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gen_prompt

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

gen_prompt appears in the code Syntology harvested for 35 papers, as 32 distinct code bodies found in 46 places (a place is one code body under one paper). At least one of them ran in 28 of the papers; 2 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 gen_prompt 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 21 of the 32 distinct code bodies named gen_prompt; 11 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
7ran · our draft was wrong
0ran · fixture could not drive it
14ran
11unverified
2fingerprinted

Licence is a property of each copy, so it is counted per place: 22 of the 46 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

35 papers shown of 35, newest first; 46 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 4 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
Ghosted Layers: Unconstrained Activation Alignment for Recovering Layer-Pruned LLMs added by Syntology 2026-05 (from id) chenxinrui-tsinghua/LinearPatch/eval/mmlu_eval.py 3383488ea82b6c15 ran MIT (permissive)
Psychological Steering of Large Language Models added by Syntology 2026-04 (from id) kaistAI/FLASK/gpt_review/gpt4_eval.py 71866adce400868a ran · our draft was wrong no licence file found · pointer only
Psychological Steering of Large Language Models added by Syntology 2026-04 (from id) kaistAI/FLASK/metadata_annotation/skillset/skillset_annotation.py 1c33539256f10e59 ran · our draft was wrong no licence file found · pointer only
Psychological Steering of Large Language Models added by Syntology 2026-04 (from id) kaistAI/FLASK/metadata_annotation/difficulty/difficulty_annotation.py d9f1b4538ee3c0dd unverified no licence file found · pointer only
Psychological Steering of Large Language Models added by Syntology 2026-04 (from id) kaistAI/FLASK/metadata_annotation/domain/domain_annotation.py ca86191a67ce7cdb unverified no licence file found · pointer only
SnapMLA: Efficient Long-Context MLA Decoding via Hardware-Aware FP8 Quantized Pipelining added by Syntology 2026-02 (from id) meituan-longcat/SGLang-FluentLLM/benchmark/mmlu/bench_sglang.py c7131fbea2cbdc2d unverified Apache-2.0 (permissive)
MRAG: Benchmarking Retrieval-Augmented Generation for Bio-medicine added by Syntology 2026-01 (from id) hendrycks/test/evaluate_flan.py 3383488ea82b6c15 ran MIT (permissive)
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment 28 Oct 2024 AboveParadise/LLMCBench/evaluate_mmlu.py 3383488ea82b6c15 ran MIT (permissive)
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment 28 Oct 2024 AboveParadise/LLMCBench/evaluate_advglue.py 00e220ac67451517 unverified MIT (permissive)
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment 28 Oct 2024 AboveParadise/LLMCBench/evaluate_mnli.py b8a3329c6d548881 unverified MIT (permissive)
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment 28 Oct 2024 AboveParadise/LLMCBench/evaluate_qnli.py 65cc2c5bebc786da unverified MIT (permissive)
HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling 19 Sep 2024 bytedance/hllm/code/HLLM_Creator_eval_scripts/gpt_eval_open.py a7f4c057cdcda01d unverified Apache-2.0 (permissive)
Great Memory, Shallow Reasoning: Limits of $k$NN-LMs 21 Aug 2024 gsyfate/knnlm-limits/eval_bbh.py d42ce8e145a19d21 ran no licence file found · pointer only
A deeper look at depth pruning of LLMs 23 Jul 2024 shoaibahmed/llm_depth_pruning/evals/mmlu.py 3383488ea82b6c15 ran no licence file found · pointer only
Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning 12 Jun 2024 jaehyun513/octree/ours/utils_xg.py 2d9f70d8150b77f3 ran · our draft was wrong fingerprinted no licence file found · pointer only
Why Don't Prompt-Based Fairness Metrics Correlate? 9 Jun 2024 chandar-lab/CAIRO/model/generation.py 4f8c1cf6dee484a6 unverified MIT (permissive)
DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs 3 Jun 2024 Hsu1023/DuQuant/mmlu_eval.py 3383488ea82b6c15 ran MIT (permissive)
Multiple-Choice Questions are Efficient and Robust LLM Evaluators 20 May 2024 geralt-targaryen/mc-evaluation/dataset_mc.py df462d439e738510 ran MIT (permissive)
A safety realignment framework via subspace-oriented model fusion for large language models 15 May 2024 xinykou/safety_realignment/evaluate/safety_datasets.py 728c60994ca0f8f0 ran no licence file found · pointer only
Bridging the Gap between Different Vocabularies for LLM Ensemble 15 Apr 2024 xydaytoy/eva/ensemble/eva_multi.py 5b3d9ad8287c5ece ran · our draft was wrong no licence file found · pointer only
Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal 2 Mar 2024 DeepLearnXMU/SSR/mmlu_test/evaluate_flan.py 3383488ea82b6c15 ran Apache-2.0 (permissive)
Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal 2 Mar 2024 DeepLearnXMU/SSR/mmlu_test/evaluate_causal.py 37d029794d683c68 ran Apache-2.0 (permissive)
Learning or Self-aligning? Rethinking Instruction Fine-tuning 28 Feb 2024 renmengjie7/self-aligning/eval/my_benchmark_eval.py 400468b4ab8c64df ran no licence file found · pointer only
Learning or Self-aligning? Rethinking Instruction Fine-tuning 28 Feb 2024 renmengjie7/self-aligning/eval/my_domain_eval.py d46a3cff5e2c4b42 ran no licence file found · pointer only
Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic 19 Feb 2024 declare-lab/red-instruct/starling_training/inference.py f9a7ad6a646ae62e ran fingerprinted Apache-2.0 (permissive)
Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning 7 Feb 2024 tml-epfl/long-is-more-for-alignment/evaluation/evaluation_gpt4.py 36c101b773eb28ed ran · our draft was wrong no licence file found · pointer only
Fairness-Aware Structured Pruning in Transformers 24 Dec 2023 chandar-lab/fasp/model/generation.py e0a15e5b01ac0d34 unverified MIT (permissive)
Sparse is Enough in Fine-tuning Pre-trained Large Language Models 19 Dec 2023 song-wx/SIFT/exp/mmlu/eval_mmlu.py 3383488ea82b6c15 ran no licence file found · pointer only
Arabic Mini-ClimateGPT : A Climate Change and Sustainability Tailored Arabic LLM 14 Dec 2023 mbzuai-oryx/climategpt/fastchat/eval/eval_gpt_review.py a6a3ac30bf6e7bcf ran · our draft was wrong no licence file found · pointer only
SGLang: Efficient Execution of Structured Language Model Programs 12 Dec 2023 tginart/sglang/benchmark/mmlu/bench_sglang.py c7131fbea2cbdc2d unverified Apache-2.0 (permissive)
Generative Parameter-Efficient Fine-Tuning 1 Dec 2023 savadikarc/gift/language_modeling/math_code_instruct/eval_mmlu.py 04fd5045fce0c33a ran MIT (permissive)
Can Large Language Model Comprehend Ancient Chinese? A Preliminary Test on ACLUE 14 Oct 2023 isen-zhang/aclue/src/utils.py 9cbcb7e3d68900c3 ran MIT (permissive)
LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models 9 Oct 2023 FranxYao/chain-of-thought-hub/MMLU/run_mmlu_llama.py 3383488ea82b6c15 ran MIT (permissive)
Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations 2 Oct 2023 ys-zong/foolyourvllms/VLLMs_attack.py 271092220057d5e7 unverified no licence file found · pointer only
Extrapolating Large Language Models to Non-English by Aligning Languages 9 Aug 2023 NJUNLP/x-LLM/eval/mieval.eval.py b934977219a4b0ec ran Apache-2.0 (permissive)
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition 7 Aug 2023 universal-ner/universal-ner/src/train/fastchat/eval/eval_gpt_review.py a6a3ac30bf6e7bcf ran · our draft was wrong MIT (permissive)
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets 20 Jul 2023 kaistai/flask/gpt_review/gpt4_eval.py 71866adce400868a ran · our draft was wrong no licence file found · pointer only
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets 20 Jul 2023 kaistai/flask/metadata_annotation/skillset/skillset_annotation.py 1c33539256f10e59 ran · our draft was wrong no licence file found · pointer only
CA-LoRA: Adapting Existing LoRA for Compressed LLMs to Enable Efficient Multi-Tasking on Personal Devices 15 Jul 2023 thunlp/ca-lora/src/section-4.2.1/instruct-eval/bbh.py d4004fed05d494ec ran no licence file found · pointer only
CA-LoRA: Adapting Existing LoRA for Compressed LLMs to Enable Efficient Multi-Tasking on Personal Devices 15 Jul 2023 thunlp/ca-lora/src/section-4.2.1/instruct-eval/crass.py f85537d953a50f7a ran no licence file found · pointer only
CA-LoRA: Adapting Existing LoRA for Compressed LLMs to Enable Efficient Multi-Tasking on Personal Devices 15 Jul 2023 thunlp/ca-lora/src/section-4.2.1/instruct-eval/drop.py 20d15978d45a2320 ran no licence file found · pointer only
Large Language Models are not Fair Evaluators 29 May 2023 i-eval/faireval/FairEval.py f6629e230f783ee7 ran · our draft was wrong no licence file found · pointer only
Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning Performance 26 May 2023 franxyao/chain-of-thought-hub/MMLU/run_mmlu_llama.py 3383488ea82b6c15 ran MIT (permissive)
Lion: Adversarial Distillation of Proprietary Large Language Models 22 May 2023 yjiangcm/lion/src/chatgpt_referee.py 2d9884b05d0bfa25 unverified MIT (permissive)
Clinical Camel: An Open Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding 19 May 2023 bowang-lab/clinical-camel/evaluation/eval_gpt_review.py a6a3ac30bf6e7bcf ran · our draft was wrong AGPL-3.0 (copyleft) · pointer only
Measuring Massive Multitask Language Understanding 7 Sep 2020 ollmer/mmlu/evaluate_flan.py 3383488ea82b6c15 ran MIT (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".

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