{"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":"/paper/an-empirical-evaluation-of-temporal-graph","title":"An Empirical Evaluation of Temporal Graph Benchmark","arxiv_id":"2307.12510","date":"2023-07-24","proceeding":null,"authors":["Le Yu"],"abstract":"In this paper, we conduct an empirical evaluation of Temporal Graph Benchmark (TGB) by extending our Dynamic Graph Library (DyGLib) to TGB. Compared with TGB, we include eleven popular dynamic graph learning methods for more exhaustive comparisons. Through the experiments, we find that (1) different models depict varying performance across various datasets, which is in line with previous observations; (2) the performance of some baselines can be significantly improved over the reported results in TGB when using DyGLib. This work aims to ease the researchers' efforts in evaluating various dynamic graph learning methods on TGB and attempts to offer results that can be directly referenced in the follow-up research. All the used resources in this project are publicly available at https://github.com/yule-BUAA/DyGLib_TGB. This work is in progress, and feedback from the community is welcomed for improvements.","url_abs":"https://arxiv.org/abs/2307.12510v5","url_pdf":"https://arxiv.org/pdf/2307.12510v5.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"an-empirical-evaluation-of-temporal-graph","repo_url":"https://github.com/yule-BUAA/DyGLib_TGB","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"graph-learning","task_name":"Graph Learning"}],"methods":[{"method_slug":null,"method_name":"Library"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2307.12510","atlas_url":"https://app.syntology.ai/?focus=2307.12510","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.12510"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/yule-BUAA/DyGLib_TGB","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran":4},"by_repo_kind":{"official":{"samples":4,"ran":4,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"727d90514a9a5475","entry":"compute_src_dst_node_time_shifts","repo":"yule-BUAA/DyGLib_TGB","repo_kind":"official","path":"models/MemoryModel.py","file_url":"https://github.com/yule-BUAA/DyGLib_TGB/blob/HEAD/models/MemoryModel.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"727d90514a9a5475"}},{"code_sha256_prefix":"1de6e005e59cdf96","entry":"edge_bank_time_window_memory","repo":"yule-BUAA/DyGLib_TGB","repo_kind":"official","path":"models/EdgeBank.py","file_url":"https://github.com/yule-BUAA/DyGLib_TGB/blob/HEAD/models/EdgeBank.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1de6e005e59cdf96"}},{"code_sha256_prefix":"0f56e3ae8a152b2b","entry":"edge_bank_unlimited_memory","repo":"yule-BUAA/DyGLib_TGB","repo_kind":"official","path":"models/EdgeBank.py","file_url":"https://github.com/yule-BUAA/DyGLib_TGB/blob/HEAD/models/EdgeBank.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"0f56e3ae8a152b2b"}},{"code_sha256_prefix":"8bcef3dc22f0489a","entry":"predict_link_probabilities","repo":"yule-BUAA/DyGLib_TGB","repo_kind":"official","path":"models/EdgeBank.py","file_url":"https://github.com/yule-BUAA/DyGLib_TGB/blob/HEAD/models/EdgeBank.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"8bcef3dc22f0489a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}