{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ULN6J2S6HMWG75OGT3AHSGDOZA","short_pith_number":"pith:ULN6J2S6","canonical_record":{"source":{"id":"2508.04827","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T19:12:42Z","cross_cats_sorted":[],"title_canon_sha256":"1f1645c599b3f09d1e062fc051845a370d87b64aa86ed690a76673ad0632e0e0","abstract_canon_sha256":"8041513fb20a48c7585040110190bdb70f25dc551de7d2d3eeb1a33a949c77a5"},"schema_version":"1.0"},"canonical_sha256":"a2dbe4ea5e3b2c6ff5c69ec079186ec80e4efdc1a7a84f681d3eb442f396d737","source":{"kind":"arxiv","id":"2508.04827","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.04827","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"arxiv_version","alias_value":"2508.04827v1","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.04827","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"pith_short_12","alias_value":"ULN6J2S6HMWG","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"pith_short_16","alias_value":"ULN6J2S6HMWG75OG","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"pith_short_8","alias_value":"ULN6J2S6","created_at":"2026-07-05T11:50:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ULN6J2S6HMWG75OGT3AHSGDOZA","target":"record","payload":{"canonical_record":{"source":{"id":"2508.04827","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T19:12:42Z","cross_cats_sorted":[],"title_canon_sha256":"1f1645c599b3f09d1e062fc051845a370d87b64aa86ed690a76673ad0632e0e0","abstract_canon_sha256":"8041513fb20a48c7585040110190bdb70f25dc551de7d2d3eeb1a33a949c77a5"},"schema_version":"1.0"},"canonical_sha256":"a2dbe4ea5e3b2c6ff5c69ec079186ec80e4efdc1a7a84f681d3eb442f396d737","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:50:02.710641Z","signature_b64":"AJmZQBEcVTuZY0enX6y8bFLsAvC++ANs09i810334AHrqBEWu6dkzoh8XXgcUvtS9ZBy0IDEdr9OkabR/eacAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a2dbe4ea5e3b2c6ff5c69ec079186ec80e4efdc1a7a84f681d3eb442f396d737","last_reissued_at":"2026-07-05T11:50:02.710196Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:50:02.710196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.04827","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":"2026-07-05T11:50:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E3QVhM8rr+XsyYnSt5p97HMnPoqGTIFvkCZGIIr7/j6HL3KrwgJhC/7swxFgJ6O8urbhxTGYDxkCvlg8WY1CBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:53:21.089503Z"},"content_sha256":"7bde7261950479b3d02b48b4160e9b082f79fb6499e9038518363765ee2ec81e","schema_version":"1.0","event_id":"sha256:7bde7261950479b3d02b48b4160e9b082f79fb6499e9038518363765ee2ec81e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ULN6J2S6HMWG75OGT3AHSGDOZA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A deep learning approach to track eye movements based on events","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chirag Seth, Divya Naiken, Keyan Lin","submitted_at":"2025-08-06T19:12:42Z","abstract_excerpt":"This research project addresses the challenge of accurately tracking eye movements during specific events by leveraging previous research. Given the rapid movements of human eyes, which can reach speeds of 300{\\deg}/s, precise eye tracking typically requires expensive and high-speed cameras. Our primary objective is to locate the eye center position (x, y) using inputs from an event camera. Eye movement analysis has extensive applications in consumer electronics, especially in VR and AR product development. Therefore, our ultimate goal is to develop an interpretable and cost-effective algorith"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.04827","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/2508.04827/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":"2026-07-05T11:50:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rc+Nx7rbMTomrCzIpKdzYBd0uPJ5YvAbhMFGJaGG7hLmagYENAWAG9hlIYjkqdLcTL8fkg6/I9FccjrRsL+jDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:53:21.090026Z"},"content_sha256":"78e6a3807cf40c698f92c8245dde115e863af9f7116e62b3243b8831a7c64b09","schema_version":"1.0","event_id":"sha256:78e6a3807cf40c698f92c8245dde115e863af9f7116e62b3243b8831a7c64b09"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ULN6J2S6HMWG75OGT3AHSGDOZA/bundle.json","state_url":"https://pith.science/pith/ULN6J2S6HMWG75OGT3AHSGDOZA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ULN6J2S6HMWG75OGT3AHSGDOZA/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":"2026-08-06T19:53:21Z","links":{"resolver":"https://pith.science/pith/ULN6J2S6HMWG75OGT3AHSGDOZA","bundle":"https://pith.science/pith/ULN6J2S6HMWG75OGT3AHSGDOZA/bundle.json","state":"https://pith.science/pith/ULN6J2S6HMWG75OGT3AHSGDOZA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ULN6J2S6HMWG75OGT3AHSGDOZA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ULN6J2S6HMWG75OGT3AHSGDOZA","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":"8041513fb20a48c7585040110190bdb70f25dc551de7d2d3eeb1a33a949c77a5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T19:12:42Z","title_canon_sha256":"1f1645c599b3f09d1e062fc051845a370d87b64aa86ed690a76673ad0632e0e0"},"schema_version":"1.0","source":{"id":"2508.04827","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.04827","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"arxiv_version","alias_value":"2508.04827v1","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.04827","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"pith_short_12","alias_value":"ULN6J2S6HMWG","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"pith_short_16","alias_value":"ULN6J2S6HMWG75OG","created_at":"2026-07-05T11:50:02Z"},{"alias_kind":"pith_short_8","alias_value":"ULN6J2S6","created_at":"2026-07-05T11:50:02Z"}],"graph_snapshots":[{"event_id":"sha256:78e6a3807cf40c698f92c8245dde115e863af9f7116e62b3243b8831a7c64b09","target":"graph","created_at":"2026-07-05T11:50:02Z","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/2508.04827/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This research project addresses the challenge of accurately tracking eye movements during specific events by leveraging previous research. Given the rapid movements of human eyes, which can reach speeds of 300{\\deg}/s, precise eye tracking typically requires expensive and high-speed cameras. Our primary objective is to locate the eye center position (x, y) using inputs from an event camera. Eye movement analysis has extensive applications in consumer electronics, especially in VR and AR product development. Therefore, our ultimate goal is to develop an interpretable and cost-effective algorith","authors_text":"Chirag Seth, Divya Naiken, Keyan Lin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T19:12:42Z","title":"A deep learning approach to track eye movements based on events"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.04827","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":"sha256:7bde7261950479b3d02b48b4160e9b082f79fb6499e9038518363765ee2ec81e","target":"record","created_at":"2026-07-05T11:50:02Z","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":"8041513fb20a48c7585040110190bdb70f25dc551de7d2d3eeb1a33a949c77a5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T19:12:42Z","title_canon_sha256":"1f1645c599b3f09d1e062fc051845a370d87b64aa86ed690a76673ad0632e0e0"},"schema_version":"1.0","source":{"id":"2508.04827","kind":"arxiv","version":1}},"canonical_sha256":"a2dbe4ea5e3b2c6ff5c69ec079186ec80e4efdc1a7a84f681d3eb442f396d737","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a2dbe4ea5e3b2c6ff5c69ec079186ec80e4efdc1a7a84f681d3eb442f396d737","first_computed_at":"2026-07-05T11:50:02.710196Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:50:02.710196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AJmZQBEcVTuZY0enX6y8bFLsAvC++ANs09i810334AHrqBEWu6dkzoh8XXgcUvtS9ZBy0IDEdr9OkabR/eacAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:50:02.710641Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.04827","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7bde7261950479b3d02b48b4160e9b082f79fb6499e9038518363765ee2ec81e","sha256:78e6a3807cf40c698f92c8245dde115e863af9f7116e62b3243b8831a7c64b09"],"state_sha256":"ad4f5d525c26babc8ce126daf2759114a2ca30fad182d25721a71d9e8ddb71a5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FUR8vZ8wl1CXqwv8oeT+iaM/81l9djwN5q/6pFbYu9GWQGjVVgBkJ+DYty4cWmbbxSZcUfebWiEUevHaJZAkBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:53:21.093771Z","bundle_sha256":"92afa15fcf9eef8a38159f471a9efa34d85149d225fe6c0c4c925354de151a87"}}