{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ZNCB4LCZBVFWSARH7XUDMG33WG","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":"ee0f86293b9d42778d78c7e31332bcab425a89ee4701f320486b6e504757da68","cross_cats_sorted":["cs.AI","math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-23T20:02:51Z","title_canon_sha256":"10b7ec90a0ea9c730009d7d15905eb6d39855934db7e0c0bde4afd93e4997593"},"schema_version":"1.0","source":{"id":"2606.25127","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25127","created_at":"2026-06-25T00:18:18Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25127v1","created_at":"2026-06-25T00:18:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25127","created_at":"2026-06-25T00:18:18Z"},{"alias_kind":"pith_short_12","alias_value":"ZNCB4LCZBVFW","created_at":"2026-06-25T00:18:18Z"},{"alias_kind":"pith_short_16","alias_value":"ZNCB4LCZBVFWSARH","created_at":"2026-06-25T00:18:18Z"},{"alias_kind":"pith_short_8","alias_value":"ZNCB4LCZ","created_at":"2026-06-25T00:18:18Z"}],"graph_snapshots":[{"event_id":"sha256:52b9a185436e7665f2d9db0f8451ebf4d24d5f6ba7d2f3068d585bffe32ff82b","target":"graph","created_at":"2026-06-25T00:18:18Z","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/2606.25127/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We investigate how reward design shapes the internal attention patterns of reinforcement learning agents trained for autonomous driving. Using three Perceiver-based agents that share identical architectures and training data but differ only in their reward configurations$\\unicode{x2014}$ranging from basic violation penalties to continuous proximity penalties$\\unicode{x2014}$we analyze cross-attention allocation across 50 real-world scenarios from the Waymo Open Motion Dataset. A central methodological finding is that na\\\"ive pooling of timesteps across episodes substantially underestimates the","authors_text":"Ahmed Djalal Hacini, Aissa Boulmerka, Mohamed Benabdelouahad, Nadir Farhi","cross_cats":["cs.AI","math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-23T20:02:51Z","title":"Reward-Conditioned Attention: How Reward Design Shapes What Autonomous Driving Agents See"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25127","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":"sha256:86ec8c5346e1d812fdb95317a074c4b8f7f2369f52a14ec80070362d982caa9e","target":"record","created_at":"2026-06-25T00:18:18Z","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":"ee0f86293b9d42778d78c7e31332bcab425a89ee4701f320486b6e504757da68","cross_cats_sorted":["cs.AI","math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-23T20:02:51Z","title_canon_sha256":"10b7ec90a0ea9c730009d7d15905eb6d39855934db7e0c0bde4afd93e4997593"},"schema_version":"1.0","source":{"id":"2606.25127","kind":"arxiv","version":1}},"canonical_sha256":"cb441e2c590d4b690227fde8361b7bb1bb152c367ac78cd73c5ed137a88f839d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb441e2c590d4b690227fde8361b7bb1bb152c367ac78cd73c5ed137a88f839d","first_computed_at":"2026-06-25T00:18:18.790414Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-25T00:18:18.790414Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+3AVd5wTPA3cGfxQZm33+Rm1xoEL0uYFTa8TM8MmgxwnjKWraL9awCPd9h0MoKC4IIj9UpP2JjKoLsZZUbPCBA==","signature_status":"signed_v1","signed_at":"2026-06-25T00:18:18.790818Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.25127","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:86ec8c5346e1d812fdb95317a074c4b8f7f2369f52a14ec80070362d982caa9e","sha256:52b9a185436e7665f2d9db0f8451ebf4d24d5f6ba7d2f3068d585bffe32ff82b"],"state_sha256":"deaab01f47c2c6dbddb48100a6b4168063f7c0f7964fb5476db103a643fd17a4"}