Home › Code › encode_with_prompt_completion_format

encode_with_prompt_completion_format

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

encode_with_prompt_completion_format appears in the code Syntology harvested for 25 papers, as 15 distinct code bodies found in 27 places (a place is one code body under one paper). At least one of them ran in 14 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 encode_with_prompt_completion_format 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 6 of the 15 distinct code bodies named encode_with_prompt_completion_format; 9 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
0ran · fixture could not drive it
3ran
9unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 15 of the 27 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

25 papers shown of 25, newest first; 27 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; 1 papers have no page here and are shown by arXiv id only. 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
Optimsyn: Influence-Guided Rubrics Optimization for Synthetic Data Generation added by Syntology 2026-04 (from id) FanZT6/OptimSyn/training/influence/get_training_dataset.py 7e98a164bbb50ba8 unverified no licence file found · pointer only
IG-Pruning: Input-Guided Block Pruning for Large Language Models added by Syntology 2025-11 (from id) ictnlp/IG-Pruning/cluster_samples.py 9675ac6bf324cb46 unverified no licence file found · pointer only
LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning 12 May 2025 HKUSTDial/LEAD/src/online/template.py 57148174b9cdbbea unverified MIT (permissive)
Compute-Constrained Data Selection 21 Oct 2024 oseyosey/CCDS/ccds/evaluation/open_instruct/finetune.py 5966cc3120c46d61 unverified Apache-2.0 (permissive)
Router-Tuning: A Simple and Effective Approach for Enabling Dynamic-Depth in Transformers 17 Oct 2024 case-lab-umd/router-tuning/entrypoints/finetune/finetune_router_tuning.py 88b8bf1223d522a4 ran · our draft was wrong no licence file found · pointer only
Learning Fine-Grained Grounded Citations for Attributed Large Language Models 8 Aug 2024 luckyyysta/fine-grained-attribution/training/stage1_grounding_guided_generation/finetune.py 46b021a3b51b711f unverified no licence file found · pointer only
Learning Fine-Grained Grounded Citations for Attributed Large Language Models 8 Aug 2024 luckyyysta/fine-grained-attribution/training/stage2_consistency_aware_alignment/dpo_tune.py d01f5d65c58ed96d unverified no licence file found · pointer only
Cutting Through the Noise: Boosting LLM Performance on Math Word Problems 30 May 2024 him1411/problemathic/scripts/finetune.py 119cad9954acc960 unverified MIT (permissive)
SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales 31 May 2024 xu1868/SaySelf/training/finetune.py 119cad9954acc960 unverified MIT (permissive)
Instruction Tuning With Loss Over Instructions 23 May 2024 zhengxiangshi/instructionmodelling/src/compute_loss.py c90f3a5ec6457c6d ran · our draft was wrong no licence file found · pointer only
Instruction Tuning With Loss Over Instructions 23 May 2024 ZhengxiangShi/InstructionModelling/src/finetune.py e7170ef85d1fec78 ran no licence file found · pointer only
ADELIE: Aligning Large Language Models on Information Extraction 8 May 2024 THU-KEG/ADELIE/train4llama/open_instruct/finetune.py 5966cc3120c46d61 unverified no licence file found · pointer only
MEIT: Multi-Modal Electrocardiogram Instruction Tuning on Large Language Models for Report Generation 7 Mar 2024 aiot-mlsys-lab/meit/ECG_LLMs/finetune_ecgllm_with_lora_mimic_without_IT.py 88b8bf1223d522a4 ran · our draft was wrong no licence file found · pointer only
Learning to Decode Collaboratively with Multiple Language Models 6 Mar 2024 clinicalml/co-llm/collm/training/qlora_finetuning.py 661419d69a095bfe ran no licence file found · pointer only
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning 23 Feb 2024 cyzhh/MMOS/train/finetune.py 1906977026be9a86 ran · our draft was wrong no licence file found · pointer only
SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection 26 Feb 2024 Blue-Raincoat/SelectIT/eval/open_instruct/finetune.py 119cad9954acc960 unverified no licence file found · pointer only
AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback 2 Feb 2024 JianGuanTHU/AMOR/code/finetune.py 99e4a58eb23854c4 ran no licence file found · pointer only
Scaling Sparse Fine-Tuning to Large Language Models 29 Jan 2024 ducdauge/sft-llm/finetune/finetune.py 88b8bf1223d522a4 ran · our draft was wrong MIT (permissive)
Airavata: Introducing Hindi Instruction-tuned LLM 26 Jan 2024 ai4bharat/indicinstruct/open_instruct/finetune.py 661419d69a095bfe ran Apache-2.0 (permissive)
Knowledge Verification to Nip Hallucination in the Bud 19 Jan 2024 fanqiwan/KCA/examination/utils.py 661419d69a095bfe ran Apache-2.0 (permissive)
Tuning Language Models by Proxy 16 Jan 2024 alisawuffles/proxy-tuning/open_instruct/finetune.py 88b8bf1223d522a4 ran · our draft was wrong no licence file found · pointer only
diff History for Neural Language Agents 12 Dec 2023 upiterbarg/diff_history/finetune.py 661419d69a095bfe ran MIT (permissive)
Agent Lumos: Unified and Modular Training for Open-Source Language Agents 9 Nov 2023 allenai/lumos/model/finetune.py 88b8bf1223d522a4 ran · our draft was wrong MIT (permissive)
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection 17 Oct 2023 AkariAsai/self-rag/retrieval_lm/finetune.py aac14d7de4178849 unverified MIT (permissive)
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving 29 Sep 2023 microsoft/ToRA/src/train/finetune.py 1906977026be9a86 ran · our draft was wrong MIT (permissive)
Cumulative Reasoning with Large Language Models 8 Aug 2023 iiis-ai/cumulative-reasoning/CR-Agent/train/finetune.py 1906977026be9a86 ran · our draft was wrong no licence file found · pointer only
arXiv:2024.findings-emnlp.575 shirley-wu/vdebugger/vdebugger/finetune.py aaf01f77204b6898 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