{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CEJX2WZLGBLJE5BO2KAGH7V7AB","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":"d1ec47b69056790600af0fff0049fed943cebbeee93492aa3940fce414122a5e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-01T18:31:34Z","title_canon_sha256":"3a2bff0fbb6badca7137acddf73c4577779400254be0f13a4d654740da8662a8"},"schema_version":"1.0","source":{"id":"2402.00841","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00841","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00841v2","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00841","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_12","alias_value":"CEJX2WZLGBLJ","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_16","alias_value":"CEJX2WZLGBLJE5BO","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_8","alias_value":"CEJX2WZL","created_at":"2026-07-05T08:08:01Z"}],"graph_snapshots":[{"event_id":"sha256:69ffc04c7470734277881da91bc3b979809710798fd247dc72d6ab9eab421327","target":"graph","created_at":"2026-07-05T08:08:01Z","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/2402.00841/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated impressive capabilities to solve a wide range of tasks without being explicitly fine-tuned on task-specific datasets. However, deploying LLMs in the real world is not trivial, as it requires substantial computing resources. In this paper, we investigate whether smaller, compact LLMs are a good alternative to the comparatively Larger LLMs2 to address significant costs associated with utilizing LLMs in the real world. In this regard, we study the meeting summarization task in a real-world industrial environment and conduct extensive experiments by c","authors_text":"Cheng Chen, Elena Khasanova, Md Tahmid Rahman Laskar, Shashi Bhushan TN, Xue-Yong Fu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-01T18:31:34Z","title":"Tiny Titans: Can Smaller Large Language Models Punch Above Their Weight in the Real World for Meeting Summarization?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00841","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":"sha256:230ee72950c440f0af1ab46ec554482187a67e8626f900f28cf7a85bb9c848a3","target":"record","created_at":"2026-07-05T08:08:01Z","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":"d1ec47b69056790600af0fff0049fed943cebbeee93492aa3940fce414122a5e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-01T18:31:34Z","title_canon_sha256":"3a2bff0fbb6badca7137acddf73c4577779400254be0f13a4d654740da8662a8"},"schema_version":"1.0","source":{"id":"2402.00841","kind":"arxiv","version":2}},"canonical_sha256":"11137d5b2b305692742ed28063febf00454dd9d1ca382c2ebc4f75e84d461c95","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"11137d5b2b305692742ed28063febf00454dd9d1ca382c2ebc4f75e84d461c95","first_computed_at":"2026-07-05T08:08:01.636545Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:01.636545Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L0kJWWHjvsZmEMQjSIi7u6lT2a/rtqQDkBrfZ7oINMynJz+nJrzRE1UEuSocQC5C/n33PPD0f1TlmutEgA7cAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:01.637025Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.00841","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:230ee72950c440f0af1ab46ec554482187a67e8626f900f28cf7a85bb9c848a3","sha256:69ffc04c7470734277881da91bc3b979809710798fd247dc72d6ab9eab421327"],"state_sha256":"78acacc0357b0d081f85ca651f33ce1171233dd26fd8c57b1951315971a4faa2"}