{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FY6UZ4TGMCGNOW44XHECDEFUBY","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":"93269f47a9fc48ac4afca98505b178af4149845b22393e7fd09fad49cada8b9a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-26T22:45:08Z","title_canon_sha256":"feb8a31e98a39dd5253fdcd7652299b9959bced2dd519fb2913bb81a0f1256d2"},"schema_version":"1.0","source":{"id":"2502.19607","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.19607","created_at":"2026-07-05T10:22:15Z"},{"alias_kind":"arxiv_version","alias_value":"2502.19607v2","created_at":"2026-07-05T10:22:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.19607","created_at":"2026-07-05T10:22:15Z"},{"alias_kind":"pith_short_12","alias_value":"FY6UZ4TGMCGN","created_at":"2026-07-05T10:22:15Z"},{"alias_kind":"pith_short_16","alias_value":"FY6UZ4TGMCGNOW44","created_at":"2026-07-05T10:22:15Z"},{"alias_kind":"pith_short_8","alias_value":"FY6UZ4TG","created_at":"2026-07-05T10:22:15Z"}],"graph_snapshots":[{"event_id":"sha256:05aa30953e1deb286e3007db08e79c9365616752097b8f559d02a1ddffdd142b","target":"graph","created_at":"2026-07-05T10:22:15Z","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/2502.19607/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have recently shown remarkable advancement in various NLP tasks. As such, a popular trend has emerged lately where NLP researchers extract word/sentence/document embeddings from these large decoder-only models and use them for various inference tasks with promising results. However, it is still unclear whether the performance improvement of LLM-induced embeddings is merely because of scale or whether underlying embeddings they produce significantly differ from classical encoding models like Word2Vec, GloVe, Sentence-BERT (SBERT) or Universal Sentence Encoder (USE).","authors_text":"Matthew Freestone, Santu Karmaker, Sathyanarayanan Aakur, Yash Mahajan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-26T22:45:08Z","title":"Revisiting Word Embeddings in the LLM Era"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.19607","kind":"arxiv","version":2},"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":"sha256:602d0919eb5e1cb3156185d45f92d13fa806a0747eb706ba3dade9ba1bbf1e45","target":"record","created_at":"2026-07-05T10:22:15Z","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":"93269f47a9fc48ac4afca98505b178af4149845b22393e7fd09fad49cada8b9a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-26T22:45:08Z","title_canon_sha256":"feb8a31e98a39dd5253fdcd7652299b9959bced2dd519fb2913bb81a0f1256d2"},"schema_version":"1.0","source":{"id":"2502.19607","kind":"arxiv","version":2}},"canonical_sha256":"2e3d4cf266608cd75b9cb9c82190b40e27af816f77c236c47a58a707b65f2762","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2e3d4cf266608cd75b9cb9c82190b40e27af816f77c236c47a58a707b65f2762","first_computed_at":"2026-07-05T10:22:15.500151Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:22:15.500151Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DntsILdlRFdSFGIkXxE5ax9AJX77yv+wRFk/yQy+KreTDZ/G7X/5lVJCm8MnFzUNzqCYHJ5CBO83wfcpMN2ICA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:22:15.500728Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.19607","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:602d0919eb5e1cb3156185d45f92d13fa806a0747eb706ba3dade9ba1bbf1e45","sha256:05aa30953e1deb286e3007db08e79c9365616752097b8f559d02a1ddffdd142b"],"state_sha256":"bdf4cdd3287ddd2e5d01e94f2a09d9802bf920213a39ce7c297764234902baee"}