{"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/torch-load","entry":"torch_load","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":9,"n_papers_ran":0,"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":7,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":9,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":7},"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":"2605.20803","paper":"/paper/arxiv-2605-20803","title":"Tunable MAGMAX: Preference-Aware Model Merging for Continual Learning","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"KeiHiroshima/tunable-magmax","path":"src/utils.py","file_url":"https://github.com/KeiHiroshima/tunable-magmax/blob/HEAD/src/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"79ae2d63ada03edb","mcp_get_code":{"code_sha256":"79ae2d63ada03edb"}},{"arxiv_id":"2605.05676","paper":"/paper/arxiv-2605-05676","title":"Decomposing the Basic Abilities of Large Language Models: Mitigating Cross-Task Interference in Multi-Task Instruct-Tuning","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"wangbing1416/BADIT","path":"peft/tuners/multitask_prompt_tuning/model.py","file_url":"https://github.com/wangbing1416/BADIT/blob/HEAD/peft/tuners/multitask_prompt_tuning/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"922d9b65d9f360e7","mcp_get_code":{"code_sha256":"922d9b65d9f360e7"}},{"arxiv_id":"2503.10809","paper":"/paper/attacking-multimodal-os-agents-with-malicious","title":"Attacking Multimodal OS Agents with Malicious Image Patches","date":"2025-03-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"AIchberger/mip-against-agent","path":"src/mip_attack/artifacts.py","file_url":"https://github.com/AIchberger/mip-against-agent/blob/HEAD/src/mip_attack/artifacts.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"4cf99e43d4302ec0","mcp_get_code":{"code_sha256":"4cf99e43d4302ec0"}},{"arxiv_id":"2410.03782","paper":"/paper/dawin-training-free-dynamic-weight","title":"DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation","date":"2024-10-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"naver-ai/dawin","path":"dawin_rft/main_dawin.py","file_url":"https://github.com/naver-ai/dawin/blob/HEAD/dawin_rft/main_dawin.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"2235e9caabb77a27","mcp_get_code":{"code_sha256":"2235e9caabb77a27"}},{"arxiv_id":"2308.12213","paper":"/paper/clipn-for-zero-shot-ood-detection-teaching","title":"CLIPN for Zero-Shot OOD Detection: Teaching CLIP to Say No","date":"2023-08-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xmed-lab/clipn","path":"src/classification.py","file_url":"https://github.com/xmed-lab/clipn/blob/HEAD/src/classification.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2235e9caabb77a27","mcp_get_code":{"code_sha256":"2235e9caabb77a27"}},{"arxiv_id":"2208.05592","paper":"/paper/patching-open-vocabulary-models-by","title":"Patching open-vocabulary models by interpolating weights","date":"2022-08-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mlfoundations/patching","path":"src/utils.py","file_url":"https://github.com/mlfoundations/patching/blob/HEAD/src/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2235e9caabb77a27","mcp_get_code":{"code_sha256":"2235e9caabb77a27"}},{"arxiv_id":"2009.13891","paper":"/paper/towards-effective-context-for-meta","title":"Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning","date":"2020-09-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"TJU-DRL-LAB/self-supervised-rl","path":"RL_with_Environment_Representation/PAnDR/pandr_utils.py","file_url":"https://github.com/TJU-DRL-LAB/self-supervised-rl/blob/HEAD/RL_with_Environment_Representation/PAnDR/pandr_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"f500cf83b3947999","mcp_get_code":{"code_sha256":"f500cf83b3947999"}},{"arxiv_id":"1901.08706","paper":"/paper/emergent-linguistic-phenomena-in-multi-agent","title":"Emergent Linguistic Phenomena in Multi-Agent Communication Games","date":"2019-01-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"lgraesser/MultimodalGame","path":"misc.py","file_url":"https://github.com/lgraesser/MultimodalGame/blob/HEAD/misc.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":"ceb3746f90391b0e","mcp_get_code":{"code_sha256":"ceb3746f90391b0e"}},{"arxiv_id":"aaai_27950","paper":null,"title":"arXiv:aaai_27950","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"gaojingsheng/LAMM","path":"utils.py","file_url":"https://github.com/gaojingsheng/LAMM/blob/HEAD/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b7f889f383d3efc8","mcp_get_code":{"code_sha256":"b7f889f383d3efc8"}}]}