{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:3ZVQKVZYWGOPGUADARAX4RSVJD","short_pith_number":"pith:3ZVQKVZY","schema_version":"1.0","canonical_sha256":"de6b055738b19cf3500304417e465548c8081b2a02d2e01fcb098e60df250c16","source":{"kind":"arxiv","id":"2404.14710","version":2},"attestation_state":"computed","paper":{"title":"Challenges of Using Pre-trained Models: the Practitioners' Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Fang Liu, Li Zhang, Ruohe Chen, Taichuan Li, Xin Tan","submitted_at":"2024-04-23T03:39:14Z","abstract_excerpt":"The challenges associated with using pre-trained models (PTMs) have not been specifically investigated, which hampers their effective utilization. To address this knowledge gap, we collected and analyzed a dataset of 5,896 PTM-related questions on Stack Overflow. We first analyze the popularity and difficulty trends of PTM-related questions. We find that PTM-related questions are becoming more and more popular over time. However, it is noteworthy that PTM-related questions not only have a lower response rate but also exhibit a longer response time compared to many well-researched topics in sof"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2404.14710","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2024-04-23T03:39:14Z","cross_cats_sorted":[],"title_canon_sha256":"40102c59c717fa7293900869b140bf8abcc6ef31a9e572a8ed74f84030ffdf5e","abstract_canon_sha256":"c653d24f06779fa87e3fa5dcb7c34c10ff72a350e87a8be98b4c85e5ffad16db"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:14:05.776933Z","signature_b64":"tWXvO9pixJAif+d0H07DozN656mG0G7OeOUy7uDZ1zsSz+vTIMba5d1tad9kasuQNYncz3bwHTE4P5aaQBd0BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"de6b055738b19cf3500304417e465548c8081b2a02d2e01fcb098e60df250c16","last_reissued_at":"2026-07-05T08:14:05.776522Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:14:05.776522Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Challenges of Using Pre-trained Models: the Practitioners' Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Fang Liu, Li Zhang, Ruohe Chen, Taichuan Li, Xin Tan","submitted_at":"2024-04-23T03:39:14Z","abstract_excerpt":"The challenges associated with using pre-trained models (PTMs) have not been specifically investigated, which hampers their effective utilization. To address this knowledge gap, we collected and analyzed a dataset of 5,896 PTM-related questions on Stack Overflow. We first analyze the popularity and difficulty trends of PTM-related questions. We find that PTM-related questions are becoming more and more popular over time. However, it is noteworthy that PTM-related questions not only have a lower response rate but also exhibit a longer response time compared to many well-researched topics in sof"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.14710","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2404.14710/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2404.14710","created_at":"2026-07-05T08:14:05.776578+00:00"},{"alias_kind":"arxiv_version","alias_value":"2404.14710v2","created_at":"2026-07-05T08:14:05.776578+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.14710","created_at":"2026-07-05T08:14:05.776578+00:00"},{"alias_kind":"pith_short_12","alias_value":"3ZVQKVZYWGOP","created_at":"2026-07-05T08:14:05.776578+00:00"},{"alias_kind":"pith_short_16","alias_value":"3ZVQKVZYWGOPGUAD","created_at":"2026-07-05T08:14:05.776578+00:00"},{"alias_kind":"pith_short_8","alias_value":"3ZVQKVZY","created_at":"2026-07-05T08:14:05.776578+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.14240","citing_title":"HuggingGraph: Understanding the Supply Chain of LLM Ecosystem","ref_index":50,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD","json":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD.json","graph_json":"https://pith.science/api/pith-number/3ZVQKVZYWGOPGUADARAX4RSVJD/graph.json","events_json":"https://pith.science/api/pith-number/3ZVQKVZYWGOPGUADARAX4RSVJD/events.json","paper":"https://pith.science/paper/3ZVQKVZY"},"agent_actions":{"view_html":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD","download_json":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD.json","view_paper":"https://pith.science/paper/3ZVQKVZY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2404.14710&json=true","fetch_graph":"https://pith.science/api/pith-number/3ZVQKVZYWGOPGUADARAX4RSVJD/graph.json","fetch_events":"https://pith.science/api/pith-number/3ZVQKVZYWGOPGUADARAX4RSVJD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD/action/storage_attestation","attest_author":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD/action/author_attestation","sign_citation":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD/action/citation_signature","submit_replication":"https://pith.science/pith/3ZVQKVZYWGOPGUADARAX4RSVJD/action/replication_record"}},"created_at":"2026-07-05T08:14:05.776578+00:00","updated_at":"2026-07-05T08:14:05.776578+00:00"}