{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ICYFH7AL2AC4DXB24PURJNFIUN","short_pith_number":"pith:ICYFH7AL","canonical_record":{"source":{"id":"2004.11054","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-23T10:22:16Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"e24b6a6bd566787c762553e54001fb29057d55f38fc8cdadd72883139f1a1d68","abstract_canon_sha256":"e926a9a1c4dfc3e63739136948f9bc6ae45fa1ef444210af2c49871c69a76fb5"},"schema_version":"1.0"},"canonical_sha256":"40b053fc0bd005c1dc3ae3e914b4a8a35fdda659280837067dab709c76c3edc2","source":{"kind":"arxiv","id":"2004.11054","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.11054","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"2004.11054v2","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.11054","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"ICYFH7AL2AC4","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"pith_short_16","alias_value":"ICYFH7AL2AC4DXB2","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"pith_short_8","alias_value":"ICYFH7AL","created_at":"2026-07-05T01:26:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ICYFH7AL2AC4DXB24PURJNFIUN","target":"record","payload":{"canonical_record":{"source":{"id":"2004.11054","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-23T10:22:16Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"e24b6a6bd566787c762553e54001fb29057d55f38fc8cdadd72883139f1a1d68","abstract_canon_sha256":"e926a9a1c4dfc3e63739136948f9bc6ae45fa1ef444210af2c49871c69a76fb5"},"schema_version":"1.0"},"canonical_sha256":"40b053fc0bd005c1dc3ae3e914b4a8a35fdda659280837067dab709c76c3edc2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:26:51.717373Z","signature_b64":"EuRx+DVHs8HASANLd5fIUI6tYTMZNdEfa3MKUfhWIB33SYj9t2fmBQD3yvwhtHznpH2M8PohGGTRbIBnBIHqDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40b053fc0bd005c1dc3ae3e914b4a8a35fdda659280837067dab709c76c3edc2","last_reissued_at":"2026-07-05T01:26:51.716834Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:26:51.716834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.11054","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":"2026-07-05T01:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1sJrVTunX5oTwx0TsV+hoI6kxqumGjgWiDPKbcWgrmyTj1TAl2XiuFO5PxgOhOWVk9+NE+a8+DVjkcf14w/aDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:01:36.299437Z"},"content_sha256":"a633e93790eab3fe21dacd5f8755cd456fb0b2e61703c5078375ea7c7b3334b2","schema_version":"1.0","event_id":"sha256:a633e93790eab3fe21dacd5f8755cd456fb0b2e61703c5078375ea7c7b3334b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ICYFH7AL2AC4DXB24PURJNFIUN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Dialog Policies from Weak Demonstrations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"cs.CL","authors_text":"Gabriel Gordon-Hall, Philip John Gorinski, Shay B. Cohen","submitted_at":"2020-04-23T10:22:16Z","abstract_excerpt":"Deep reinforcement learning is a promising approach to training a dialog manager, but current methods struggle with the large state and action spaces of multi-domain dialog systems. Building upon Deep Q-learning from Demonstrations (DQfD), an algorithm that scores highly in difficult Atari games, we leverage dialog data to guide the agent to successfully respond to a user's requests. We make progressively fewer assumptions about the data needed, using labeled, reduced-labeled, and even unlabeled data to train expert demonstrators. We introduce Reinforced Fine-tune Learning, an extension to DQf"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.11054","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/2004.11054/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":"2026-07-05T01:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y0YCmddq1Oc80gOXiD2pYgW34iJA/wD45R9M7Q+NnKBo/dZFx1D50Kn067VZgq3Xu2cJKI2+HUevMdPqWayRCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:01:36.299822Z"},"content_sha256":"9e88771326f5281c2e1d92cafd1a6f1162c2a46690f6d34c8c958a8ba8775a43","schema_version":"1.0","event_id":"sha256:9e88771326f5281c2e1d92cafd1a6f1162c2a46690f6d34c8c958a8ba8775a43"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ICYFH7AL2AC4DXB24PURJNFIUN/bundle.json","state_url":"https://pith.science/pith/ICYFH7AL2AC4DXB24PURJNFIUN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ICYFH7AL2AC4DXB24PURJNFIUN/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":"2026-07-06T17:01:36Z","links":{"resolver":"https://pith.science/pith/ICYFH7AL2AC4DXB24PURJNFIUN","bundle":"https://pith.science/pith/ICYFH7AL2AC4DXB24PURJNFIUN/bundle.json","state":"https://pith.science/pith/ICYFH7AL2AC4DXB24PURJNFIUN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ICYFH7AL2AC4DXB24PURJNFIUN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ICYFH7AL2AC4DXB24PURJNFIUN","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":"e926a9a1c4dfc3e63739136948f9bc6ae45fa1ef444210af2c49871c69a76fb5","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-23T10:22:16Z","title_canon_sha256":"e24b6a6bd566787c762553e54001fb29057d55f38fc8cdadd72883139f1a1d68"},"schema_version":"1.0","source":{"id":"2004.11054","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.11054","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"2004.11054v2","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.11054","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"ICYFH7AL2AC4","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"pith_short_16","alias_value":"ICYFH7AL2AC4DXB2","created_at":"2026-07-05T01:26:51Z"},{"alias_kind":"pith_short_8","alias_value":"ICYFH7AL","created_at":"2026-07-05T01:26:51Z"}],"graph_snapshots":[{"event_id":"sha256:9e88771326f5281c2e1d92cafd1a6f1162c2a46690f6d34c8c958a8ba8775a43","target":"graph","created_at":"2026-07-05T01:26:51Z","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/2004.11054/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep reinforcement learning is a promising approach to training a dialog manager, but current methods struggle with the large state and action spaces of multi-domain dialog systems. Building upon Deep Q-learning from Demonstrations (DQfD), an algorithm that scores highly in difficult Atari games, we leverage dialog data to guide the agent to successfully respond to a user's requests. We make progressively fewer assumptions about the data needed, using labeled, reduced-labeled, and even unlabeled data to train expert demonstrators. We introduce Reinforced Fine-tune Learning, an extension to DQf","authors_text":"Gabriel Gordon-Hall, Philip John Gorinski, Shay B. Cohen","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-23T10:22:16Z","title":"Learning Dialog Policies from Weak Demonstrations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.11054","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:a633e93790eab3fe21dacd5f8755cd456fb0b2e61703c5078375ea7c7b3334b2","target":"record","created_at":"2026-07-05T01:26:51Z","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":"e926a9a1c4dfc3e63739136948f9bc6ae45fa1ef444210af2c49871c69a76fb5","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-23T10:22:16Z","title_canon_sha256":"e24b6a6bd566787c762553e54001fb29057d55f38fc8cdadd72883139f1a1d68"},"schema_version":"1.0","source":{"id":"2004.11054","kind":"arxiv","version":2}},"canonical_sha256":"40b053fc0bd005c1dc3ae3e914b4a8a35fdda659280837067dab709c76c3edc2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40b053fc0bd005c1dc3ae3e914b4a8a35fdda659280837067dab709c76c3edc2","first_computed_at":"2026-07-05T01:26:51.716834Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:26:51.716834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EuRx+DVHs8HASANLd5fIUI6tYTMZNdEfa3MKUfhWIB33SYj9t2fmBQD3yvwhtHznpH2M8PohGGTRbIBnBIHqDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:26:51.717373Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.11054","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a633e93790eab3fe21dacd5f8755cd456fb0b2e61703c5078375ea7c7b3334b2","sha256:9e88771326f5281c2e1d92cafd1a6f1162c2a46690f6d34c8c958a8ba8775a43"],"state_sha256":"c141abca05944e6f15404b9debd1df02096be8ba2076c529a6d233593b04ae96"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rtsl9fSAHfM5KV3hSb6WtHpGjgGkooTw/ltX9Q211/gwKVwhhHJceG6g1XVYKVi3qulxUwifuzleThL2+IzOCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:01:36.301769Z","bundle_sha256":"3c6c3f6c449c0ba3a508ceea7046815657201c3a465f8a12f23d16de0ee8f02c"}}