world-lgl/handle_meta_data.py d5ebd613cef4acf2 ran no licence file found · pointer only
Unified Adversarial Patch for Cross-modal Attacks in the Physical World 15 Jul 2023 aries-iai/cross-modal_patch_attack/spline_DE_attack.py aab637864c086647 unverified MIT (permissive)
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems 20 Feb 2023 shentao-yang/fantastic_reward_iclr2023/EstimateBehaviorPolicy.py 7f76b00aa1bb20bf unverified MIT (permissive)
Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges 28 May 2022 amazon-research/replay-based-recurrent-rl/code/misc/torch_utility.py a61f2ad7df535ba0 unverified Apache-2.0 (permissive)
Large Batch Experience Replay 4 Oct 2021 sureli/laber/MinAtar_experiments/agents/dqn_LABER.py acd5bcd47c0df9f6 ran · fixture could not drive it MIT (permissive)
MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments 7 Mar 2019 identical code first harvested elsewhere acd5bcd47c0df9f6 ran · fixture could not drive it licence of this copy not recorded
Provably Efficient Maximum Entropy Exploration 6 Dec 2018 abbyvansoest/maxent/ant/ant_soft_actor_critic.py 2b35e42973a59560 unverified MIT (permissive)
Relational Deep Reinforcement Learning 5 Jun 2018 nicoladainese96/RelationalDeepRL/Utils/train_agent.py 2840e9977435e9ff ran · our draft was wrong no licence file found · pointer only
Inferring and Executing Programs for Visual Reasoning 10 May 2017 facebookresearch/clevr-iep/scripts/train_model.py 13ab7b9cc80a2b9b ran · our draft was wrong licence not identified · pointer only
Deep Successor Reinforcement Learning 8 Jun 2016 Ardavans/DSR/dsr/doom.py 734ef573d15eb87b unverified MIT (permissive)
The Arcade Learning Environment: An Evaluation Platform for General Agents 19 Jul 2012 identical code first harvested elsewhere acd5bcd47c0df9f6 ran · fixture could not drive it licence of this copy not recorded

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections