{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:5CMQ2UZFI37ANWETRFSWKGKAB2","short_pith_number":"pith:5CMQ2UZF","schema_version":"1.0","canonical_sha256":"e8990d532546fe06d89389656519400e8a9ab75c5752732ee0d10c3b3f8f0e81","source":{"kind":"arxiv","id":"2503.23121","version":1},"attestation_state":"computed","paper":{"title":"Efficient Explicit Joint-level Interaction Modeling with Mamba for Text-guided HOI Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guohong Huang, Ling-An Zeng, Shengbo Gu, Wei-Shi Zheng, Zexin Zheng","submitted_at":"2025-03-29T15:23:21Z","abstract_excerpt":"We propose a novel approach for generating text-guided human-object interactions (HOIs) that achieves explicit joint-level interaction modeling in a computationally efficient manner. Previous methods represent the entire human body as a single token, making it difficult to capture fine-grained joint-level interactions and resulting in unrealistic HOIs. However, treating each individual joint as a token would yield over twenty times more tokens, increasing computational overhead. To address these challenges, we introduce an Efficient Explicit Joint-level Interaction Model (EJIM). EJIM features "},"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":"2503.23121","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-29T15:23:21Z","cross_cats_sorted":[],"title_canon_sha256":"cbf40dffdc185bdcfee4d704e5236b904b1adbb996823f8acba6313be9c4849d","abstract_canon_sha256":"308dbaeebcd22ac810cdcb7a7a3ac312bce57853a4704cb65dd18a4d6b90a660"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:41:31.030187Z","signature_b64":"g8iq8JF6+zGFoykzVTXvqWn1gdYacHdK2fW//pMGc0rMO58GbGsv39kuVsELodlKoor43UMsZRmS7sDcBP1EDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e8990d532546fe06d89389656519400e8a9ab75c5752732ee0d10c3b3f8f0e81","last_reissued_at":"2026-07-05T10:41:31.029698Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:41:31.029698Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient Explicit Joint-level Interaction Modeling with Mamba for Text-guided HOI Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guohong Huang, Ling-An Zeng, Shengbo Gu, Wei-Shi Zheng, Zexin Zheng","submitted_at":"2025-03-29T15:23:21Z","abstract_excerpt":"We propose a novel approach for generating text-guided human-object interactions (HOIs) that achieves explicit joint-level interaction modeling in a computationally efficient manner. Previous methods represent the entire human body as a single token, making it difficult to capture fine-grained joint-level interactions and resulting in unrealistic HOIs. However, treating each individual joint as a token would yield over twenty times more tokens, increasing computational overhead. To address these challenges, we introduce an Efficient Explicit Joint-level Interaction Model (EJIM). EJIM features "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.23121","kind":"arxiv","version":1},"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/2503.23121/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":"2503.23121","created_at":"2026-07-05T10:41:31.029752+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.23121v1","created_at":"2026-07-05T10:41:31.029752+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.23121","created_at":"2026-07-05T10:41:31.029752+00:00"},{"alias_kind":"pith_short_12","alias_value":"5CMQ2UZFI37A","created_at":"2026-07-05T10:41:31.029752+00:00"},{"alias_kind":"pith_short_16","alias_value":"5CMQ2UZFI37ANWET","created_at":"2026-07-05T10:41:31.029752+00:00"},{"alias_kind":"pith_short_8","alias_value":"5CMQ2UZF","created_at":"2026-07-05T10:41:31.029752+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2","json":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2.json","graph_json":"https://pith.science/api/pith-number/5CMQ2UZFI37ANWETRFSWKGKAB2/graph.json","events_json":"https://pith.science/api/pith-number/5CMQ2UZFI37ANWETRFSWKGKAB2/events.json","paper":"https://pith.science/paper/5CMQ2UZF"},"agent_actions":{"view_html":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2","download_json":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2.json","view_paper":"https://pith.science/paper/5CMQ2UZF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.23121&json=true","fetch_graph":"https://pith.science/api/pith-number/5CMQ2UZFI37ANWETRFSWKGKAB2/graph.json","fetch_events":"https://pith.science/api/pith-number/5CMQ2UZFI37ANWETRFSWKGKAB2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2/action/storage_attestation","attest_author":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2/action/author_attestation","sign_citation":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2/action/citation_signature","submit_replication":"https://pith.science/pith/5CMQ2UZFI37ANWETRFSWKGKAB2/action/replication_record"}},"created_at":"2026-07-05T10:41:31.029752+00:00","updated_at":"2026-07-05T10:41:31.029752+00:00"}