{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:H3T5GARM7V46MS5IJR4HWGQCYM","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":"72424b0464ea037ee2c339735d9ec50e049ed702e81df7cadb51b653a99384a3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T10:15:40Z","title_canon_sha256":"c223021dda1bc1ea74c4b89168e4b70a74eae6d9cf3a7326c2195aa16d29805a"},"schema_version":"1.0","source":{"id":"2605.18172","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18172","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18172v1","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18172","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_12","alias_value":"H3T5GARM7V46","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_16","alias_value":"H3T5GARM7V46MS5I","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_8","alias_value":"H3T5GARM","created_at":"2026-05-20T00:05:49Z"}],"graph_snapshots":[{"event_id":"sha256:3544a278e837da9cfc4a5482ce745b1d5945f7fc24102c77dab788c7cd59fee9","target":"graph","created_at":"2026-05-20T00:05:49Z","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":[{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T23:41:59.044818Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.351173Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.18172/integrity.json","findings":[],"snapshot_sha256":"53bcc5a85c6a61cd341a954441ce111e69aace5934a34a0dfed9072288f39ded","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Leveraging the universal representations of pre-trained LLMs and MLLMs offers a promising path toward brain foundation models. However, visually-evoked EEG datasets remain scarce, leading existing methods to align neural signals mainly with abstract text, a lossy translation that may discard fine-grained perceptual information encoded in brain activity. We propose Generative Visual Grounding (GVG), a framework that visualizes the invisible by using an EEG-to-image generative model as a visual translator. Instead of forcing EEG into text alone, GVG hallucinates instance-specific proxy images fo","authors_text":"Baoliang Lu, Dongsheng Li, Enze Zhang, Junyu Pan, Weilong Zheng, Yansen Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T10:15:40Z","title":"Visualizing the Invisible: Generative Visual Grounding Empowers Universal EEG Understanding in MLLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18172","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":"sha256:665d0f9933653a458f7f55005c5d79dbea2c452d2b944b68833b538e2fd7c725","target":"record","created_at":"2026-05-20T00:05:49Z","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":"72424b0464ea037ee2c339735d9ec50e049ed702e81df7cadb51b653a99384a3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T10:15:40Z","title_canon_sha256":"c223021dda1bc1ea74c4b89168e4b70a74eae6d9cf3a7326c2195aa16d29805a"},"schema_version":"1.0","source":{"id":"2605.18172","kind":"arxiv","version":1}},"canonical_sha256":"3ee7d3022cfd79e64ba84c787b1a02c316e4effb0e16d1254125c1fbc346c856","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3ee7d3022cfd79e64ba84c787b1a02c316e4effb0e16d1254125c1fbc346c856","first_computed_at":"2026-05-20T00:05:49.255742Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:05:49.255742Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"g49NsAawQHl/7bY9RirhgrgwqKexXSfTD1G6NxF7l2wEPoIaG0OTgpJLBem8ECb/B+g8TsH/6Hy0qXGMxIKtCQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:05:49.256232Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.18172","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:665d0f9933653a458f7f55005c5d79dbea2c452d2b944b68833b538e2fd7c725","sha256:3544a278e837da9cfc4a5482ce745b1d5945f7fc24102c77dab788c7cd59fee9"],"state_sha256":"ebf2605c0bd46f999e3937df3f38f4db0d56975e4b4da69fbab18da721300d32"}