Home › Code › get_target

get_target

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

get_target appears in the code Syntology harvested for 11 papers, as 11 distinct code bodies found in 11 places (a place is one code body under one paper). At least one of them ran in 4 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_target 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 4 of the 11 distinct code bodies named get_target; 7 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
4ran
7unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 5 of the 11 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

11 papers shown of 11, newest first; 11 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 2 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
Enhancing Scientific Named Entity Recognition via Large Language Models: A Type-driven Multi-task Learning Approach added by Syntology 2026-08 (from id) tongbao96/code-for-SciNER/Model/demonstrations.py 2d527e8ca5933776 ran no licence file found · pointer only
Toward Embodiment Equivariant Vision-Language-Action Policy added by Syntology 2025-09 (from id) hhcaz/e2vla/models/action_expert.py 5d00ada5abf1b6a0 unverified MIT (permissive)
Training Neural Samplers with Reverse Diffusive KL Divergence 16 Oct 2024 jiajunhe98/DiKL/DiKL/train_utils.py 3c1b0fd4fe0ce00b unverified MIT (permissive)
Is Your LLM Outdated? Evaluating LLMs at Temporal Generalization 14 May 2024 freedomintelligence/freshbench/GoodJudgeOpen_crawler/make_json_for_harness.py e6da4e59e0382a4e ran no licence file found · pointer only
Incorporating Gradients to Rules: Towards Lightweight, Adaptive Provenance-based Intrusion Detection 2024-04 (from id) lexuswang/captain/model/target_label.py 9cdd54cb086862b8 ran Apache-2.0 (permissive)
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models 18 Feb 2024 hyperwjf/logiccheckgpt/logiccheckgpt/check_llava.py 57b34d6519d9f181 unverified no licence file found · pointer only
Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise 10 Dec 2023 seabrapt/brain_underlying_structure_identification/walkthrough/helper_functions.py 4f9ebb664921611b ran no licence file found · pointer only
Not All Poisons are Created Equal: Robust Training against Data Poisoning 18 Oct 2022 yuyang0901/effective-poison-identification/dataset/cifar.py d65b4886674fe03e unverified MIT (permissive)
Neural Pose Transfer by Spatially Adaptive Instance Normalization 16 Mar 2020 jiashunwang/Neural-Pose-Transfer/utils.py 350649521efdd9e2 unverified Apache-2.0 (permissive)
Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards 13 Jun 2019 mizolotu/SmartExcavator/env_backend.py 506539b39f74a526 unverified MIT recorded; this copy not marked cleared · pointer only
An efficient framework for learning sentence representations 7 Mar 2018 google/embedding-tests/train_word_embedding_dp.py 83f35794b2541212 unverified Apache-2.0 (permissive)

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