{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:Q4UJR4ECTESMEPPGXANIFD4AQA","short_pith_number":"pith:Q4UJR4EC","canonical_record":{"source":{"id":"2404.09492","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T06:28:20Z","cross_cats_sorted":[],"title_canon_sha256":"ad4d79a4e655c1994d2405fa3e9749eca9443fe4477fed9f48c6b54dce3a006c","abstract_canon_sha256":"c298ef74ebb1c871e0300f60a07ddd241543079fc5456bb699662c0d4366f3e6"},"schema_version":"1.0"},"canonical_sha256":"872898f0829924c23de6b81a828f80802fd01ac4abd0049152e395ef02e738f3","source":{"kind":"arxiv","id":"2404.09492","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.09492","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"arxiv_version","alias_value":"2404.09492v1","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.09492","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"pith_short_12","alias_value":"Q4UJR4ECTESM","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"pith_short_16","alias_value":"Q4UJR4ECTESMEPPG","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"pith_short_8","alias_value":"Q4UJR4EC","created_at":"2026-07-05T08:08:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:Q4UJR4ECTESMEPPGXANIFD4AQA","target":"record","payload":{"canonical_record":{"source":{"id":"2404.09492","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T06:28:20Z","cross_cats_sorted":[],"title_canon_sha256":"ad4d79a4e655c1994d2405fa3e9749eca9443fe4477fed9f48c6b54dce3a006c","abstract_canon_sha256":"c298ef74ebb1c871e0300f60a07ddd241543079fc5456bb699662c0d4366f3e6"},"schema_version":"1.0"},"canonical_sha256":"872898f0829924c23de6b81a828f80802fd01ac4abd0049152e395ef02e738f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:08:07.217651Z","signature_b64":"u9TcqSbPeYFzI7XZiQ1+Jpjk9kP6l5sc/I2XP4hTejmnZ+Rr8QPMhT4lxqbQaSDIy9hwWt3lo8W7Zsk16E8hBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"872898f0829924c23de6b81a828f80802fd01ac4abd0049152e395ef02e738f3","last_reissued_at":"2026-07-05T08:08:07.217284Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:08:07.217284Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.09492","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":"2026-07-05T08:08:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FbUlvok1JBWBN0biYf/Bao1KrNji66RXx2DdRXInC7khtlifW+LZbbqBvfgnjEzM9SY9vJINWhDJey+lSWwrBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T11:47:58.164572Z"},"content_sha256":"88818165c8fc3addf9b26ff889fd4f76ba548c2c9e2b222a652966b224bdf9f2","schema_version":"1.0","event_id":"sha256:88818165c8fc3addf9b26ff889fd4f76ba548c2c9e2b222a652966b224bdf9f2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:Q4UJR4ECTESMEPPGXANIFD4AQA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bridging the Gap between Different Vocabularies for LLM Ensemble","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jiajun Zhang, Jinliang Lu, Yangyifan Xu","submitted_at":"2024-04-15T06:28:20Z","abstract_excerpt":"Ensembling different large language models (LLMs) to unleash their complementary potential and harness their individual strengths is highly valuable. Nevertheless, vocabulary discrepancies among various LLMs have constrained previous studies to either selecting or blending completely generated outputs. This limitation hinders the dynamic correction and enhancement of outputs during the generation process, resulting in a limited capacity for effective ensemble. To address this issue, we propose a novel method to Ensemble LLMs via Vocabulary Alignment (EVA). EVA bridges the lexical gap among var"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.09492","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/2404.09492/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":"2026-07-05T08:08:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+G6jv9AWZxrrR7FM7Oo0ZI99ZaP2rK2yF4o9fPsbPTf4TccAb6T1ows0zNgy1A1lSndel0HW5I8DsNw+TZ0OBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T11:47:58.165053Z"},"content_sha256":"4387110df39d502a7d4c2b2659cdf9e37a5bfd026de97ef038ca5cc5ef31f73d","schema_version":"1.0","event_id":"sha256:4387110df39d502a7d4c2b2659cdf9e37a5bfd026de97ef038ca5cc5ef31f73d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q4UJR4ECTESMEPPGXANIFD4AQA/bundle.json","state_url":"https://pith.science/pith/Q4UJR4ECTESMEPPGXANIFD4AQA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q4UJR4ECTESMEPPGXANIFD4AQA/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":"2026-08-08T11:47:58Z","links":{"resolver":"https://pith.science/pith/Q4UJR4ECTESMEPPGXANIFD4AQA","bundle":"https://pith.science/pith/Q4UJR4ECTESMEPPGXANIFD4AQA/bundle.json","state":"https://pith.science/pith/Q4UJR4ECTESMEPPGXANIFD4AQA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q4UJR4ECTESMEPPGXANIFD4AQA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:Q4UJR4ECTESMEPPGXANIFD4AQA","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":"c298ef74ebb1c871e0300f60a07ddd241543079fc5456bb699662c0d4366f3e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T06:28:20Z","title_canon_sha256":"ad4d79a4e655c1994d2405fa3e9749eca9443fe4477fed9f48c6b54dce3a006c"},"schema_version":"1.0","source":{"id":"2404.09492","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.09492","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"arxiv_version","alias_value":"2404.09492v1","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.09492","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"pith_short_12","alias_value":"Q4UJR4ECTESM","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"pith_short_16","alias_value":"Q4UJR4ECTESMEPPG","created_at":"2026-07-05T08:08:07Z"},{"alias_kind":"pith_short_8","alias_value":"Q4UJR4EC","created_at":"2026-07-05T08:08:07Z"}],"graph_snapshots":[{"event_id":"sha256:4387110df39d502a7d4c2b2659cdf9e37a5bfd026de97ef038ca5cc5ef31f73d","target":"graph","created_at":"2026-07-05T08:08:07Z","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/2404.09492/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Ensembling different large language models (LLMs) to unleash their complementary potential and harness their individual strengths is highly valuable. Nevertheless, vocabulary discrepancies among various LLMs have constrained previous studies to either selecting or blending completely generated outputs. This limitation hinders the dynamic correction and enhancement of outputs during the generation process, resulting in a limited capacity for effective ensemble. To address this issue, we propose a novel method to Ensemble LLMs via Vocabulary Alignment (EVA). EVA bridges the lexical gap among var","authors_text":"Jiajun Zhang, Jinliang Lu, Yangyifan Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T06:28:20Z","title":"Bridging the Gap between Different Vocabularies for LLM Ensemble"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.09492","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":"sha256:88818165c8fc3addf9b26ff889fd4f76ba548c2c9e2b222a652966b224bdf9f2","target":"record","created_at":"2026-07-05T08:08:07Z","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":"c298ef74ebb1c871e0300f60a07ddd241543079fc5456bb699662c0d4366f3e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T06:28:20Z","title_canon_sha256":"ad4d79a4e655c1994d2405fa3e9749eca9443fe4477fed9f48c6b54dce3a006c"},"schema_version":"1.0","source":{"id":"2404.09492","kind":"arxiv","version":1}},"canonical_sha256":"872898f0829924c23de6b81a828f80802fd01ac4abd0049152e395ef02e738f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"872898f0829924c23de6b81a828f80802fd01ac4abd0049152e395ef02e738f3","first_computed_at":"2026-07-05T08:08:07.217284Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:07.217284Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u9TcqSbPeYFzI7XZiQ1+Jpjk9kP6l5sc/I2XP4hTejmnZ+Rr8QPMhT4lxqbQaSDIy9hwWt3lo8W7Zsk16E8hBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:07.217651Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.09492","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88818165c8fc3addf9b26ff889fd4f76ba548c2c9e2b222a652966b224bdf9f2","sha256:4387110df39d502a7d4c2b2659cdf9e37a5bfd026de97ef038ca5cc5ef31f73d"],"state_sha256":"f14c117159759d2b861992c96f32554ca31236a7090d7eafb1759e4b022c156a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lMx2eQ4uSFFDfZT2N5V1KlO5SoFqvpQ6882IEKD4Sg3mPB0Cqnw/aF5bjLe3OaX+hy/m5WE8VWz49nxwb1JSCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T11:47:58.168526Z","bundle_sha256":"6538d43e7f7cd59de431d6d1a29bc8d0cfef5832707e2ee02d608f8a0cfa8b8c"}}