{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:GDPAH73QL5EPOEKXZ3SRGGFRMB","short_pith_number":"pith:GDPAH73Q","canonical_record":{"source":{"id":"2505.15304","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-21T09:35:12Z","cross_cats_sorted":[],"title_canon_sha256":"4c2f253d4613b198f526fd3cab30eb9cd33c65418ce3d65c6f78c8a7664c61fc","abstract_canon_sha256":"ff0127077ab13dcf6b89a5763cbae62dbe1f9c55b209f3b80379183b9ce596e6"},"schema_version":"1.0"},"canonical_sha256":"30de03ff705f48f71157cee51318b1604bb280704d84e2f951e555905b211ca4","source":{"kind":"arxiv","id":"2505.15304","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.15304","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"arxiv_version","alias_value":"2505.15304v2","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.15304","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_12","alias_value":"GDPAH73QL5EP","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_16","alias_value":"GDPAH73QL5EPOEKX","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_8","alias_value":"GDPAH73Q","created_at":"2026-07-05T11:12:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:GDPAH73QL5EPOEKXZ3SRGGFRMB","target":"record","payload":{"canonical_record":{"source":{"id":"2505.15304","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-21T09:35:12Z","cross_cats_sorted":[],"title_canon_sha256":"4c2f253d4613b198f526fd3cab30eb9cd33c65418ce3d65c6f78c8a7664c61fc","abstract_canon_sha256":"ff0127077ab13dcf6b89a5763cbae62dbe1f9c55b209f3b80379183b9ce596e6"},"schema_version":"1.0"},"canonical_sha256":"30de03ff705f48f71157cee51318b1604bb280704d84e2f951e555905b211ca4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:12:32.512633Z","signature_b64":"wXlK0+57nr9X5dcKoEgdeY1sEQ0vYnJ8fIOaHAJVeubiBoWfFaA7b8iI046uzp6AWueTSlph+UmDtOzXQseICQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30de03ff705f48f71157cee51318b1604bb280704d84e2f951e555905b211ca4","last_reissued_at":"2026-07-05T11:12:32.512052Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:12:32.512052Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.15304","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:12:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zaNqVTftsZj4EK0IaIpKndH//0Vc4WSeHbe8tu0bkdK/UW2/UQnJ1eVpu9CCLxGEMvViQZIoEBtLsrHHvUm6DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:53:25.942249Z"},"content_sha256":"78821a889667e3362d8954081981876e2350a19cfd103ece7cdadaf2fb7cf191","schema_version":"1.0","event_id":"sha256:78821a889667e3362d8954081981876e2350a19cfd103ece7cdadaf2fb7cf191"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:GDPAH73QL5EPOEKXZ3SRGGFRMB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Byeongwook Jeon, Hyungmin Kim, Jungwook Choi, JuYoung Yang, Sangwoo Kim, Seongmin Park, Wonseok Jeon, Yoonseon Oh","submitted_at":"2025-05-21T09:35:12Z","abstract_excerpt":"Deep neural network (DNN)-based policy models, such as vision-language-action (VLA) models, excel at automating complex decision-making from multi-modal inputs. However, scaling these models greatly increases computational overhead, complicating deployment in resource-constrained settings like robot manipulation and autonomous driving. To address this, we propose Saliency-Aware Quantized Imitation Learning (SQIL), which combines quantization-aware training with a selective loss-weighting strategy for mission-critical states. By identifying these states via saliency scores and emphasizing them "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.15304","kind":"arxiv","version":2},"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/2505.15304/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":"2026-07-05T11:12:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EHfcqEJExYqnLEsgn6B3R5HqKPoSrZ4kMb6BOWhT7Dw1OWCNcDa9fjFT16Rm/8lAmNr+DV3NuhcJePfGYLnxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:53:25.942826Z"},"content_sha256":"ed9f01b3727c1a6fb9e2b5d72db9f8593a30ab3c647bc383a391f33ee4c5c366","schema_version":"1.0","event_id":"sha256:ed9f01b3727c1a6fb9e2b5d72db9f8593a30ab3c647bc383a391f33ee4c5c366"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GDPAH73QL5EPOEKXZ3SRGGFRMB/bundle.json","state_url":"https://pith.science/pith/GDPAH73QL5EPOEKXZ3SRGGFRMB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GDPAH73QL5EPOEKXZ3SRGGFRMB/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":"2026-08-05T15:53:25Z","links":{"resolver":"https://pith.science/pith/GDPAH73QL5EPOEKXZ3SRGGFRMB","bundle":"https://pith.science/pith/GDPAH73QL5EPOEKXZ3SRGGFRMB/bundle.json","state":"https://pith.science/pith/GDPAH73QL5EPOEKXZ3SRGGFRMB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GDPAH73QL5EPOEKXZ3SRGGFRMB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GDPAH73QL5EPOEKXZ3SRGGFRMB","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":"ff0127077ab13dcf6b89a5763cbae62dbe1f9c55b209f3b80379183b9ce596e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-21T09:35:12Z","title_canon_sha256":"4c2f253d4613b198f526fd3cab30eb9cd33c65418ce3d65c6f78c8a7664c61fc"},"schema_version":"1.0","source":{"id":"2505.15304","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.15304","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"arxiv_version","alias_value":"2505.15304v2","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.15304","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_12","alias_value":"GDPAH73QL5EP","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_16","alias_value":"GDPAH73QL5EPOEKX","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_8","alias_value":"GDPAH73Q","created_at":"2026-07-05T11:12:32Z"}],"graph_snapshots":[{"event_id":"sha256:ed9f01b3727c1a6fb9e2b5d72db9f8593a30ab3c647bc383a391f33ee4c5c366","target":"graph","created_at":"2026-07-05T11:12:32Z","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/2505.15304/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep neural network (DNN)-based policy models, such as vision-language-action (VLA) models, excel at automating complex decision-making from multi-modal inputs. However, scaling these models greatly increases computational overhead, complicating deployment in resource-constrained settings like robot manipulation and autonomous driving. To address this, we propose Saliency-Aware Quantized Imitation Learning (SQIL), which combines quantization-aware training with a selective loss-weighting strategy for mission-critical states. By identifying these states via saliency scores and emphasizing them ","authors_text":"Byeongwook Jeon, Hyungmin Kim, Jungwook Choi, JuYoung Yang, Sangwoo Kim, Seongmin Park, Wonseok Jeon, Yoonseon Oh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-21T09:35:12Z","title":"Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.15304","kind":"arxiv","version":2},"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":"sha256:78821a889667e3362d8954081981876e2350a19cfd103ece7cdadaf2fb7cf191","target":"record","created_at":"2026-07-05T11:12:32Z","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":"ff0127077ab13dcf6b89a5763cbae62dbe1f9c55b209f3b80379183b9ce596e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-21T09:35:12Z","title_canon_sha256":"4c2f253d4613b198f526fd3cab30eb9cd33c65418ce3d65c6f78c8a7664c61fc"},"schema_version":"1.0","source":{"id":"2505.15304","kind":"arxiv","version":2}},"canonical_sha256":"30de03ff705f48f71157cee51318b1604bb280704d84e2f951e555905b211ca4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30de03ff705f48f71157cee51318b1604bb280704d84e2f951e555905b211ca4","first_computed_at":"2026-07-05T11:12:32.512052Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:12:32.512052Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wXlK0+57nr9X5dcKoEgdeY1sEQ0vYnJ8fIOaHAJVeubiBoWfFaA7b8iI046uzp6AWueTSlph+UmDtOzXQseICQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:12:32.512633Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.15304","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:78821a889667e3362d8954081981876e2350a19cfd103ece7cdadaf2fb7cf191","sha256:ed9f01b3727c1a6fb9e2b5d72db9f8593a30ab3c647bc383a391f33ee4c5c366"],"state_sha256":"08bdc728aa3079e6b350fa26f68317b27361ea06eb302cd89083635ea7183911"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cGG5Pm9WuVZN9ghlCE+HtE9E53DJ8VfYOhrcHA68yGYReluqfpQCGgCFxP+ctMp5YfMtUeTVdcwdEJfLKajnBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T15:53:25.947273Z","bundle_sha256":"a6a2776406e710134aef56913a2713a77c91d74661fd18540b77e47fbbd61118"}}