{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:PV5ET5YFMMHC3FXUUXED3D2UY4","short_pith_number":"pith:PV5ET5YF","canonical_record":{"source":{"id":"2507.21619","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:18:22Z","cross_cats_sorted":[],"title_canon_sha256":"44501399bcd17cd053d97a41cae070cebecd90e94cc43ef306c1ced24f82a7a6","abstract_canon_sha256":"27741e03fc88931fe40b859ef858f442b94e5bab897f1fe042dac5b6a1b571b8"},"schema_version":"1.0"},"canonical_sha256":"7d7a49f705630e2d96f4a5c83d8f54c7025a90e6427a5d2ee649f792b3be24e2","source":{"kind":"arxiv","id":"2507.21619","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21619","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21619v1","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21619","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_12","alias_value":"PV5ET5YFMMHC","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_16","alias_value":"PV5ET5YFMMHC3FXU","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_8","alias_value":"PV5ET5YF","created_at":"2026-07-05T11:45:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:PV5ET5YFMMHC3FXUUXED3D2UY4","target":"record","payload":{"canonical_record":{"source":{"id":"2507.21619","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:18:22Z","cross_cats_sorted":[],"title_canon_sha256":"44501399bcd17cd053d97a41cae070cebecd90e94cc43ef306c1ced24f82a7a6","abstract_canon_sha256":"27741e03fc88931fe40b859ef858f442b94e5bab897f1fe042dac5b6a1b571b8"},"schema_version":"1.0"},"canonical_sha256":"7d7a49f705630e2d96f4a5c83d8f54c7025a90e6427a5d2ee649f792b3be24e2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:03.288877Z","signature_b64":"FOMC2qZzEtO2CMexpzMQXptc0YVwUkohbjUoIhj6dphqqn5tdyekjbGSM+tzz12LKVMBckXvhLmDrKzruzprAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7d7a49f705630e2d96f4a5c83d8f54c7025a90e6427a5d2ee649f792b3be24e2","last_reissued_at":"2026-07-05T11:45:03.288438Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:03.288438Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.21619","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:45:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P0t6Gfbh3MUvlGKNK0pHmXxfyMoaqwJVQo7355tag2w5dgfvQTj8/CCrFXeJ675GEgh5pcNrYy90P4JubknJCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:52:06.290293Z"},"content_sha256":"107d2ee05a1bd8b3e333fb631f971499d93bbae6a1e3bc04246b799391d53aa2","schema_version":"1.0","event_id":"sha256:107d2ee05a1bd8b3e333fb631f971499d93bbae6a1e3bc04246b799391d53aa2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:PV5ET5YFMMHC3FXUUXED3D2UY4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hao Tan, Huijia Zhu, Jian Cao, Jun Lan, Wei Guan, Weiqiang Wang","submitted_at":"2025-07-29T09:18:22Z","abstract_excerpt":"Industrial anomaly detection (IAD) plays a crucial role in maintaining the safety and reliability of manufacturing systems. While multimodal large language models (MLLMs) show strong vision-language reasoning abilities, their effectiveness in IAD remains limited without domain-specific adaptation. In this work, we propose EMIT, a unified framework that enhances MLLMs for IAD via difficulty-aware group relative policy optimization (GRPO). EMIT constructs a multi-task IAD dataset and utilizes GPT-generated object text descriptions to compensate for missing defective images. For few-shot anomaly "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21619","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/2507.21619/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:45:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ci0MnZa0axlR2tygNsGisBwGD3d+ITdoowkKKgpg4Q9M6bi2yqX45JjtA5AKhdbf+FL0dfHUzcZu4QwVNrziCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:52:06.291314Z"},"content_sha256":"35241540828ed905b5d60b24c67c2c0379e86a7b02db6b6fc4c7314b81bddee8","schema_version":"1.0","event_id":"sha256:35241540828ed905b5d60b24c67c2c0379e86a7b02db6b6fc4c7314b81bddee8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PV5ET5YFMMHC3FXUUXED3D2UY4/bundle.json","state_url":"https://pith.science/pith/PV5ET5YFMMHC3FXUUXED3D2UY4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PV5ET5YFMMHC3FXUUXED3D2UY4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-07T16:52:06Z","links":{"resolver":"https://pith.science/pith/PV5ET5YFMMHC3FXUUXED3D2UY4","bundle":"https://pith.science/pith/PV5ET5YFMMHC3FXUUXED3D2UY4/bundle.json","state":"https://pith.science/pith/PV5ET5YFMMHC3FXUUXED3D2UY4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PV5ET5YFMMHC3FXUUXED3D2UY4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:PV5ET5YFMMHC3FXUUXED3D2UY4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"27741e03fc88931fe40b859ef858f442b94e5bab897f1fe042dac5b6a1b571b8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:18:22Z","title_canon_sha256":"44501399bcd17cd053d97a41cae070cebecd90e94cc43ef306c1ced24f82a7a6"},"schema_version":"1.0","source":{"id":"2507.21619","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21619","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21619v1","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21619","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_12","alias_value":"PV5ET5YFMMHC","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_16","alias_value":"PV5ET5YFMMHC3FXU","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_8","alias_value":"PV5ET5YF","created_at":"2026-07-05T11:45:03Z"}],"graph_snapshots":[{"event_id":"sha256:35241540828ed905b5d60b24c67c2c0379e86a7b02db6b6fc4c7314b81bddee8","target":"graph","created_at":"2026-07-05T11:45:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.21619/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Industrial anomaly detection (IAD) plays a crucial role in maintaining the safety and reliability of manufacturing systems. While multimodal large language models (MLLMs) show strong vision-language reasoning abilities, their effectiveness in IAD remains limited without domain-specific adaptation. In this work, we propose EMIT, a unified framework that enhances MLLMs for IAD via difficulty-aware group relative policy optimization (GRPO). EMIT constructs a multi-task IAD dataset and utilizes GPT-generated object text descriptions to compensate for missing defective images. For few-shot anomaly ","authors_text":"Hao Tan, Huijia Zhu, Jian Cao, Jun Lan, Wei Guan, Weiqiang Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:18:22Z","title":"EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21619","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:107d2ee05a1bd8b3e333fb631f971499d93bbae6a1e3bc04246b799391d53aa2","target":"record","created_at":"2026-07-05T11:45:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"27741e03fc88931fe40b859ef858f442b94e5bab897f1fe042dac5b6a1b571b8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:18:22Z","title_canon_sha256":"44501399bcd17cd053d97a41cae070cebecd90e94cc43ef306c1ced24f82a7a6"},"schema_version":"1.0","source":{"id":"2507.21619","kind":"arxiv","version":1}},"canonical_sha256":"7d7a49f705630e2d96f4a5c83d8f54c7025a90e6427a5d2ee649f792b3be24e2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7d7a49f705630e2d96f4a5c83d8f54c7025a90e6427a5d2ee649f792b3be24e2","first_computed_at":"2026-07-05T11:45:03.288438Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:03.288438Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FOMC2qZzEtO2CMexpzMQXptc0YVwUkohbjUoIhj6dphqqn5tdyekjbGSM+tzz12LKVMBckXvhLmDrKzruzprAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:03.288877Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.21619","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:107d2ee05a1bd8b3e333fb631f971499d93bbae6a1e3bc04246b799391d53aa2","sha256:35241540828ed905b5d60b24c67c2c0379e86a7b02db6b6fc4c7314b81bddee8"],"state_sha256":"cf49a28f00ed4e3eea6db2975bed5caf32ea010fc19428c0958e700ace5b7982"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vn8G6tOZGy/vt7+/sV/Rqmwd3jljaIIEysiCqk21MbcUzAKSXSfeW46JPkytH9JT8b9yaoHRruw2z1NFFGFtAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T16:52:06.296950Z","bundle_sha256":"4a31821dc0cbdba48ba6927780937cc5eb68b3e973927470b2df8d94f5f6b455"}}