{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:7HTZUSQHSORH33M2HV35C6TAE2","short_pith_number":"pith:7HTZUSQH","canonical_record":{"source":{"id":"2606.17579","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-16T06:30:30Z","cross_cats_sorted":["cs.AI","cs.CL","cs.SI"],"title_canon_sha256":"7c92e943f6cecc2a623adcba9acc891adcd416e304bd0aab310c7d4985d75f70","abstract_canon_sha256":"a7045205536daeb9f9fe658f3d9a59387b980067cd3beb9206de99a9791a64b1"},"schema_version":"1.0"},"canonical_sha256":"f9e79a4a0793a27ded9a3d77d17a602689e0ba63f810755ed9fcd8e41bd06125","source":{"kind":"arxiv","id":"2606.17579","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.17579","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"arxiv_version","alias_value":"2606.17579v1","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.17579","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"pith_short_12","alias_value":"7HTZUSQHSORH","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"pith_short_16","alias_value":"7HTZUSQHSORH33M2","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"pith_short_8","alias_value":"7HTZUSQH","created_at":"2026-06-19T16:10:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:7HTZUSQHSORH33M2HV35C6TAE2","target":"record","payload":{"canonical_record":{"source":{"id":"2606.17579","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-16T06:30:30Z","cross_cats_sorted":["cs.AI","cs.CL","cs.SI"],"title_canon_sha256":"7c92e943f6cecc2a623adcba9acc891adcd416e304bd0aab310c7d4985d75f70","abstract_canon_sha256":"a7045205536daeb9f9fe658f3d9a59387b980067cd3beb9206de99a9791a64b1"},"schema_version":"1.0"},"canonical_sha256":"f9e79a4a0793a27ded9a3d77d17a602689e0ba63f810755ed9fcd8e41bd06125","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:10:16.473734Z","signature_b64":"hZQ8uaGbOV1J3oikR9xTxwASkSTqqxKHcgqLeXLBtohwQxa5ajbM5JVoH3OCdt4Z+nfv0D1rouX3ABWUOU9hBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f9e79a4a0793a27ded9a3d77d17a602689e0ba63f810755ed9fcd8e41bd06125","last_reissued_at":"2026-06-19T16:10:16.473385Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:10:16.473385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.17579","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":"2026-06-19T16:10:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x4BXTXSXbEJLbZE3eybbhOw/qKJm6gBC+KXQ8okjUqR3WptZ2pulXvoRc1gB76Vi3nlrV5Qbnr35TGZFpNG9Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T08:17:55.374522Z"},"content_sha256":"7f4b89936c693f801ec3475c067f134136726df31507a4d5a58f28339368c68b","schema_version":"1.0","event_id":"sha256:7f4b89936c693f801ec3475c067f134136726df31507a4d5a58f28339368c68b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:7HTZUSQHSORH33M2HV35C6TAE2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LLM Features Can Hurt GNNs: Concatenation Interference on Homophilous Graph Benchmarks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.SI"],"primary_cat":"cs.LG","authors_text":"Pratyusha Vemuri, Zhongyuan Wang","submitted_at":"2026-06-16T06:30:30Z","abstract_excerpt":"Adding LLM-generated node features to graph neural networks (GNNs) is widely reported to improve accuracy on standard benchmarks. We document a contrasting observation: when LLM features are introduced through pure input concatenation (rather than joint training, distillation, or prompt-conditioning), they can systematically degrade accuracy on the same homophilous benchmarks where end-to-end LLM pipelines succeed. With an MLP backbone on the Planetoid public split and bag-of-words original features, concatenating SBERT-encoded GPT-4o-mini TAPE features reduces PubMed test accuracy by -17.0 +/"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.17579","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/2606.17579/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":"2026-06-19T16:10:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O2UqOv/2u23cxusY1vL+9wu552SMgjHohXfPCJi9YXZPNIEGrDMrtO02UbWkvA/G+GtMa7iqjTzKv91ObMXrCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T08:17:55.374926Z"},"content_sha256":"640676bc54400cb007e814c31ac4638dede0f3b979883bf229e855b0e68f19a3","schema_version":"1.0","event_id":"sha256:640676bc54400cb007e814c31ac4638dede0f3b979883bf229e855b0e68f19a3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7HTZUSQHSORH33M2HV35C6TAE2/bundle.json","state_url":"https://pith.science/pith/7HTZUSQHSORH33M2HV35C6TAE2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7HTZUSQHSORH33M2HV35C6TAE2/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":"2026-07-04T08:17:55Z","links":{"resolver":"https://pith.science/pith/7HTZUSQHSORH33M2HV35C6TAE2","bundle":"https://pith.science/pith/7HTZUSQHSORH33M2HV35C6TAE2/bundle.json","state":"https://pith.science/pith/7HTZUSQHSORH33M2HV35C6TAE2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7HTZUSQHSORH33M2HV35C6TAE2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7HTZUSQHSORH33M2HV35C6TAE2","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":"a7045205536daeb9f9fe658f3d9a59387b980067cd3beb9206de99a9791a64b1","cross_cats_sorted":["cs.AI","cs.CL","cs.SI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-16T06:30:30Z","title_canon_sha256":"7c92e943f6cecc2a623adcba9acc891adcd416e304bd0aab310c7d4985d75f70"},"schema_version":"1.0","source":{"id":"2606.17579","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.17579","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"arxiv_version","alias_value":"2606.17579v1","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.17579","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"pith_short_12","alias_value":"7HTZUSQHSORH","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"pith_short_16","alias_value":"7HTZUSQHSORH33M2","created_at":"2026-06-19T16:10:16Z"},{"alias_kind":"pith_short_8","alias_value":"7HTZUSQH","created_at":"2026-06-19T16:10:16Z"}],"graph_snapshots":[{"event_id":"sha256:640676bc54400cb007e814c31ac4638dede0f3b979883bf229e855b0e68f19a3","target":"graph","created_at":"2026-06-19T16:10:16Z","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/2606.17579/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adding LLM-generated node features to graph neural networks (GNNs) is widely reported to improve accuracy on standard benchmarks. We document a contrasting observation: when LLM features are introduced through pure input concatenation (rather than joint training, distillation, or prompt-conditioning), they can systematically degrade accuracy on the same homophilous benchmarks where end-to-end LLM pipelines succeed. With an MLP backbone on the Planetoid public split and bag-of-words original features, concatenating SBERT-encoded GPT-4o-mini TAPE features reduces PubMed test accuracy by -17.0 +/","authors_text":"Pratyusha Vemuri, Zhongyuan Wang","cross_cats":["cs.AI","cs.CL","cs.SI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-16T06:30:30Z","title":"LLM Features Can Hurt GNNs: Concatenation Interference on Homophilous Graph Benchmarks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.17579","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":"sha256:7f4b89936c693f801ec3475c067f134136726df31507a4d5a58f28339368c68b","target":"record","created_at":"2026-06-19T16:10:16Z","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":"a7045205536daeb9f9fe658f3d9a59387b980067cd3beb9206de99a9791a64b1","cross_cats_sorted":["cs.AI","cs.CL","cs.SI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-16T06:30:30Z","title_canon_sha256":"7c92e943f6cecc2a623adcba9acc891adcd416e304bd0aab310c7d4985d75f70"},"schema_version":"1.0","source":{"id":"2606.17579","kind":"arxiv","version":1}},"canonical_sha256":"f9e79a4a0793a27ded9a3d77d17a602689e0ba63f810755ed9fcd8e41bd06125","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f9e79a4a0793a27ded9a3d77d17a602689e0ba63f810755ed9fcd8e41bd06125","first_computed_at":"2026-06-19T16:10:16.473385Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:10:16.473385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hZQ8uaGbOV1J3oikR9xTxwASkSTqqxKHcgqLeXLBtohwQxa5ajbM5JVoH3OCdt4Z+nfv0D1rouX3ABWUOU9hBA==","signature_status":"signed_v1","signed_at":"2026-06-19T16:10:16.473734Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.17579","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7f4b89936c693f801ec3475c067f134136726df31507a4d5a58f28339368c68b","sha256:640676bc54400cb007e814c31ac4638dede0f3b979883bf229e855b0e68f19a3"],"state_sha256":"6eb8ac2cd70f3b0b4111d1436c808b6445cf9df849a9accc4d2337aaf16a8b5b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8xX9n6wO4SVhwEzi0QmN55rZxPQsaszJYM38BUYmUVABd7/lENedtz46r/HagS/1Q2QQY/+1oRibkdrfUhNhAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-04T08:17:55.377009Z","bundle_sha256":"d3aaf49f9055abf68eac3d11e18ffbd801d21c7b7fbad53c46ac9bbed0c2ca3a"}}