{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:44VCDRSS2BFH4S53KWIGLXKS62","short_pith_number":"pith:44VCDRSS","canonical_record":{"source":{"id":"2606.01069","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-31T07:25:49Z","cross_cats_sorted":[],"title_canon_sha256":"d79984aa5a8d9e8564b53c8e8bfdb9eee10c19ca6af4ae790b693c296f0d7567","abstract_canon_sha256":"0496607ac786cdf4e1635f53274e3801b4d4f3159df46ee8dbad6de5a4c2a594"},"schema_version":"1.0"},"canonical_sha256":"e72a21c652d04a7e4bbb559065dd52f6bc154de5c4f3146595bbc752d5b589b0","source":{"kind":"arxiv","id":"2606.01069","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.01069","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"arxiv_version","alias_value":"2606.01069v1","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01069","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"pith_short_12","alias_value":"44VCDRSS2BFH","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"pith_short_16","alias_value":"44VCDRSS2BFH4S53","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"pith_short_8","alias_value":"44VCDRSS","created_at":"2026-06-02T01:04:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:44VCDRSS2BFH4S53KWIGLXKS62","target":"record","payload":{"canonical_record":{"source":{"id":"2606.01069","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-31T07:25:49Z","cross_cats_sorted":[],"title_canon_sha256":"d79984aa5a8d9e8564b53c8e8bfdb9eee10c19ca6af4ae790b693c296f0d7567","abstract_canon_sha256":"0496607ac786cdf4e1635f53274e3801b4d4f3159df46ee8dbad6de5a4c2a594"},"schema_version":"1.0"},"canonical_sha256":"e72a21c652d04a7e4bbb559065dd52f6bc154de5c4f3146595bbc752d5b589b0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T01:04:20.442006Z","signature_b64":"OJPN3sIItEoD8dYChuyPF6v25WPzf0wL23u8MuTBF3AwCdH3jHbD3JbwcXZngq7tsPE219nxOcnVfgKZIzTJCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e72a21c652d04a7e4bbb559065dd52f6bc154de5c4f3146595bbc752d5b589b0","last_reissued_at":"2026-06-02T01:04:20.441491Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T01:04:20.441491Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.01069","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":"2026-06-02T01:04:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Js/AVVNguYsjV09rmg6dhWlwt7Mx9WBbBZTHNO+/vmv1MMuCdLBVgF8eVaZcxYeX67QS5xazTJo0fyrQw0jcCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T21:47:02.774010Z"},"content_sha256":"9e88721783fd36431b8700728a60683102e43686daadf190061e08147f87e66c","schema_version":"1.0","event_id":"sha256:9e88721783fd36431b8700728a60683102e43686daadf190061e08147f87e66c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:44VCDRSS2BFH4S53KWIGLXKS62","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Multiscale Network with Supervised Contrastive Learning for Real-Time Facial Emotion Recognition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Archisman Adhikary, Chayan Halder, Kaushik Roy, Payel Rakshit, Rejoy Chakraborty, Sanchita Ghosh","submitted_at":"2026-05-31T07:25:49Z","abstract_excerpt":"Real-time emotion recognition from facial expressions is a challenging task, particularly in video-based scenarios where multiple emotional states may occur over time. The difficulty increases further due to the fact that each emotional state is associated with facial expressions that vary significantly across individuals. The change of facial expressions portraying emotional state is not discrete, but rather continuous, which is very challenging to represent through computational aids. A system with the ability to detect variations in facial expressions can have a significant impact on determ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01069","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/2606.01069/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":"2026-06-02T01:04:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"07vwLxxqOoCk4PY5GZ7bhuiY+ah0PbtZZtkELLeI3kr4PW7dPeYlvJ4boAcP3uLXmVD6mQkRylcjgRLinwPPDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T21:47:02.774407Z"},"content_sha256":"9ced23dd9be782744bba041a9cfba4d053ea6ec1a5e8815332521315731d8239","schema_version":"1.0","event_id":"sha256:9ced23dd9be782744bba041a9cfba4d053ea6ec1a5e8815332521315731d8239"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/44VCDRSS2BFH4S53KWIGLXKS62/bundle.json","state_url":"https://pith.science/pith/44VCDRSS2BFH4S53KWIGLXKS62/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/44VCDRSS2BFH4S53KWIGLXKS62/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":"2026-06-25T21:47:02Z","links":{"resolver":"https://pith.science/pith/44VCDRSS2BFH4S53KWIGLXKS62","bundle":"https://pith.science/pith/44VCDRSS2BFH4S53KWIGLXKS62/bundle.json","state":"https://pith.science/pith/44VCDRSS2BFH4S53KWIGLXKS62/state.json","well_known_bundle":"https://pith.science/.well-known/pith/44VCDRSS2BFH4S53KWIGLXKS62/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:44VCDRSS2BFH4S53KWIGLXKS62","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":"0496607ac786cdf4e1635f53274e3801b4d4f3159df46ee8dbad6de5a4c2a594","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-31T07:25:49Z","title_canon_sha256":"d79984aa5a8d9e8564b53c8e8bfdb9eee10c19ca6af4ae790b693c296f0d7567"},"schema_version":"1.0","source":{"id":"2606.01069","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.01069","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"arxiv_version","alias_value":"2606.01069v1","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01069","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"pith_short_12","alias_value":"44VCDRSS2BFH","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"pith_short_16","alias_value":"44VCDRSS2BFH4S53","created_at":"2026-06-02T01:04:20Z"},{"alias_kind":"pith_short_8","alias_value":"44VCDRSS","created_at":"2026-06-02T01:04:20Z"}],"graph_snapshots":[{"event_id":"sha256:9ced23dd9be782744bba041a9cfba4d053ea6ec1a5e8815332521315731d8239","target":"graph","created_at":"2026-06-02T01:04:20Z","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/2606.01069/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Real-time emotion recognition from facial expressions is a challenging task, particularly in video-based scenarios where multiple emotional states may occur over time. The difficulty increases further due to the fact that each emotional state is associated with facial expressions that vary significantly across individuals. The change of facial expressions portraying emotional state is not discrete, but rather continuous, which is very challenging to represent through computational aids. A system with the ability to detect variations in facial expressions can have a significant impact on determ","authors_text":"Archisman Adhikary, Chayan Halder, Kaushik Roy, Payel Rakshit, Rejoy Chakraborty, Sanchita Ghosh","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-31T07:25:49Z","title":"A Multiscale Network with Supervised Contrastive Learning for Real-Time Facial Emotion Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01069","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":"sha256:9e88721783fd36431b8700728a60683102e43686daadf190061e08147f87e66c","target":"record","created_at":"2026-06-02T01:04:20Z","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":"0496607ac786cdf4e1635f53274e3801b4d4f3159df46ee8dbad6de5a4c2a594","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-31T07:25:49Z","title_canon_sha256":"d79984aa5a8d9e8564b53c8e8bfdb9eee10c19ca6af4ae790b693c296f0d7567"},"schema_version":"1.0","source":{"id":"2606.01069","kind":"arxiv","version":1}},"canonical_sha256":"e72a21c652d04a7e4bbb559065dd52f6bc154de5c4f3146595bbc752d5b589b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e72a21c652d04a7e4bbb559065dd52f6bc154de5c4f3146595bbc752d5b589b0","first_computed_at":"2026-06-02T01:04:20.441491Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T01:04:20.441491Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OJPN3sIItEoD8dYChuyPF6v25WPzf0wL23u8MuTBF3AwCdH3jHbD3JbwcXZngq7tsPE219nxOcnVfgKZIzTJCw==","signature_status":"signed_v1","signed_at":"2026-06-02T01:04:20.442006Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.01069","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9e88721783fd36431b8700728a60683102e43686daadf190061e08147f87e66c","sha256:9ced23dd9be782744bba041a9cfba4d053ea6ec1a5e8815332521315731d8239"],"state_sha256":"632e8bc6252299088aa3ea602c2d4a3421b9f41e9c4f4dfeec1bd345aed97291"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TuM6DLrrYhbujbmR164YYPH5GY3UV7hN0sWrRa1Iy18DZ1Z3T5/xKu01L+fHPpPjI92yCAnbylZFfg838SnzAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T21:47:02.776462Z","bundle_sha256":"8b2df3f51d8d7ca5956e1e0d5f86ca1b7806ee75fab3edfb1441480a5a2ac484"}}