{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/gelu-impl","entry":"gelu_impl","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":5,"n_papers_ran":4,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":2,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":1},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2411.04168","paper":"/paper/dimsum-diffusion-mamba-a-scalable-and-unified","title":"DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation","date":"2024-11-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"vinairesearch/dimsum","path":"dimsum/bias_gelu.py","file_url":"https://github.com/vinairesearch/dimsum/blob/HEAD/dimsum/bias_gelu.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"8184d7cda6c94d2f","mcp_get_code":{"code_sha256":"8184d7cda6c94d2f"}},{"arxiv_id":"2310.18339","paper":"/paper/moelora-an-moe-based-parameter-efficient-fine","title":"When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications","date":"2023-10-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"applied-machine-learning-lab/moelora-peft","path":"resources/modeling_chatglm.py","file_url":"https://github.com/applied-machine-learning-lab/moelora-peft/blob/HEAD/resources/modeling_chatglm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c8f235d13277facd","mcp_get_code":{"code_sha256":"c8f235d13277facd"}},{"arxiv_id":"2307.13528","paper":"/paper/factool-factuality-detection-in-generative-ai","title":"FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios","date":"2023-07-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"freedomintelligence/sdak","path":"code/src/modeling_chatglm_med.py","file_url":"https://github.com/freedomintelligence/sdak/blob/HEAD/code/src/modeling_chatglm_med.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"c8f235d13277facd","mcp_get_code":{"code_sha256":"c8f235d13277facd"}},{"arxiv_id":"2210.02414","paper":"/paper/glm-130b-an-open-bilingual-pre-trained-model","title":"GLM-130B: An Open Bilingual Pre-trained Model","date":"2022-10-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jackaduma/ChatGLM-LoRA-RLHF-PyTorch","path":"models/modeling_chatglm.py","file_url":"https://github.com/jackaduma/ChatGLM-LoRA-RLHF-PyTorch/blob/HEAD/models/modeling_chatglm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c8f235d13277facd","mcp_get_code":{"code_sha256":"c8f235d13277facd"}},{"arxiv_id":"2025.findings-acl.583","paper":null,"title":"arXiv:2025.findings-acl.583","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"CSHaitao/LexiLaw","path":"src/modeling_chatglm.py","file_url":"https://github.com/CSHaitao/LexiLaw/blob/HEAD/src/modeling_chatglm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c8f235d13277facd","mcp_get_code":{"code_sha256":"c8f235d13277facd"}}]}