{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:7BYVYXIW6FXAYZ3R5VCVCNNW2A","short_pith_number":"pith:7BYVYXIW","canonical_record":{"source":{"id":"2605.16650","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-15T21:39:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3d789d5a5f4c1989d31bf4c0d27d005715b1f9a680ec90a9df8530274e8c2721","abstract_canon_sha256":"8c31cd2642ae2f3830726a2b3abb4608c6dee3f1f4ee2e7f1f1c99e18df580d3"},"schema_version":"1.0"},"canonical_sha256":"f8715c5d16f16e0c6771ed455135b6d01209e9c03ad9c1cd5443009906dc6a57","source":{"kind":"arxiv","id":"2605.16650","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16650","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16650v1","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16650","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"pith_short_12","alias_value":"7BYVYXIW6FXA","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"pith_short_16","alias_value":"7BYVYXIW6FXAYZ3R","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"pith_short_8","alias_value":"7BYVYXIW","created_at":"2026-05-20T00:02:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:7BYVYXIW6FXAYZ3R5VCVCNNW2A","target":"record","payload":{"canonical_record":{"source":{"id":"2605.16650","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-15T21:39:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3d789d5a5f4c1989d31bf4c0d27d005715b1f9a680ec90a9df8530274e8c2721","abstract_canon_sha256":"8c31cd2642ae2f3830726a2b3abb4608c6dee3f1f4ee2e7f1f1c99e18df580d3"},"schema_version":"1.0"},"canonical_sha256":"f8715c5d16f16e0c6771ed455135b6d01209e9c03ad9c1cd5443009906dc6a57","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:02:34.318634Z","signature_b64":"wa7ouA4e/Y4Mxq/NIzmIU88tgAN/3NqROVOvqF4rVv64/73BYwQx5k2UwGFvCD5AY4Rj+N/NHyavhHNx64SMDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f8715c5d16f16e0c6771ed455135b6d01209e9c03ad9c1cd5443009906dc6a57","last_reissued_at":"2026-05-20T00:02:34.317938Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:02:34.317938Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.16650","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":"2026-05-20T00:02:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1KKEEyLif6B+lNhlitRSdOb707/hxT971nPykiDNSib2kTBfek4dyZXjHNqRA17a4pUKtQBfSZ9IBeIi2W88Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T19:40:11.836683Z"},"content_sha256":"de3acd5bad4ece7e18ddcf83e1249e4c302da78b20a96742709cfe576f6b5db3","schema_version":"1.0","event_id":"sha256:de3acd5bad4ece7e18ddcf83e1249e4c302da78b20a96742709cfe576f6b5db3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:7BYVYXIW6FXAYZ3R5VCVCNNW2A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SKG-Eval: Stateful Evaluation of Multi-Turn Dialogue via Incremental Semantic Knowledge Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Avijit Shil, Suman Samui","submitted_at":"2026-05-15T21:39:48Z","abstract_excerpt":"Evaluating multi-turn dialogue systems remains challenging because response quality depends not only on the current prompt, but also on previously established entities, claims, and conversational commitments. Existing automatic evaluators, including LLM-as-a-judge frameworks and embedding-based metrics, largely rely on flat or turn-isolated representations, making them less effective at detecting long-range issues such as contradiction, topic drift, and entity inconsistency. To address this, we propose SKG-Eval, a quasi-deterministic and interpretable framework that models dialogue as an evolv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16650","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/2605.16650/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"claim_evidence","ran_at":"2026-05-19T19:01:56.406112Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T18:33:26.525416Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"a58dcd43f852d306b578b1b8e9fdf21d4a3278eeefa2b679f943d15dcabe69e1"},"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":"2026-05-20T00:02:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"em13Kb7KF0ByFs5uYy84dqCIMItAaGR5Ax4hVhNiQ/MnHEjvS+f6d7lAKGV7EEedRxR0uT+mDcsC+EPfJW78AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T19:40:11.837537Z"},"content_sha256":"0a3faac5f3e652cf89c1275b28de6512f1ab41c0253bc918d45c5e6d9430d2b9","schema_version":"1.0","event_id":"sha256:0a3faac5f3e652cf89c1275b28de6512f1ab41c0253bc918d45c5e6d9430d2b9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7BYVYXIW6FXAYZ3R5VCVCNNW2A/bundle.json","state_url":"https://pith.science/pith/7BYVYXIW6FXAYZ3R5VCVCNNW2A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7BYVYXIW6FXAYZ3R5VCVCNNW2A/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":"2026-06-11T19:40:11Z","links":{"resolver":"https://pith.science/pith/7BYVYXIW6FXAYZ3R5VCVCNNW2A","bundle":"https://pith.science/pith/7BYVYXIW6FXAYZ3R5VCVCNNW2A/bundle.json","state":"https://pith.science/pith/7BYVYXIW6FXAYZ3R5VCVCNNW2A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7BYVYXIW6FXAYZ3R5VCVCNNW2A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7BYVYXIW6FXAYZ3R5VCVCNNW2A","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":"8c31cd2642ae2f3830726a2b3abb4608c6dee3f1f4ee2e7f1f1c99e18df580d3","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-15T21:39:48Z","title_canon_sha256":"3d789d5a5f4c1989d31bf4c0d27d005715b1f9a680ec90a9df8530274e8c2721"},"schema_version":"1.0","source":{"id":"2605.16650","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16650","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16650v1","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16650","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"pith_short_12","alias_value":"7BYVYXIW6FXA","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"pith_short_16","alias_value":"7BYVYXIW6FXAYZ3R","created_at":"2026-05-20T00:02:34Z"},{"alias_kind":"pith_short_8","alias_value":"7BYVYXIW","created_at":"2026-05-20T00:02:34Z"}],"graph_snapshots":[{"event_id":"sha256:0a3faac5f3e652cf89c1275b28de6512f1ab41c0253bc918d45c5e6d9430d2b9","target":"graph","created_at":"2026-05-20T00:02:34Z","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":[{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T19:01:56.406112Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T18:33:26.525416Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.16650/integrity.json","findings":[],"snapshot_sha256":"a58dcd43f852d306b578b1b8e9fdf21d4a3278eeefa2b679f943d15dcabe69e1","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Evaluating multi-turn dialogue systems remains challenging because response quality depends not only on the current prompt, but also on previously established entities, claims, and conversational commitments. Existing automatic evaluators, including LLM-as-a-judge frameworks and embedding-based metrics, largely rely on flat or turn-isolated representations, making them less effective at detecting long-range issues such as contradiction, topic drift, and entity inconsistency. To address this, we propose SKG-Eval, a quasi-deterministic and interpretable framework that models dialogue as an evolv","authors_text":"Avijit Shil, Suman Samui","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-15T21:39:48Z","title":"SKG-Eval: Stateful Evaluation of Multi-Turn Dialogue via Incremental Semantic Knowledge Graphs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16650","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:de3acd5bad4ece7e18ddcf83e1249e4c302da78b20a96742709cfe576f6b5db3","target":"record","created_at":"2026-05-20T00:02:34Z","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":"8c31cd2642ae2f3830726a2b3abb4608c6dee3f1f4ee2e7f1f1c99e18df580d3","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-15T21:39:48Z","title_canon_sha256":"3d789d5a5f4c1989d31bf4c0d27d005715b1f9a680ec90a9df8530274e8c2721"},"schema_version":"1.0","source":{"id":"2605.16650","kind":"arxiv","version":1}},"canonical_sha256":"f8715c5d16f16e0c6771ed455135b6d01209e9c03ad9c1cd5443009906dc6a57","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f8715c5d16f16e0c6771ed455135b6d01209e9c03ad9c1cd5443009906dc6a57","first_computed_at":"2026-05-20T00:02:34.317938Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:34.317938Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wa7ouA4e/Y4Mxq/NIzmIU88tgAN/3NqROVOvqF4rVv64/73BYwQx5k2UwGFvCD5AY4Rj+N/NHyavhHNx64SMDA==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:34.318634Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.16650","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:de3acd5bad4ece7e18ddcf83e1249e4c302da78b20a96742709cfe576f6b5db3","sha256:0a3faac5f3e652cf89c1275b28de6512f1ab41c0253bc918d45c5e6d9430d2b9"],"state_sha256":"09e49877f66f033e33d89c21371ecd7f36236922aa8cf23048903efec045b62f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0GodTt1F05dlJ9MbXoZ3AYP8TQRyNOJaOTqfNBC800g2MIz1zmpAwUbSPvThmKlIbY4puHoG3gAByLl1O704Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T19:40:11.841611Z","bundle_sha256":"25a4514f9a09b7996345fb70eac95df2048620b88b8488456068a96989640434"}}