{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:UOXZK7JXRHB3557275IOHD3S7T","short_pith_number":"pith:UOXZK7JX","canonical_record":{"source":{"id":"2607.26370","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-29T01:07:28Z","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"ad0df1be2c4a0c70192477cc4f1fa6a201fb7d607a838d330bfbee2a2ef08075","abstract_canon_sha256":"dc061fae1a004225851cf90db61b42b326c5118dd7230291d92d450668e8d571"},"schema_version":"1.0"},"canonical_sha256":"a3af957d3789c3bef7faff50e38f72fcf161e008fa0c67b4af2624694a377899","source":{"kind":"arxiv","id":"2607.26370","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.26370","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"arxiv_version","alias_value":"2607.26370v1","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.26370","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"pith_short_12","alias_value":"UOXZK7JXRHB3","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"pith_short_16","alias_value":"UOXZK7JXRHB35572","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"pith_short_8","alias_value":"UOXZK7JX","created_at":"2026-07-30T01:18:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:UOXZK7JXRHB3557275IOHD3S7T","target":"record","payload":{"canonical_record":{"source":{"id":"2607.26370","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-29T01:07:28Z","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"ad0df1be2c4a0c70192477cc4f1fa6a201fb7d607a838d330bfbee2a2ef08075","abstract_canon_sha256":"dc061fae1a004225851cf90db61b42b326c5118dd7230291d92d450668e8d571"},"schema_version":"1.0"},"canonical_sha256":"a3af957d3789c3bef7faff50e38f72fcf161e008fa0c67b4af2624694a377899","receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a3af957d3789c3bef7faff50e38f72fcf161e008fa0c67b4af2624694a377899","last_reissued_at":"2026-07-30T01:18:13.631404Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-30T01:18:13.631404Z"},"source_kind":"arxiv","source_id":"2607.26370","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":"2026-07-30T01:18:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"56WYbWAA2oJTXgugDLviR0FMdwZIPJmPqOQGeJWy2i6MfPp5OrL63LFd7jp7WTSTrDQB/5argXalwjZXgMJOBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T18:08:36.957874Z"},"content_sha256":"cfb54b356000230e56b0a090c9b1be4d57857dc47f9a354e89274e70d4be62d1","schema_version":"1.0","event_id":"sha256:cfb54b356000230e56b0a090c9b1be4d57857dc47f9a354e89274e70d4be62d1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:UOXZK7JXRHB3557275IOHD3S7T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Self-Adaptive Learning and Model Predictive Control for Tracking Unknown Dynamics with No Regret","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Atharva Navsalkar, Hongyu Zhou, Vasileios Tzoumas","submitted_at":"2026-07-29T01:07:28Z","abstract_excerpt":"We propose a self-adaptive online learning for control method for tracking unknown target dynamics. The target dynamics can exhibit switching behavior, particularly, a mixture of structured, random, and/or adversarial motion. Such challenging target tracking scenarios arise in applications of dynamic mapping, traffic control, and pursuit evasion, where robots need to track, pursue, or avoid collision with moving landmarks, objects, humans, etc., whose dynamics are unknown. Our method simultaneously learns multiple predictors from scratch, via self-supervised, one-shot, and computationally effi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.26370","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/2607.26370/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":"2026-07-30T01:18:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m6vuAF6RSKAEsO7QdwQXHF+xwbMKwG4lQ1BmLuEsSLUrJVNNlvJJ8QSvyHqhF6wCGATmjG+iAbqHtHK/+5sGAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T18:08:36.958380Z"},"content_sha256":"432b3e2e50ebe2dcdddecc1edb1fca060cfc1993714c3d470fb38907f5012c65","schema_version":"1.0","event_id":"sha256:432b3e2e50ebe2dcdddecc1edb1fca060cfc1993714c3d470fb38907f5012c65"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UOXZK7JXRHB3557275IOHD3S7T/bundle.json","state_url":"https://pith.science/pith/UOXZK7JXRHB3557275IOHD3S7T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UOXZK7JXRHB3557275IOHD3S7T/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":"2026-08-04T18:08:36Z","links":{"resolver":"https://pith.science/pith/UOXZK7JXRHB3557275IOHD3S7T","bundle":"https://pith.science/pith/UOXZK7JXRHB3557275IOHD3S7T/bundle.json","state":"https://pith.science/pith/UOXZK7JXRHB3557275IOHD3S7T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UOXZK7JXRHB3557275IOHD3S7T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:UOXZK7JXRHB3557275IOHD3S7T","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":"dc061fae1a004225851cf90db61b42b326c5118dd7230291d92d450668e8d571","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-29T01:07:28Z","title_canon_sha256":"ad0df1be2c4a0c70192477cc4f1fa6a201fb7d607a838d330bfbee2a2ef08075"},"schema_version":"1.0","source":{"id":"2607.26370","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.26370","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"arxiv_version","alias_value":"2607.26370v1","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.26370","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"pith_short_12","alias_value":"UOXZK7JXRHB3","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"pith_short_16","alias_value":"UOXZK7JXRHB35572","created_at":"2026-07-30T01:18:13Z"},{"alias_kind":"pith_short_8","alias_value":"UOXZK7JX","created_at":"2026-07-30T01:18:13Z"}],"graph_snapshots":[{"event_id":"sha256:432b3e2e50ebe2dcdddecc1edb1fca060cfc1993714c3d470fb38907f5012c65","target":"graph","created_at":"2026-07-30T01:18:13Z","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/2607.26370/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a self-adaptive online learning for control method for tracking unknown target dynamics. The target dynamics can exhibit switching behavior, particularly, a mixture of structured, random, and/or adversarial motion. Such challenging target tracking scenarios arise in applications of dynamic mapping, traffic control, and pursuit evasion, where robots need to track, pursue, or avoid collision with moving landmarks, objects, humans, etc., whose dynamics are unknown. Our method simultaneously learns multiple predictors from scratch, via self-supervised, one-shot, and computationally effi","authors_text":"Atharva Navsalkar, Hongyu Zhou, Vasileios Tzoumas","cross_cats":["cs.LG","cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-29T01:07:28Z","title":"Self-Adaptive Learning and Model Predictive Control for Tracking Unknown Dynamics with No Regret"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.26370","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:cfb54b356000230e56b0a090c9b1be4d57857dc47f9a354e89274e70d4be62d1","target":"record","created_at":"2026-07-30T01:18:13Z","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":"dc061fae1a004225851cf90db61b42b326c5118dd7230291d92d450668e8d571","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-29T01:07:28Z","title_canon_sha256":"ad0df1be2c4a0c70192477cc4f1fa6a201fb7d607a838d330bfbee2a2ef08075"},"schema_version":"1.0","source":{"id":"2607.26370","kind":"arxiv","version":1}},"canonical_sha256":"a3af957d3789c3bef7faff50e38f72fcf161e008fa0c67b4af2624694a377899","receipt":{"builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a3af957d3789c3bef7faff50e38f72fcf161e008fa0c67b4af2624694a377899","first_computed_at":"2026-07-30T01:18:13.631404Z","kind":"pith_receipt","last_reissued_at":"2026-07-30T01:18:13.631404Z","receipt_version":"0.3","signature_status":"unsigned_v0"},"source_id":"2607.26370","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cfb54b356000230e56b0a090c9b1be4d57857dc47f9a354e89274e70d4be62d1","sha256:432b3e2e50ebe2dcdddecc1edb1fca060cfc1993714c3d470fb38907f5012c65"],"state_sha256":"85e0977257546d6f56e5a67dd87460ab6974cecbb9610776706790ffa53b2c36"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zLzYrCHs2GUuxokg5Ne+DmpEJjXrQKQVFAyishGDNXTRfhjakKDtXl9qZ1zF+NxaDxZbsbCxta77YtM1zacLBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T18:08:36.961660Z","bundle_sha256":"a07136919324977f410284ddd5f2105be348451213248bc8970c05ef81d93553"}}