{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:RWXX2FANQ4HE645HCWKMKMNBQ2","short_pith_number":"pith:RWXX2FAN","schema_version":"1.0","canonical_sha256":"8daf7d140d870e4f73a71594c531a186a18d62f4b453711788a000e19c3df857","source":{"kind":"arxiv","id":"2505.04066","version":2},"attestation_state":"computed","paper":{"title":"LLAMAPIE: Proactive In-Ear Conversation Assistants","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.HC","cs.SD","eess.AS"],"primary_cat":"cs.LG","authors_text":"Alisa Liu, Nicholas Batchelder, Noah Smith, Shyamnath Gollakota, Tuochao Chen","submitted_at":"2025-05-07T02:08:56Z","abstract_excerpt":"We introduce LlamaPIE, the first real-time proactive assistant designed to enhance human conversations through discreet, concise guidance delivered via hearable devices. Unlike traditional language models that require explicit user invocation, this assistant operates in the background, anticipating user needs without interrupting conversations. We address several challenges, including determining when to respond, crafting concise responses that enhance conversations, leveraging knowledge of the user for context-aware assistance, and real-time, on-device processing. To achieve this, we construc"},"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":"2505.04066","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-07T02:08:56Z","cross_cats_sorted":["cs.CL","cs.HC","cs.SD","eess.AS"],"title_canon_sha256":"e1dbb3a113e279fd7034065117aac1d1300b0541841fb15be527bbd403358904","abstract_canon_sha256":"6e5de8d8ab312cb0d85309c1baa37233fa88ae6016cee8cdd39060ca8a84635a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:44:48.282602Z","signature_b64":"kntPVzkYcp+gKRYPTDqxoxj58qOYBAd35P9eYG13mhk0XObdCqwGpn29dQFmUkpHsqjuZNPffaL/3CJHSOGgBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8daf7d140d870e4f73a71594c531a186a18d62f4b453711788a000e19c3df857","last_reissued_at":"2026-07-05T11:44:48.282141Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:44:48.282141Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LLAMAPIE: Proactive In-Ear Conversation Assistants","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.HC","cs.SD","eess.AS"],"primary_cat":"cs.LG","authors_text":"Alisa Liu, Nicholas Batchelder, Noah Smith, Shyamnath Gollakota, Tuochao Chen","submitted_at":"2025-05-07T02:08:56Z","abstract_excerpt":"We introduce LlamaPIE, the first real-time proactive assistant designed to enhance human conversations through discreet, concise guidance delivered via hearable devices. Unlike traditional language models that require explicit user invocation, this assistant operates in the background, anticipating user needs without interrupting conversations. We address several challenges, including determining when to respond, crafting concise responses that enhance conversations, leveraging knowledge of the user for context-aware assistance, and real-time, on-device processing. To achieve this, we construc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.04066","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/2505.04066/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":"2505.04066","created_at":"2026-07-05T11:44:48.282208+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.04066v2","created_at":"2026-07-05T11:44:48.282208+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.04066","created_at":"2026-07-05T11:44:48.282208+00:00"},{"alias_kind":"pith_short_12","alias_value":"RWXX2FANQ4HE","created_at":"2026-07-05T11:44:48.282208+00:00"},{"alias_kind":"pith_short_16","alias_value":"RWXX2FANQ4HE645H","created_at":"2026-07-05T11:44:48.282208+00:00"},{"alias_kind":"pith_short_8","alias_value":"RWXX2FAN","created_at":"2026-07-05T11:44:48.282208+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.09461","citing_title":"H2HMem: A Multimodal Memory Benchmark for Agents in Human-Human Interactions","ref_index":1,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2","json":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2.json","graph_json":"https://pith.science/api/pith-number/RWXX2FANQ4HE645HCWKMKMNBQ2/graph.json","events_json":"https://pith.science/api/pith-number/RWXX2FANQ4HE645HCWKMKMNBQ2/events.json","paper":"https://pith.science/paper/RWXX2FAN"},"agent_actions":{"view_html":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2","download_json":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2.json","view_paper":"https://pith.science/paper/RWXX2FAN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.04066&json=true","fetch_graph":"https://pith.science/api/pith-number/RWXX2FANQ4HE645HCWKMKMNBQ2/graph.json","fetch_events":"https://pith.science/api/pith-number/RWXX2FANQ4HE645HCWKMKMNBQ2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2/action/storage_attestation","attest_author":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2/action/author_attestation","sign_citation":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2/action/citation_signature","submit_replication":"https://pith.science/pith/RWXX2FANQ4HE645HCWKMKMNBQ2/action/replication_record"}},"created_at":"2026-07-05T11:44:48.282208+00:00","updated_at":"2026-07-05T11:44:48.282208+00:00"}