{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:L5FYAWY6MACPZPBHRLZSQD4645","short_pith_number":"pith:L5FYAWY6","canonical_record":{"source":{"id":"2605.23052","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-21T21:35:08Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"739e93abc81ee7ea50f375770bfb2e0508506386bf25eb42051746edbff454e2","abstract_canon_sha256":"af8d3609d6ab3ef01c19929c5c0cdc3814d41e26fe547331c327ef4dd32560e6"},"schema_version":"1.0"},"canonical_sha256":"5f4b805b1e6004fcbc278af3280f9ee756973df6c5cf628a955353ee2a07bffc","source":{"kind":"arxiv","id":"2605.23052","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.23052","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"arxiv_version","alias_value":"2605.23052v1","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23052","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"pith_short_12","alias_value":"L5FYAWY6MACP","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"pith_short_16","alias_value":"L5FYAWY6MACPZPBH","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"pith_short_8","alias_value":"L5FYAWY6","created_at":"2026-05-25T02:01:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:L5FYAWY6MACPZPBHRLZSQD4645","target":"record","payload":{"canonical_record":{"source":{"id":"2605.23052","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-21T21:35:08Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"739e93abc81ee7ea50f375770bfb2e0508506386bf25eb42051746edbff454e2","abstract_canon_sha256":"af8d3609d6ab3ef01c19929c5c0cdc3814d41e26fe547331c327ef4dd32560e6"},"schema_version":"1.0"},"canonical_sha256":"5f4b805b1e6004fcbc278af3280f9ee756973df6c5cf628a955353ee2a07bffc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-25T02:01:36.316718Z","signature_b64":"BO1L8EX0fuZQynBPqiylVs+gCT5OaBIIQG451OhoGaxdLP0zH9Y8O3WcB+IibnwQQvx1X0wjF2xgo9stiu8BDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f4b805b1e6004fcbc278af3280f9ee756973df6c5cf628a955353ee2a07bffc","last_reissued_at":"2026-05-25T02:01:36.316042Z","signature_status":"signed_v1","first_computed_at":"2026-05-25T02:01:36.316042Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.23052","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":"2026-05-25T02:01:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tx4J5tFvL20rsl1ZUSWBbHWAqdW8N38pw/SQ6+Q1V5BiwORhpOkygdifU5D3y5BM3127utfx2pe66SfnbE/vDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T02:21:07.270775Z"},"content_sha256":"4e250469c56889eafbc6d87d37cec81cacb61b17c44166b12adecc293047eaf7","schema_version":"1.0","event_id":"sha256:4e250469c56889eafbc6d87d37cec81cacb61b17c44166b12adecc293047eaf7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:L5FYAWY6MACPZPBHRLZSQD4645","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DreamerNLplus: Interpretable Modeling of Mental Health Dynamics from Social Media Timelines using Hybrid Rule-Based and RAG Methods","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Daisy Monika Lal, Erik van Mulligen, Lifeng Han, Maryia Zhyrko","submitted_at":"2026-05-21T21:35:08Z","abstract_excerpt":"We present DreamerNLplus, a hybrid framework for modeling mental health dynamics from social media timelines in the CLPsych 2026 shared task. Our system addresses three tasks: psychological state modeling, temporal change detection, and sequence-level summarization.\n  For Task 1, we combine LLM-based data augmentation, DeBERTa classification, and Random Forest regression for structured state prediction. For Task 2, we use few-shot prompting with a locally deployed Llama 3.1 model to detect Switch and Escalation events using short-term temporal context. For Task 3.1, we explore both a determini"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23052","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/2605.23052/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":"2026-05-25T02:01:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0EsnGawDj1Y8eWqohtMTAbUZGldOIJIPhTcfh3ilH4HpItH/Oc/oxUdzbnFWetiCPFKXaLdfl4zIGI2jjjjJCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T02:21:07.271155Z"},"content_sha256":"70efae216863dbbf59d71579fab62f2b8f15f8f45533427b34f852ce6083e0f8","schema_version":"1.0","event_id":"sha256:70efae216863dbbf59d71579fab62f2b8f15f8f45533427b34f852ce6083e0f8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L5FYAWY6MACPZPBHRLZSQD4645/bundle.json","state_url":"https://pith.science/pith/L5FYAWY6MACPZPBHRLZSQD4645/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L5FYAWY6MACPZPBHRLZSQD4645/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":"2026-05-28T02:21:07Z","links":{"resolver":"https://pith.science/pith/L5FYAWY6MACPZPBHRLZSQD4645","bundle":"https://pith.science/pith/L5FYAWY6MACPZPBHRLZSQD4645/bundle.json","state":"https://pith.science/pith/L5FYAWY6MACPZPBHRLZSQD4645/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L5FYAWY6MACPZPBHRLZSQD4645/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:L5FYAWY6MACPZPBHRLZSQD4645","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":"af8d3609d6ab3ef01c19929c5c0cdc3814d41e26fe547331c327ef4dd32560e6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-21T21:35:08Z","title_canon_sha256":"739e93abc81ee7ea50f375770bfb2e0508506386bf25eb42051746edbff454e2"},"schema_version":"1.0","source":{"id":"2605.23052","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.23052","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"arxiv_version","alias_value":"2605.23052v1","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23052","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"pith_short_12","alias_value":"L5FYAWY6MACP","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"pith_short_16","alias_value":"L5FYAWY6MACPZPBH","created_at":"2026-05-25T02:01:36Z"},{"alias_kind":"pith_short_8","alias_value":"L5FYAWY6","created_at":"2026-05-25T02:01:36Z"}],"graph_snapshots":[{"event_id":"sha256:70efae216863dbbf59d71579fab62f2b8f15f8f45533427b34f852ce6083e0f8","target":"graph","created_at":"2026-05-25T02:01:36Z","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/2605.23052/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present DreamerNLplus, a hybrid framework for modeling mental health dynamics from social media timelines in the CLPsych 2026 shared task. Our system addresses three tasks: psychological state modeling, temporal change detection, and sequence-level summarization.\n  For Task 1, we combine LLM-based data augmentation, DeBERTa classification, and Random Forest regression for structured state prediction. For Task 2, we use few-shot prompting with a locally deployed Llama 3.1 model to detect Switch and Escalation events using short-term temporal context. For Task 3.1, we explore both a determini","authors_text":"Daisy Monika Lal, Erik van Mulligen, Lifeng Han, Maryia Zhyrko","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-21T21:35:08Z","title":"DreamerNLplus: Interpretable Modeling of Mental Health Dynamics from Social Media Timelines using Hybrid Rule-Based and RAG Methods"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23052","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":"sha256:4e250469c56889eafbc6d87d37cec81cacb61b17c44166b12adecc293047eaf7","target":"record","created_at":"2026-05-25T02:01:36Z","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":"af8d3609d6ab3ef01c19929c5c0cdc3814d41e26fe547331c327ef4dd32560e6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-21T21:35:08Z","title_canon_sha256":"739e93abc81ee7ea50f375770bfb2e0508506386bf25eb42051746edbff454e2"},"schema_version":"1.0","source":{"id":"2605.23052","kind":"arxiv","version":1}},"canonical_sha256":"5f4b805b1e6004fcbc278af3280f9ee756973df6c5cf628a955353ee2a07bffc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f4b805b1e6004fcbc278af3280f9ee756973df6c5cf628a955353ee2a07bffc","first_computed_at":"2026-05-25T02:01:36.316042Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-25T02:01:36.316042Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BO1L8EX0fuZQynBPqiylVs+gCT5OaBIIQG451OhoGaxdLP0zH9Y8O3WcB+IibnwQQvx1X0wjF2xgo9stiu8BDg==","signature_status":"signed_v1","signed_at":"2026-05-25T02:01:36.316718Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.23052","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e250469c56889eafbc6d87d37cec81cacb61b17c44166b12adecc293047eaf7","sha256:70efae216863dbbf59d71579fab62f2b8f15f8f45533427b34f852ce6083e0f8"],"state_sha256":"92fdbfe59b31711b7107ad09b054344a45d0d074570274bec90e60e0667bcb93"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w1jmcb117Byo9uDbJi+lQm7bQrq9g3SLdc6HJMAijk1N68C9xqGxdDhjTPpU7EeYH/gHpc0kUH/BKUcftEO+Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T02:21:07.273208Z","bundle_sha256":"d7b42f3e91b41b16fde54fea04333ca57ec9a84837af6ca106780fe6c4bebe4d"}}