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get_peft_state_non_lora_maybe_zero_3

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

get_peft_state_non_lora_maybe_zero_3 appears in the code Syntology harvested for 24 papers, as 4 distinct code bodies found in 24 places (a place is one code body under one paper). At least one of them ran in 0 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_peft_state_non_lora_maybe_zero_3 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 0 of the 4 distinct code bodies named get_peft_state_non_lora_maybe_zero_3; 4 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
0ran
4unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 14 of the 24 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

24 papers shown of 24, newest first; 24 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; 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
CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning added by Syntology 2026-05 (from id) YangLiu-Lewis/CP-MoE/llava/train/train_MOE.py 1c53657305b66e9f unverified MIT (permissive)
Reasoning Portability: Guiding Continual Learning for MLLMs in the RLVR Era added by Syntology 2026-05 (from id) lluosi/RDB-CL/ETrain/Train/Base_trainer.py 1c53657305b66e9f unverified no licence file found · pointer only
Evaluating the Diagnostic Classification Ability of Multimodal Large Language Models: Insights from the Osteoarthritis Initiative added by Syntology 2026-01 (from id) wanglihx/LLaVA-OA/train_weighted.py 1c53657305b66e9f unverified no licence file found · pointer only
COIDO: Efficient Data Selection for Visual Instruction Tuning via Coupled Importance-Diversity Optimization added by Syntology 2025-10 (from id) SuDIS-ZJU/CoIDO/coido_scorer/stage1.py 3474fd37c97a48d0 unverified AGPL-3.0 (copyleft) · pointer only
Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-tuning 14 Mar 2025 OPTML-Group/VLM-Safety-Unlearn/llava/train/train_unlearn.py 1c53657305b66e9f unverified MIT (permissive)
Re-Imagining Multimodal Instruction Tuning: A Representation View 2 Mar 2025 identical code first harvested elsewhere 1c53657305b66e9f unverified licence of this copy not recorded
Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key 16 Jan 2025 zhyang2226/opa-dpo/opadpo/opa_train.py 1c53657305b66e9f unverified MIT recorded; this copy not marked cleared · pointer only
Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving 29 Oct 2024 hustvl/senna/llava/senna/train_senna_llava_laion_pretrain.py 1c53657305b66e9f unverified Apache-2.0 (permissive)
Improve Vision Language Model Chain-of-thought Reasoning 21 Oct 2024 riflezhang/llava-hound-dpo/llava_hound_dpo/dpo_scripts/run_dpo.py 1c53657305b66e9f unverified no licence file found · pointer only
RAP: Retrieval-Augmented Personalization for Multimodal Large Language Models 17 Oct 2024 hoar012/rap-mllm/llava/train/rap_train.py 1c53657305b66e9f unverified no licence file found · pointer only
TRACE: Temporal Grounding Video LLM via Causal Event Modeling 8 Oct 2024 gyxxyg/trace/trace/train_mt.py 1c53657305b66e9f unverified Apache-2.0 (permissive)
UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation 21 Aug 2024 xiangyu-mm/UniFashion/src/blip_fine_tune_2.py b6d749eb9a3b3158 unverified no licence file found · pointer only
STLLaVA-Med: Self-Training Large Language and Vision Assistant for Medical Question-Answering 28 Jun 2024 heliossun/stllava-med/train_dpo.py 1c53657305b66e9f unverified MIT (permissive)
mDPO: Conditional Preference Optimization for Multimodal Large Language Models 17 Jun 2024 luka-group/mDPO/bunny/run_mdpo_bunny.py 1c53657305b66e9f unverified no licence file found · pointer only
ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO 17 Jun 2024 yonseivnl/vlm-rlaif/RLAIF/finetune_policy_init.py 1c53657305b66e9f unverified Apache-2.0 (permissive)
Vript: A Video Is Worth Thousands of Words 10 Jun 2024 mutonix/Vript/vriptor/train_hf.py 1c53657305b66e9f unverified no licence file found · pointer only
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis 31 May 2024 PhysGame/PhysGame/train_dpo.py 1c53657305b66e9f unverified Apache-2.0 (permissive)
VoCoT: Unleashing Visually Grounded Multi-Step Reasoning in Large Multi-Modal Models 27 May 2024 rupertluo/vocot/train_volcano.py 95fa5f303fe6207c unverified no licence file found · pointer only
Grounding Language Models for Visual Entity Recognition 28 Feb 2024 mrzilinxiao/autover/train_oven.py 1c53657305b66e9f unverified Apache-2.0 (permissive)
Your Vision-Language Model Itself Is a Strong Filter: Towards High-Quality Instruction Tuning with Data Selection 19 Feb 2024 rayruibochen/self-filter/self_filter/stage1.py 1c53657305b66e9f unverified AGPL-3.0 (copyleft) · pointer only
LLaVA-Phi: Efficient Multi-Modal Assistant with Small Language Model 4 Jan 2024 zhuyiche/llava-phi/llava_phi/train/convert_model2base_llava_phi.py 1c53657305b66e9f unverified no licence file found · pointer only
LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models 5 Dec 2023 ux-decoder/llava-grounding/llava/train/train_grounding_1st.py 1c53657305b66e9f unverified Apache-2.0 (permissive)
HallE-Control: Controlling Object Hallucination in Large Multimodal Models 3 Oct 2023 bronyayang/HallE_Switch/llava/train/train_switch.py 1c53657305b66e9f unverified no licence file found · pointer only
arXiv:Wang_SMoLoRA_Exploring_and_Defying_Dual_Catastrophic_Forgetting_in_Continual_Visual_ICCV_2025_paper Minato-Zackie/SMoLoRA/llava/train/train_SMoLoRA.py 1c53657305b66e9f 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".

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