{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:EE32JH4DGZZEN26ZBEF4PTGGQI","short_pith_number":"pith:EE32JH4D","canonical_record":{"source":{"id":"2607.20462","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-16T08:16:08Z","cross_cats_sorted":[],"title_canon_sha256":"762ca303e01e62c708d1cda5134bd04b0c552048eef0648f082e62394343ae7f","abstract_canon_sha256":"a5c605e9d3605ab3fd3ee0d00e43481f97ff58dff35ef3b59c4705c9386138dc"},"schema_version":"1.0"},"canonical_sha256":"2137a49f83367246ebd9090bc7ccc6823cf9b6a35c22e5f88bbf2e2843b6cc76","source":{"kind":"arxiv","id":"2607.20462","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.20462","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"arxiv_version","alias_value":"2607.20462v1","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.20462","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"pith_short_12","alias_value":"EE32JH4DGZZE","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"pith_short_16","alias_value":"EE32JH4DGZZEN26Z","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"pith_short_8","alias_value":"EE32JH4D","created_at":"2026-07-24T00:23:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:EE32JH4DGZZEN26ZBEF4PTGGQI","target":"record","payload":{"canonical_record":{"source":{"id":"2607.20462","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-16T08:16:08Z","cross_cats_sorted":[],"title_canon_sha256":"762ca303e01e62c708d1cda5134bd04b0c552048eef0648f082e62394343ae7f","abstract_canon_sha256":"a5c605e9d3605ab3fd3ee0d00e43481f97ff58dff35ef3b59c4705c9386138dc"},"schema_version":"1.0"},"canonical_sha256":"2137a49f83367246ebd9090bc7ccc6823cf9b6a35c22e5f88bbf2e2843b6cc76","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-24T00:23:16.851940Z","signature_b64":"OpuDBl9Wbcr12E+55TptFWzMzsd0l8M3/5LlbiLP6tpjSWaP0cZjJSDfP70fHNwQIrlZrokZtzn6IGD/e+RZBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2137a49f83367246ebd9090bc7ccc6823cf9b6a35c22e5f88bbf2e2843b6cc76","last_reissued_at":"2026-07-24T00:23:16.851076Z","signature_status":"signed_v1","first_computed_at":"2026-07-24T00:23:16.851076Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.20462","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":"2026-07-24T00:23:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CBGFAT4UstuVDVxM40uw9HclOF3nsB/d20sX1uBuWInMlBbx68qGMLsS4UrTFAX+se1jbNu15sGdIA3rdj8IAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T14:41:13.746744Z"},"content_sha256":"629f1e1532363110d9bcce557a3d91508b572d803235177506df8b0f4fa04267","schema_version":"1.0","event_id":"sha256:629f1e1532363110d9bcce557a3d91508b572d803235177506df8b0f4fa04267"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:EE32JH4DGZZEN26ZBEF4PTGGQI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Martin Vechev, Melanie Rieff, Robin Staab, Stefan Hegselmann, Thibaud Gloaguen","submitted_at":"2026-05-16T08:16:08Z","abstract_excerpt":"Large language models (LLMs) are increasingly integrated into clinical workflows, stressing the need for reliable traceability of model-generated output with watermarking. Yet, most watermarks are evaluated on general-purpose benchmarks, leaving domains like medicine, where small token-level perturbations can result in significant semantic changes, underexplored. In this work, we present the first rigorous study of how LLM watermarks affect medical performance, benchmarking 5 watermarking schemes across 11 LLMs and 7 VLMs on various tasks spanning unimodal and multimodal clinical reasoning. Im"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.20462","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/2607.20462/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":"2026-07-24T00:23:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5ht2GecbtqRo1pHCQKnna20NmFXtielJjli47LR8nMXMxVKQhDrUXHvOAqzOZuvYM6mS7FGxHT7uWk3e5H0UBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T14:41:13.747596Z"},"content_sha256":"045205ac4bca61183569ad22a1ec8b0ad85dcdebcec7a8f9341220b90cc50fef","schema_version":"1.0","event_id":"sha256:045205ac4bca61183569ad22a1ec8b0ad85dcdebcec7a8f9341220b90cc50fef"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EE32JH4DGZZEN26ZBEF4PTGGQI/bundle.json","state_url":"https://pith.science/pith/EE32JH4DGZZEN26ZBEF4PTGGQI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EE32JH4DGZZEN26ZBEF4PTGGQI/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":"2026-08-10T14:41:13Z","links":{"resolver":"https://pith.science/pith/EE32JH4DGZZEN26ZBEF4PTGGQI","bundle":"https://pith.science/pith/EE32JH4DGZZEN26ZBEF4PTGGQI/bundle.json","state":"https://pith.science/pith/EE32JH4DGZZEN26ZBEF4PTGGQI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EE32JH4DGZZEN26ZBEF4PTGGQI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:EE32JH4DGZZEN26ZBEF4PTGGQI","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":"a5c605e9d3605ab3fd3ee0d00e43481f97ff58dff35ef3b59c4705c9386138dc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-16T08:16:08Z","title_canon_sha256":"762ca303e01e62c708d1cda5134bd04b0c552048eef0648f082e62394343ae7f"},"schema_version":"1.0","source":{"id":"2607.20462","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.20462","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"arxiv_version","alias_value":"2607.20462v1","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.20462","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"pith_short_12","alias_value":"EE32JH4DGZZE","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"pith_short_16","alias_value":"EE32JH4DGZZEN26Z","created_at":"2026-07-24T00:23:16Z"},{"alias_kind":"pith_short_8","alias_value":"EE32JH4D","created_at":"2026-07-24T00:23:16Z"}],"graph_snapshots":[{"event_id":"sha256:045205ac4bca61183569ad22a1ec8b0ad85dcdebcec7a8f9341220b90cc50fef","target":"graph","created_at":"2026-07-24T00:23:16Z","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/2607.20462/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are increasingly integrated into clinical workflows, stressing the need for reliable traceability of model-generated output with watermarking. Yet, most watermarks are evaluated on general-purpose benchmarks, leaving domains like medicine, where small token-level perturbations can result in significant semantic changes, underexplored. In this work, we present the first rigorous study of how LLM watermarks affect medical performance, benchmarking 5 watermarking schemes across 11 LLMs and 7 VLMs on various tasks spanning unimodal and multimodal clinical reasoning. Im","authors_text":"Martin Vechev, Melanie Rieff, Robin Staab, Stefan Hegselmann, Thibaud Gloaguen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-16T08:16:08Z","title":"Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.20462","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":"sha256:629f1e1532363110d9bcce557a3d91508b572d803235177506df8b0f4fa04267","target":"record","created_at":"2026-07-24T00:23:16Z","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":"a5c605e9d3605ab3fd3ee0d00e43481f97ff58dff35ef3b59c4705c9386138dc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-16T08:16:08Z","title_canon_sha256":"762ca303e01e62c708d1cda5134bd04b0c552048eef0648f082e62394343ae7f"},"schema_version":"1.0","source":{"id":"2607.20462","kind":"arxiv","version":1}},"canonical_sha256":"2137a49f83367246ebd9090bc7ccc6823cf9b6a35c22e5f88bbf2e2843b6cc76","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2137a49f83367246ebd9090bc7ccc6823cf9b6a35c22e5f88bbf2e2843b6cc76","first_computed_at":"2026-07-24T00:23:16.851076Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-24T00:23:16.851076Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OpuDBl9Wbcr12E+55TptFWzMzsd0l8M3/5LlbiLP6tpjSWaP0cZjJSDfP70fHNwQIrlZrokZtzn6IGD/e+RZBA==","signature_status":"signed_v1","signed_at":"2026-07-24T00:23:16.851940Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.20462","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:629f1e1532363110d9bcce557a3d91508b572d803235177506df8b0f4fa04267","sha256:045205ac4bca61183569ad22a1ec8b0ad85dcdebcec7a8f9341220b90cc50fef"],"state_sha256":"237461d98dd3f847476da308d9bd63db04ff8d171ddaf7a4b17a9e471d964769"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qj56wO7Yk1OhnW0l2CM/iXbrBmBDcW4J2G2rRXsl1kGG5F66JzOej5mPU3ina3y03h+fofW8TODq3hmuoebVDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T14:41:13.751607Z","bundle_sha256":"d2c099583e09614686daef6cf3bc0a2e91ec80b1fa9483cc7d034bcc308d47b7"}}