{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:C4AY3LNXDPHNPJJ52G32YWJUIS","short_pith_number":"pith:C4AY3LNX","schema_version":"1.0","canonical_sha256":"17018dadb71bced7a53dd1b7ac59344486c02282158cc060c9881e75d54e9119","source":{"kind":"arxiv","id":"2310.06272","version":2},"attestation_state":"computed","paper":{"title":"Let Models Speak Ciphers: Multiagent Debate through Embeddings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Boyi Liu, Bryan A. Plummer, Chau Pham, Hongxia Yang, Jianbo Yuan, Tianyi Liu, Yingxiang Yang, Zhaoran Wang, Zhengyu Chen","submitted_at":"2023-10-10T03:06:38Z","abstract_excerpt":"Discussion and debate among Large Language Models (LLMs) have gained considerable attention due to their potential to enhance the reasoning ability of LLMs. Although natural language is an obvious choice for communication due to LLM's language understanding capability, the token sampling step needed when generating natural language poses a potential risk of information loss, as it uses only one token to represent the model's belief across the entire vocabulary. In this paper, we introduce a communication regime named CIPHER (Communicative Inter-Model Protocol Through Embedding Representation) "},"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":"2310.06272","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-10T03:06:38Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"4a90636b0f1ac608e24e93925eb7e6eefd0b8ae2e78a380a2dda842ca9234962","abstract_canon_sha256":"0e706076f605fbc5b1520991a2392ee3761c9c1ab4e90565ebeeccd77fd8b5c9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:49:15.089868Z","signature_b64":"44OTPh1xIYFAcTF1dsP0/Q+x104c2TJB9dXRTY8mMWuxJvSPbBuiivnNwJgBL1l875y/SyouPg84J636mkn6Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17018dadb71bced7a53dd1b7ac59344486c02282158cc060c9881e75d54e9119","last_reissued_at":"2026-07-05T07:49:15.089326Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:49:15.089326Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Let Models Speak Ciphers: Multiagent Debate through Embeddings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Boyi Liu, Bryan A. Plummer, Chau Pham, Hongxia Yang, Jianbo Yuan, Tianyi Liu, Yingxiang Yang, Zhaoran Wang, Zhengyu Chen","submitted_at":"2023-10-10T03:06:38Z","abstract_excerpt":"Discussion and debate among Large Language Models (LLMs) have gained considerable attention due to their potential to enhance the reasoning ability of LLMs. Although natural language is an obvious choice for communication due to LLM's language understanding capability, the token sampling step needed when generating natural language poses a potential risk of information loss, as it uses only one token to represent the model's belief across the entire vocabulary. In this paper, we introduce a communication regime named CIPHER (Communicative Inter-Model Protocol Through Embedding Representation) "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.06272","kind":"arxiv","version":2},"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/2310.06272/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":"2310.06272","created_at":"2026-07-05T07:49:15.089384+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.06272v2","created_at":"2026-07-05T07:49:15.089384+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.06272","created_at":"2026-07-05T07:49:15.089384+00:00"},{"alias_kind":"pith_short_12","alias_value":"C4AY3LNXDPHN","created_at":"2026-07-05T07:49:15.089384+00:00"},{"alias_kind":"pith_short_16","alias_value":"C4AY3LNXDPHNPJJ5","created_at":"2026-07-05T07:49:15.089384+00:00"},{"alias_kind":"pith_short_8","alias_value":"C4AY3LNX","created_at":"2026-07-05T07:49:15.089384+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":7,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.20662","citing_title":"Confidence Laundering in Agent Systems: Why Uncertainty Needs a Latent Carrier","ref_index":60,"is_internal_anchor":false},{"citing_arxiv_id":"2606.11470","citing_title":"The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes","ref_index":192,"is_internal_anchor":false},{"citing_arxiv_id":"2606.08068","citing_title":"DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination","ref_index":187,"is_internal_anchor":false},{"citing_arxiv_id":"2606.05711","citing_title":"Beyond tokens: a unified framework for latent communication in LLM-based multi-agent systems","ref_index":5,"is_internal_anchor":false},{"citing_arxiv_id":"2605.25421","citing_title":"HyLaT: Efficient Multi-Agent Communication via Hybrid Latent-Text Protocol","ref_index":15,"is_internal_anchor":false},{"citing_arxiv_id":"2412.06769","citing_title":"Training Large Language Models to Reason in a Continuous Latent Space","ref_index":24,"is_internal_anchor":false},{"citing_arxiv_id":"2604.21027","citing_title":"HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering","ref_index":108,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS","json":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS.json","graph_json":"https://pith.science/api/pith-number/C4AY3LNXDPHNPJJ52G32YWJUIS/graph.json","events_json":"https://pith.science/api/pith-number/C4AY3LNXDPHNPJJ52G32YWJUIS/events.json","paper":"https://pith.science/paper/C4AY3LNX"},"agent_actions":{"view_html":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS","download_json":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS.json","view_paper":"https://pith.science/paper/C4AY3LNX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.06272&json=true","fetch_graph":"https://pith.science/api/pith-number/C4AY3LNXDPHNPJJ52G32YWJUIS/graph.json","fetch_events":"https://pith.science/api/pith-number/C4AY3LNXDPHNPJJ52G32YWJUIS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS/action/storage_attestation","attest_author":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS/action/author_attestation","sign_citation":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS/action/citation_signature","submit_replication":"https://pith.science/pith/C4AY3LNXDPHNPJJ52G32YWJUIS/action/replication_record"}},"created_at":"2026-07-05T07:49:15.089384+00:00","updated_at":"2026-07-05T07:49:15.089384+00:00"}