{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:C5IJPVETCAQSBDPPWE6SYRPIMO","short_pith_number":"pith:C5IJPVET","canonical_record":{"source":{"id":"2607.05705","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T23:59:19Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"dce0e799221ff7a13f1cefded2b3c93b6252a60929a3fbe5d3eebd7f92b5790f","abstract_canon_sha256":"1dc62135c6a48883409522bb33d6205392a81af27ebd4c07b7ef82e2c9ce8fc9"},"schema_version":"1.0"},"canonical_sha256":"175097d4931021208defb13d2c45e863b8b477dd5d85cc5ea418b7dcccca321c","source":{"kind":"arxiv","id":"2607.05705","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.05705","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"2607.05705v1","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.05705","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"C5IJPVETCAQS","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"pith_short_16","alias_value":"C5IJPVETCAQSBDPP","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"pith_short_8","alias_value":"C5IJPVET","created_at":"2026-07-08T01:18:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:C5IJPVETCAQSBDPPWE6SYRPIMO","target":"record","payload":{"canonical_record":{"source":{"id":"2607.05705","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T23:59:19Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"dce0e799221ff7a13f1cefded2b3c93b6252a60929a3fbe5d3eebd7f92b5790f","abstract_canon_sha256":"1dc62135c6a48883409522bb33d6205392a81af27ebd4c07b7ef82e2c9ce8fc9"},"schema_version":"1.0"},"canonical_sha256":"175097d4931021208defb13d2c45e863b8b477dd5d85cc5ea418b7dcccca321c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-08T01:18:41.987911Z","signature_b64":"GqdaINzBz6qNp0iINseb5iCbu2KIkc/3orXxTAWCo7sckyD4f3aMd/lCA23var1cABbgDJHrfRu8EDNqFCGqCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"175097d4931021208defb13d2c45e863b8b477dd5d85cc5ea418b7dcccca321c","last_reissued_at":"2026-07-08T01:18:41.987437Z","signature_status":"signed_v1","first_computed_at":"2026-07-08T01:18:41.987437Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.05705","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":"2026-07-08T01:18:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tk4wHZKzMRTms8kW6ZRVBsA2WxzilJWhSmM4qHkBAtXYOgwbzS1ii1XVOlVv+MzhGPoF2YnPMFHu0dg7oE/fAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:37:03.162768Z"},"content_sha256":"f73e76448e55c112727618208c59eab9b360382c7f623be02e8b99d8d332e9fc","schema_version":"1.0","event_id":"sha256:f73e76448e55c112727618208c59eab9b360382c7f623be02e8b99d8d332e9fc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:C5IJPVETCAQSBDPPWE6SYRPIMO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IMR: Iterative Mode-World Weighted Regression for Multi-Agent Trajectory Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.LG"],"primary_cat":"cs.RO","authors_text":"Honglin Wang, Shiyao Pan, Yun-Fu Liu","submitted_at":"2026-07-06T23:59:19Z","abstract_excerpt":"Multi-agent motion prediction is essential for automated vehicles to understand the intentions of surrounding vehicles. However, previous prediction-based and anchor-based methods have limitations in mode diversity and prediction accuracy, respectively. These limitations may cause inadequate safety assessments and behavioral deviations in automated vehicles. To address this issue, a mode-world weighted regression loss is proposed to bridge the gap between these features. Specifically, this approach mitigates mode collapse while simultaneously improving world ranking and top-1 confidence. Furth"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.05705","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/2607.05705/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":"2026-07-08T01:18:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"trwIpRUbEaRpvVv9c0k5oY+OULW1C32kxBQBriq3YHKp4IzQryklCf+OA7D6MT84zVV7TIOSofK7DMRBbecsDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:37:03.163636Z"},"content_sha256":"cbe41a755a4220db69f8aa6f47be3944ec749d2cae7da8076f106cd09c5f8f9d","schema_version":"1.0","event_id":"sha256:cbe41a755a4220db69f8aa6f47be3944ec749d2cae7da8076f106cd09c5f8f9d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C5IJPVETCAQSBDPPWE6SYRPIMO/bundle.json","state_url":"https://pith.science/pith/C5IJPVETCAQSBDPPWE6SYRPIMO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C5IJPVETCAQSBDPPWE6SYRPIMO/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":"2026-08-04T22:37:03Z","links":{"resolver":"https://pith.science/pith/C5IJPVETCAQSBDPPWE6SYRPIMO","bundle":"https://pith.science/pith/C5IJPVETCAQSBDPPWE6SYRPIMO/bundle.json","state":"https://pith.science/pith/C5IJPVETCAQSBDPPWE6SYRPIMO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C5IJPVETCAQSBDPPWE6SYRPIMO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:C5IJPVETCAQSBDPPWE6SYRPIMO","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":"1dc62135c6a48883409522bb33d6205392a81af27ebd4c07b7ef82e2c9ce8fc9","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T23:59:19Z","title_canon_sha256":"dce0e799221ff7a13f1cefded2b3c93b6252a60929a3fbe5d3eebd7f92b5790f"},"schema_version":"1.0","source":{"id":"2607.05705","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.05705","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"2607.05705v1","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.05705","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"C5IJPVETCAQS","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"pith_short_16","alias_value":"C5IJPVETCAQSBDPP","created_at":"2026-07-08T01:18:41Z"},{"alias_kind":"pith_short_8","alias_value":"C5IJPVET","created_at":"2026-07-08T01:18:41Z"}],"graph_snapshots":[{"event_id":"sha256:cbe41a755a4220db69f8aa6f47be3944ec749d2cae7da8076f106cd09c5f8f9d","target":"graph","created_at":"2026-07-08T01:18:41Z","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/2607.05705/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-agent motion prediction is essential for automated vehicles to understand the intentions of surrounding vehicles. However, previous prediction-based and anchor-based methods have limitations in mode diversity and prediction accuracy, respectively. These limitations may cause inadequate safety assessments and behavioral deviations in automated vehicles. To address this issue, a mode-world weighted regression loss is proposed to bridge the gap between these features. Specifically, this approach mitigates mode collapse while simultaneously improving world ranking and top-1 confidence. Furth","authors_text":"Honglin Wang, Shiyao Pan, Yun-Fu Liu","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T23:59:19Z","title":"IMR: Iterative Mode-World Weighted Regression for Multi-Agent Trajectory Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.05705","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:f73e76448e55c112727618208c59eab9b360382c7f623be02e8b99d8d332e9fc","target":"record","created_at":"2026-07-08T01:18:41Z","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":"1dc62135c6a48883409522bb33d6205392a81af27ebd4c07b7ef82e2c9ce8fc9","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T23:59:19Z","title_canon_sha256":"dce0e799221ff7a13f1cefded2b3c93b6252a60929a3fbe5d3eebd7f92b5790f"},"schema_version":"1.0","source":{"id":"2607.05705","kind":"arxiv","version":1}},"canonical_sha256":"175097d4931021208defb13d2c45e863b8b477dd5d85cc5ea418b7dcccca321c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"175097d4931021208defb13d2c45e863b8b477dd5d85cc5ea418b7dcccca321c","first_computed_at":"2026-07-08T01:18:41.987437Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-08T01:18:41.987437Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GqdaINzBz6qNp0iINseb5iCbu2KIkc/3orXxTAWCo7sckyD4f3aMd/lCA23var1cABbgDJHrfRu8EDNqFCGqCA==","signature_status":"signed_v1","signed_at":"2026-07-08T01:18:41.987911Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.05705","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f73e76448e55c112727618208c59eab9b360382c7f623be02e8b99d8d332e9fc","sha256:cbe41a755a4220db69f8aa6f47be3944ec749d2cae7da8076f106cd09c5f8f9d"],"state_sha256":"321fb0113e978263f80f7cf3070a938c9237a98da5ab0ff96809e78cdb5f40e9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n/SP1ocMdSChWyhu9JJ/7EEVUiPgL9LFhjCwEvWhygodS2zH6rY5+92g72rGykekXe43twx6HAdvJTTsCgvzDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T22:37:03.169037Z","bundle_sha256":"f054934af3c8927c3ae1e131d80268182692b2d8000a30eabdd8379bd630bca6"}}