{"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/support-or-refute-analyzing-the-stance-of","title":"Support or Refute: Analyzing the Stance of Evidence to Detect Out-of-Context Mis- and Disinformation","arxiv_id":"2311.01766","date":"2023-11-03","proceeding":null,"authors":["Xin Yuan","Jie Guo","Weidong Qiu","Zheng Huang","Shujun Li"],"abstract":"Mis- and disinformation online have become a major societal problem as major sources of online harms of different kinds. One common form of mis- and disinformation is out-of-context (OOC) information, where different pieces of information are falsely associated, e.g., a real image combined with a false textual caption or a misleading textual description. Although some past studies have attempted to defend against OOC mis- and disinformation through external evidence, they tend to disregard the role of different pieces of evidence with different stances. Motivated by the intuition that the stance of evidence represents a bias towards different detection results, we propose a stance extraction network (SEN) that can extract the stances of different pieces of multi-modal evidence in a unified framework. Moreover, we introduce a support-refutation score calculated based on the co-occurrence relations of named entities into the textual SEN. Extensive experiments on a public large-scale dataset demonstrated that our proposed method outperformed the state-of-the-art baselines, with the best model achieving a performance gain of 3.2% in accuracy.","url_abs":"https://arxiv.org/abs/2311.01766v4","url_pdf":"https://arxiv.org/pdf/2311.01766v4.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":"support-or-refute-analyzing-the-stance-of","repo_url":"https://github.com/yx3266/SEN","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2311.01766","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.01766"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+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/yx3266/SEN","reach":null}],"summary":{"ran":1,"unverified":2},"by_repo_kind":{"official":{"samples":3,"ran":1,"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":3,"samples":[{"code_sha256_prefix":"dedeca3008dd643c","entry":"LockedDropout","repo":"yx3266/SEN","repo_kind":"official","path":"training_and_evaluation/sent_emb/model.py","file_url":"https://github.com/yx3266/SEN/blob/HEAD/training_and_evaluation/sent_emb/model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"dedeca3008dd643c"}},{"code_sha256_prefix":"f3fa88ef8efde4be","entry":"ContextSEN","repo":"yx3266/SEN","repo_kind":"official","path":"training_and_evaluation/sent_emb/model.py","file_url":"https://github.com/yx3266/SEN/blob/HEAD/training_and_evaluation/sent_emb/model.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f3fa88ef8efde4be"}},{"code_sha256_prefix":"62d148258bdd054f","entry":"embedded_dropout","repo":"yx3266/SEN","repo_kind":"official","path":"training_and_evaluation/sent_emb/model.py","file_url":"https://github.com/yx3266/SEN/blob/HEAD/training_and_evaluation/sent_emb/model.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"62d148258bdd054f"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}