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convert_to_scalar

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

convert_to_scalar 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 3 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 convert_to_scalar 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 1 of the 4 distinct code bodies named convert_to_scalar; 3 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
1ran
3unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 5 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; 3 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
UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing added by Syntology 2026-04 (from id) Yunkaidang/UHR/with-SAM/longva/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
VidLaDA: Bidirectional Diffusion Large Language Models for Efficient Video Understanding added by Syntology 2026-01 (from id) ziHoHe/VidLaDA/train/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
Cross-Layer Injection for Deep Vision-Language Fusion added by Syntology 2026-01 (from id) codefuse-ai/CLI/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
Phi: Preference Hijacking in Multi-modal Large Language Models at Inference Time added by Syntology 2025-09 (from id) Yifan-Lan/Phi/trl/core.py c32b636f13ed9ee5 unverified MIT (permissive)
Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors 30 May 2025 LaVi-Lab/Video-3D-LLM/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
LaViDa: A Large Diffusion Language Model for Multimodal Understanding 22 May 2025 jacklishufan/lavida/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
Forgetting Transformer: Softmax Attention with a Forget Gate 3 Mar 2025 zhixuan-lin/forgetting-transformer/src/forgetting_transformer/logger.py df304bdd056129a1 unverified MIT (permissive)
Risk-Averse Finetuning of Large Language Models 12 Jan 2025 sapanachaudhary/ra-rlhf/trl/core.py 8483cffb5dea03d2 ran Apache-2.0 (permissive)
DriveMM: All-in-One Large Multimodal Model for Autonomous Driving 10 Dec 2024 zhijian11/DriveMM/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning 4 Dec 2024 lavi-lab/aim/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
DyCoke: Dynamic Compression of Tokens for Fast Video Large Language Models 22 Nov 2024 kd-tao/dycoke/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization 17 Nov 2024 APiaoG/SymDPO/trl/core.py c32b636f13ed9ee5 unverified no licence file found · pointer only
CCExpert: Advancing MLLM Capability in Remote Sensing Change Captioning with Difference-Aware Integration and a Foundational Dataset 18 Nov 2024 meize0729/ccexpert/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models 23 Oct 2024 liuziyu77/mia-dpo/LLaVA-Hound-DPO/llava_hound_dpo/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
Improve Vision Language Model Chain-of-thought Reasoning 21 Oct 2024 riflezhang/llava-hound-dpo/llava_hound_dpo/trl/core.py c32b636f13ed9ee5 unverified no licence file found · pointer only
Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement Learning 8 Oct 2024 Harry67Hu/CORY/trl/core.py c32b636f13ed9ee5 unverified MIT (permissive)
Suri: Multi-constraint Instruction Following for Long-form Text Generation 27 Jun 2024 chtmp223/suri/ft/lib/trl_mod/core.py c32b636f13ed9ee5 unverified no licence file found · pointer only
ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO 17 Jun 2024 snumprlab/SRT/trl/core.py c32b636f13ed9ee5 unverified no licence file found · pointer only
ALaRM: Align Language Models via Hierarchical Rewards Modeling 11 Mar 2024 halfrot/ALaRM/trl/trl/core.py 8483cffb5dea03d2 ran Apache-2.0 (permissive)
Model Editing by Standard Fine-Tuning 16 Feb 2024 au-revoir/model-editing-ft/trl/core.py 8483cffb5dea03d2 ran no licence file found · pointer only
Direct Preference Optimization: Your Language Model is Secretly a Reward Model 29 May 2023 padlex/trl/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
arXiv:aaai_26923 aivaslab/standoff/src/base_AEC.py a9248aada2a37da1 unverified Apache-2.0 (permissive)
arXiv:Zhong_AIM_Adaptive_Inference_of_Multi-Modal_LLMs_via_Token_Merging_and_ICCV_2025_paper LaVi-Lab/AIM/trl/core.py c32b636f13ed9ee5 unverified Apache-2.0 (permissive)
arXiv:2025.findings-acl.359 G-JWLee/TAMP/trl/core.py c32b636f13ed9ee5 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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