{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:E6YDVBHUSACCVDQSA4DWQBTALG","short_pith_number":"pith:E6YDVBHU","canonical_record":{"source":{"id":"1809.03044","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-09-09T21:08:57Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"63d04348f5735a1cbb0de98002e56792d9d56ae001451ed5c460dfa274a981aa","abstract_canon_sha256":"210114af0e4472475722d51ee04bf512a7453e72e68816ec5c32e1902103c2b7"},"schema_version":"1.0"},"canonical_sha256":"27b03a84f490042a8e12070768066059b9673751b30a36a1ab8bd743ea618df1","source":{"kind":"arxiv","id":"1809.03044","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.03044","created_at":"2026-05-18T00:06:10Z"},{"alias_kind":"arxiv_version","alias_value":"1809.03044v1","created_at":"2026-05-18T00:06:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.03044","created_at":"2026-05-18T00:06:10Z"},{"alias_kind":"pith_short_12","alias_value":"E6YDVBHUSACC","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_16","alias_value":"E6YDVBHUSACCVDQS","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_8","alias_value":"E6YDVBHU","created_at":"2026-05-18T12:32:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:E6YDVBHUSACCVDQSA4DWQBTALG","target":"record","payload":{"canonical_record":{"source":{"id":"1809.03044","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-09-09T21:08:57Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"63d04348f5735a1cbb0de98002e56792d9d56ae001451ed5c460dfa274a981aa","abstract_canon_sha256":"210114af0e4472475722d51ee04bf512a7453e72e68816ec5c32e1902103c2b7"},"schema_version":"1.0"},"canonical_sha256":"27b03a84f490042a8e12070768066059b9673751b30a36a1ab8bd743ea618df1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:10.241453Z","signature_b64":"5bA2bsybyM6aLT7eyxF5vEg3pm5rRVFUwPF5f8/pQ5S6jjgFO9myVClXZWbmNbyh4Oz6gpUlfh0qav0Sb5xHDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27b03a84f490042a8e12070768066059b9673751b30a36a1ab8bd743ea618df1","last_reissued_at":"2026-05-18T00:06:10.240874Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:10.240874Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.03044","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":"2026-05-18T00:06:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mgXiOPK5RaCFme1AQNenGbVXpQpYDWunvWlELxfutnj5EFmmujaDNmvPIeJrHAwmjnUqIs/F0cNeLOs59u8oBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T02:38:54.455481Z"},"content_sha256":"c4adef8a3b3585650c56f0fe82239fe97bc24d5eec13464852cca74cb0f19214","schema_version":"1.0","event_id":"sha256:c4adef8a3b3585650c56f0fe82239fe97bc24d5eec13464852cca74cb0f19214"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:E6YDVBHUSACCVDQSA4DWQBTALG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"How clever is the FiLM model, and how clever can it be?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.LG"],"primary_cat":"cs.CL","authors_text":"Alexander Kuhnle, Ann Copestake, Huiyuan Xie","submitted_at":"2018-09-09T21:08:57Z","abstract_excerpt":"The FiLM model achieves close-to-perfect performance on the diagnostic CLEVR dataset and is distinguished from other such models by having a comparatively simple and easily transferable architecture. In this paper, we investigate in more detail the ability of FiLM to learn various linguistic constructions. Our main results show that (a) FiLM is not able to learn relational statements straight away except for very simple instances, (b) training on a broader set of instances as well as pretraining on simpler instance types can help alleviate these learning difficulties, (c) mixing is less robust"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.03044","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":""},"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":"2026-05-18T00:06:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yElTcGSHPYhrvgD9UIldaznjHun0cuwnyYRB6goY+TM6cqzqo9c5f+McgcMC0JGIJIldbWjJwdWBAg7zLGbkDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T02:38:54.455828Z"},"content_sha256":"fc8f046b7ae56884dca20685fb29488bc7ab14f823f211c57655a5555c73ed53","schema_version":"1.0","event_id":"sha256:fc8f046b7ae56884dca20685fb29488bc7ab14f823f211c57655a5555c73ed53"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E6YDVBHUSACCVDQSA4DWQBTALG/bundle.json","state_url":"https://pith.science/pith/E6YDVBHUSACCVDQSA4DWQBTALG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E6YDVBHUSACCVDQSA4DWQBTALG/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":"2026-06-03T02:38:54Z","links":{"resolver":"https://pith.science/pith/E6YDVBHUSACCVDQSA4DWQBTALG","bundle":"https://pith.science/pith/E6YDVBHUSACCVDQSA4DWQBTALG/bundle.json","state":"https://pith.science/pith/E6YDVBHUSACCVDQSA4DWQBTALG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E6YDVBHUSACCVDQSA4DWQBTALG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:E6YDVBHUSACCVDQSA4DWQBTALG","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":"210114af0e4472475722d51ee04bf512a7453e72e68816ec5c32e1902103c2b7","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-09-09T21:08:57Z","title_canon_sha256":"63d04348f5735a1cbb0de98002e56792d9d56ae001451ed5c460dfa274a981aa"},"schema_version":"1.0","source":{"id":"1809.03044","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.03044","created_at":"2026-05-18T00:06:10Z"},{"alias_kind":"arxiv_version","alias_value":"1809.03044v1","created_at":"2026-05-18T00:06:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.03044","created_at":"2026-05-18T00:06:10Z"},{"alias_kind":"pith_short_12","alias_value":"E6YDVBHUSACC","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_16","alias_value":"E6YDVBHUSACCVDQS","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_8","alias_value":"E6YDVBHU","created_at":"2026-05-18T12:32:19Z"}],"graph_snapshots":[{"event_id":"sha256:fc8f046b7ae56884dca20685fb29488bc7ab14f823f211c57655a5555c73ed53","target":"graph","created_at":"2026-05-18T00:06:10Z","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"},"paper":{"abstract_excerpt":"The FiLM model achieves close-to-perfect performance on the diagnostic CLEVR dataset and is distinguished from other such models by having a comparatively simple and easily transferable architecture. In this paper, we investigate in more detail the ability of FiLM to learn various linguistic constructions. Our main results show that (a) FiLM is not able to learn relational statements straight away except for very simple instances, (b) training on a broader set of instances as well as pretraining on simpler instance types can help alleviate these learning difficulties, (c) mixing is less robust","authors_text":"Alexander Kuhnle, Ann Copestake, Huiyuan Xie","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-09-09T21:08:57Z","title":"How clever is the FiLM model, and how clever can it be?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.03044","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:c4adef8a3b3585650c56f0fe82239fe97bc24d5eec13464852cca74cb0f19214","target":"record","created_at":"2026-05-18T00:06:10Z","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":"210114af0e4472475722d51ee04bf512a7453e72e68816ec5c32e1902103c2b7","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-09-09T21:08:57Z","title_canon_sha256":"63d04348f5735a1cbb0de98002e56792d9d56ae001451ed5c460dfa274a981aa"},"schema_version":"1.0","source":{"id":"1809.03044","kind":"arxiv","version":1}},"canonical_sha256":"27b03a84f490042a8e12070768066059b9673751b30a36a1ab8bd743ea618df1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27b03a84f490042a8e12070768066059b9673751b30a36a1ab8bd743ea618df1","first_computed_at":"2026-05-18T00:06:10.240874Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:06:10.240874Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5bA2bsybyM6aLT7eyxF5vEg3pm5rRVFUwPF5f8/pQ5S6jjgFO9myVClXZWbmNbyh4Oz6gpUlfh0qav0Sb5xHDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:06:10.241453Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.03044","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4adef8a3b3585650c56f0fe82239fe97bc24d5eec13464852cca74cb0f19214","sha256:fc8f046b7ae56884dca20685fb29488bc7ab14f823f211c57655a5555c73ed53"],"state_sha256":"bd7bb19f7e1440fa9f2216c9828d7be4900c3a535ce567862b445291e1dc5ab6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T9LtfwJm4wxm+SI2xIWgAE+pJBkgIAYKEos5gNJBoNzQxC0ws5FhWpYRnunHMNrQQzCTnRXX29ULDpdwkHKFBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T02:38:54.457799Z","bundle_sha256":"17ca8d5b621d5fcd4798c7c2bc0b2af5b7649a677a950f7a5f2ac503f19cca16"}}