{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:3NZNTDBRAJU6NEU44QTC4IBXLS","short_pith_number":"pith:3NZNTDBR","schema_version":"1.0","canonical_sha256":"db72d98c310269e6929ce4262e20375cbae29db958d335f89547a458758be8e8","source":{"kind":"arxiv","id":"2606.13189","version":1},"attestation_state":"computed","paper":{"title":"SICI: A Semantic-Pragmatic Complexity Index Reveals Regime Shifts in LLM Stance Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bowen Zhang, Fuqiang Niu","submitted_at":"2026-06-11T10:58:18Z","abstract_excerpt":"Prompt-based LLMs are increasingly used for stance detection, but harder examples are not always repaired by clearer instructions, reasoning prompts, retrieval, or debate. We introduce SICI (Stance Inference Complexity Index), a seven-dimensional diagnostic measure of the semantic-pragmatic burden imposed by a target--text pair. Across SemEval-2016 and VAST, SICI predicts LLM accuracy better than surface proxies and shows substantial cross-scorer reliability ($\\alpha=0.771$). More importantly, LLM errors change regime as SICI increases: low-complexity examples invite over-attribution, especial"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.13189","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-06-11T10:58:18Z","cross_cats_sorted":[],"title_canon_sha256":"ddc4ad75b6ba8d05990caf88db4d9ccc411614b6535a98f71b76468abd8478c8","abstract_canon_sha256":"3729396b33f020a17185659eb14511d818dd634f4d89cc503a8bb3f40ae27734"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-12T01:09:45.952088Z","signature_b64":"W8qP6VgSAA3MwCw0eLJg5XnIgX64KupZR3oGYZ6wql7lGkCkR3ZFyuPG59mX95waWjPVjXRCNvjJtDxuRLS1Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db72d98c310269e6929ce4262e20375cbae29db958d335f89547a458758be8e8","last_reissued_at":"2026-06-12T01:09:45.951163Z","signature_status":"signed_v1","first_computed_at":"2026-06-12T01:09:45.951163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SICI: A Semantic-Pragmatic Complexity Index Reveals Regime Shifts in LLM Stance Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bowen Zhang, Fuqiang Niu","submitted_at":"2026-06-11T10:58:18Z","abstract_excerpt":"Prompt-based LLMs are increasingly used for stance detection, but harder examples are not always repaired by clearer instructions, reasoning prompts, retrieval, or debate. We introduce SICI (Stance Inference Complexity Index), a seven-dimensional diagnostic measure of the semantic-pragmatic burden imposed by a target--text pair. Across SemEval-2016 and VAST, SICI predicts LLM accuracy better than surface proxies and shows substantial cross-scorer reliability ($\\alpha=0.771$). More importantly, LLM errors change regime as SICI increases: low-complexity examples invite over-attribution, especial"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.13189","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/2606.13189/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.13189","created_at":"2026-06-12T01:09:45.951295+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.13189v1","created_at":"2026-06-12T01:09:45.951295+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.13189","created_at":"2026-06-12T01:09:45.951295+00:00"},{"alias_kind":"pith_short_12","alias_value":"3NZNTDBRAJU6","created_at":"2026-06-12T01:09:45.951295+00:00"},{"alias_kind":"pith_short_16","alias_value":"3NZNTDBRAJU6NEU4","created_at":"2026-06-12T01:09:45.951295+00:00"},{"alias_kind":"pith_short_8","alias_value":"3NZNTDBR","created_at":"2026-06-12T01:09:45.951295+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS","json":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS.json","graph_json":"https://pith.science/api/pith-number/3NZNTDBRAJU6NEU44QTC4IBXLS/graph.json","events_json":"https://pith.science/api/pith-number/3NZNTDBRAJU6NEU44QTC4IBXLS/events.json","paper":"https://pith.science/paper/3NZNTDBR"},"agent_actions":{"view_html":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS","download_json":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS.json","view_paper":"https://pith.science/paper/3NZNTDBR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.13189&json=true","fetch_graph":"https://pith.science/api/pith-number/3NZNTDBRAJU6NEU44QTC4IBXLS/graph.json","fetch_events":"https://pith.science/api/pith-number/3NZNTDBRAJU6NEU44QTC4IBXLS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS/action/storage_attestation","attest_author":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS/action/author_attestation","sign_citation":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS/action/citation_signature","submit_replication":"https://pith.science/pith/3NZNTDBRAJU6NEU44QTC4IBXLS/action/replication_record"}},"created_at":"2026-06-12T01:09:45.951295+00:00","updated_at":"2026-06-12T01:09:45.951295+00:00"}