{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:HSBXI6ISJEOGN7VT24BPM5DLXJ","short_pith_number":"pith:HSBXI6IS","canonical_record":{"source":{"id":"2606.23063","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T09:13:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b50da1164f6166ed5fb5def54c80b5b0d6f2f19b057aeafcff9b9272edc281f4","abstract_canon_sha256":"e163fdd3713e93e0bbfb8866d47d8833fb9ea87f0ef1401553c23ef4ea803e02"},"schema_version":"1.0"},"canonical_sha256":"3c83747912491c66feb3d702f6746bba5647abcd51de4a8c9c884212918d87ad","source":{"kind":"arxiv","id":"2606.23063","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23063","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23063v1","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23063","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"pith_short_12","alias_value":"HSBXI6ISJEOG","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"pith_short_16","alias_value":"HSBXI6ISJEOGN7VT","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"pith_short_8","alias_value":"HSBXI6IS","created_at":"2026-06-23T03:14:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:HSBXI6ISJEOGN7VT24BPM5DLXJ","target":"record","payload":{"canonical_record":{"source":{"id":"2606.23063","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T09:13:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b50da1164f6166ed5fb5def54c80b5b0d6f2f19b057aeafcff9b9272edc281f4","abstract_canon_sha256":"e163fdd3713e93e0bbfb8866d47d8833fb9ea87f0ef1401553c23ef4ea803e02"},"schema_version":"1.0"},"canonical_sha256":"3c83747912491c66feb3d702f6746bba5647abcd51de4a8c9c884212918d87ad","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T03:14:08.752478Z","signature_b64":"4HRNEvgcGSUTThz9cxb0KXlPLw0yRJj/qtSWptCSvEkLBI61KltMV3hgiJ6ML6PvVZm8E3wV6MstSO+0rTMcAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c83747912491c66feb3d702f6746bba5647abcd51de4a8c9c884212918d87ad","last_reissued_at":"2026-06-23T03:14:08.752033Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T03:14:08.752033Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.23063","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":"2026-06-23T03:14:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sKExj9N7FPtvsXUK0UPBCn1kgdnTe/z7wz0nySG0kZMwSMl0RhR6BxSVbYkwekzWZJaHXe9fxhYD/5G+VcurBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T04:33:49.391822Z"},"content_sha256":"d9dd3be2008ef5fb263c1a740d684da919ddb7c1e98d7c03ec2692368850a9fd","schema_version":"1.0","event_id":"sha256:d9dd3be2008ef5fb263c1a740d684da919ddb7c1e98d7c03ec2692368850a9fd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:HSBXI6ISJEOGN7VT24BPM5DLXJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Attention-Spectrum Regularization for Replay-Free Continual Multimodal LLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Canran Xiao, Chuangxin Zhao, Guiguang Ding, Jun Xia, Mengyao Lyu, Siyuan Ma, Yanbiao Ma, Yang Liu","submitted_at":"2026-06-22T09:13:53Z","abstract_excerpt":"Multimodal large language models (MLLMs) are increasingly required to adapt to non-stationary streams of visual domains, question types, and user instructions, yet continual fine-tuning often causes severe forgetting of previously acquired multimodal skills. Existing continual vision-language methods mainly preserve outputs, replay data or pseudo-data, regularize embedding geometry, or allocate task-specific parameters, but they provide limited control over how internal cross-modal attention patterns supporting old skills drift during adaptation. We propose Attention-Spectrum Regularization (A"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23063","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/2606.23063/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":"2026-06-23T03:14:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FDetac6UH6JeN9C75OCqkcaVwM/KObVkwMlRqs0/mm6fZcZzTA96NO1hNEdzgf4mX7p99ej6sbkcvk46Do08CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T04:33:49.392190Z"},"content_sha256":"bf3e97aeade0241e29573252b582515fa1d5537582abf7aef4ce4087f547cfb7","schema_version":"1.0","event_id":"sha256:bf3e97aeade0241e29573252b582515fa1d5537582abf7aef4ce4087f547cfb7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HSBXI6ISJEOGN7VT24BPM5DLXJ/bundle.json","state_url":"https://pith.science/pith/HSBXI6ISJEOGN7VT24BPM5DLXJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HSBXI6ISJEOGN7VT24BPM5DLXJ/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":"2026-06-30T04:33:49Z","links":{"resolver":"https://pith.science/pith/HSBXI6ISJEOGN7VT24BPM5DLXJ","bundle":"https://pith.science/pith/HSBXI6ISJEOGN7VT24BPM5DLXJ/bundle.json","state":"https://pith.science/pith/HSBXI6ISJEOGN7VT24BPM5DLXJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HSBXI6ISJEOGN7VT24BPM5DLXJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:HSBXI6ISJEOGN7VT24BPM5DLXJ","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":"e163fdd3713e93e0bbfb8866d47d8833fb9ea87f0ef1401553c23ef4ea803e02","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T09:13:53Z","title_canon_sha256":"b50da1164f6166ed5fb5def54c80b5b0d6f2f19b057aeafcff9b9272edc281f4"},"schema_version":"1.0","source":{"id":"2606.23063","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23063","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23063v1","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23063","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"pith_short_12","alias_value":"HSBXI6ISJEOG","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"pith_short_16","alias_value":"HSBXI6ISJEOGN7VT","created_at":"2026-06-23T03:14:08Z"},{"alias_kind":"pith_short_8","alias_value":"HSBXI6IS","created_at":"2026-06-23T03:14:08Z"}],"graph_snapshots":[{"event_id":"sha256:bf3e97aeade0241e29573252b582515fa1d5537582abf7aef4ce4087f547cfb7","target":"graph","created_at":"2026-06-23T03:14:08Z","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/2606.23063/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal large language models (MLLMs) are increasingly required to adapt to non-stationary streams of visual domains, question types, and user instructions, yet continual fine-tuning often causes severe forgetting of previously acquired multimodal skills. Existing continual vision-language methods mainly preserve outputs, replay data or pseudo-data, regularize embedding geometry, or allocate task-specific parameters, but they provide limited control over how internal cross-modal attention patterns supporting old skills drift during adaptation. We propose Attention-Spectrum Regularization (A","authors_text":"Canran Xiao, Chuangxin Zhao, Guiguang Ding, Jun Xia, Mengyao Lyu, Siyuan Ma, Yanbiao Ma, Yang Liu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T09:13:53Z","title":"Attention-Spectrum Regularization for Replay-Free Continual Multimodal LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23063","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:d9dd3be2008ef5fb263c1a740d684da919ddb7c1e98d7c03ec2692368850a9fd","target":"record","created_at":"2026-06-23T03:14:08Z","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":"e163fdd3713e93e0bbfb8866d47d8833fb9ea87f0ef1401553c23ef4ea803e02","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T09:13:53Z","title_canon_sha256":"b50da1164f6166ed5fb5def54c80b5b0d6f2f19b057aeafcff9b9272edc281f4"},"schema_version":"1.0","source":{"id":"2606.23063","kind":"arxiv","version":1}},"canonical_sha256":"3c83747912491c66feb3d702f6746bba5647abcd51de4a8c9c884212918d87ad","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3c83747912491c66feb3d702f6746bba5647abcd51de4a8c9c884212918d87ad","first_computed_at":"2026-06-23T03:14:08.752033Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T03:14:08.752033Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4HRNEvgcGSUTThz9cxb0KXlPLw0yRJj/qtSWptCSvEkLBI61KltMV3hgiJ6ML6PvVZm8E3wV6MstSO+0rTMcAg==","signature_status":"signed_v1","signed_at":"2026-06-23T03:14:08.752478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.23063","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d9dd3be2008ef5fb263c1a740d684da919ddb7c1e98d7c03ec2692368850a9fd","sha256:bf3e97aeade0241e29573252b582515fa1d5537582abf7aef4ce4087f547cfb7"],"state_sha256":"a7dc0b20a255ba57f24b18be13e09ba65b8f89b5c42a14a22e483cc082b6e0a0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3WyiOsmn3Ne+cPjEGMyg4oulQ4rg5G3c+XXwi4Iq7oE6Y5IryW3Ts4QJGILKwRbb4a43hS5AChVGwy+VgkX/Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T04:33:49.394188Z","bundle_sha256":"af2a88ce6a3ce199441204e337ee7c106e823332325932c1e0d59004e8ff3f46"}}