{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:IS7DZU2MDCOR47KTHZVUBZFG7V","short_pith_number":"pith:IS7DZU2M","schema_version":"1.0","canonical_sha256":"44be3cd34c189d1e7d533e6b40e4a6fd6363f5f1afd80112a18069f8412c091f","source":{"kind":"arxiv","id":"2106.08694","version":2},"attestation_state":"computed","paper":{"title":"On the proper role of linguistically-oriented deep net analysis in linguistic theorizing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Marco Baroni","submitted_at":"2021-06-16T10:57:24Z","abstract_excerpt":"A lively research field has recently emerged that uses experimental methods to probe the linguistic behavior of modern deep networks. While work in this tradition often reports intriguing results about the grammatical skills of deep nets, it is not clear what their implications for linguistic theorizing should be. As a consequence, linguistically-oriented deep net analysis has had very little impact on linguistics at large. In this chapter, I suggest that deep networks should be treated as theories making explicit predictions about the acceptability of linguistic utterances. I argue that, if w"},"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":"2106.08694","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-16T10:57:24Z","cross_cats_sorted":[],"title_canon_sha256":"f20650f0e733e156715fb39d7cccb5c024b47ccc7eaa22881c5f2a5312ed5224","abstract_canon_sha256":"9ca59459e3388b9d8d1e67c200089a54b728ecae01c25606c9c4ec1da554dfa4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:08:15.513126Z","signature_b64":"117ZyWF9ehHTE4OB7QSCs4qcDSL1SOCHX1khq2hSjYcn5xUj7wETTngV4zQFlNARdzNNb/9XXUJ4fBSLdOaJAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"44be3cd34c189d1e7d533e6b40e4a6fd6363f5f1afd80112a18069f8412c091f","last_reissued_at":"2026-07-05T04:08:15.512666Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:08:15.512666Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On the proper role of linguistically-oriented deep net analysis in linguistic theorizing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Marco Baroni","submitted_at":"2021-06-16T10:57:24Z","abstract_excerpt":"A lively research field has recently emerged that uses experimental methods to probe the linguistic behavior of modern deep networks. While work in this tradition often reports intriguing results about the grammatical skills of deep nets, it is not clear what their implications for linguistic theorizing should be. As a consequence, linguistically-oriented deep net analysis has had very little impact on linguistics at large. In this chapter, I suggest that deep networks should be treated as theories making explicit predictions about the acceptability of linguistic utterances. I argue that, if w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.08694","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/2106.08694/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":"2106.08694","created_at":"2026-07-05T04:08:15.512722+00:00"},{"alias_kind":"arxiv_version","alias_value":"2106.08694v2","created_at":"2026-07-05T04:08:15.512722+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.08694","created_at":"2026-07-05T04:08:15.512722+00:00"},{"alias_kind":"pith_short_12","alias_value":"IS7DZU2MDCOR","created_at":"2026-07-05T04:08:15.512722+00:00"},{"alias_kind":"pith_short_16","alias_value":"IS7DZU2MDCOR47KT","created_at":"2026-07-05T04:08:15.512722+00:00"},{"alias_kind":"pith_short_8","alias_value":"IS7DZU2M","created_at":"2026-07-05T04:08:15.512722+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.15440","citing_title":"Why are language models less surprised than humans? Testing the Parse Multiplicity Mismatch Hypothesis","ref_index":264,"is_internal_anchor":false},{"citing_arxiv_id":"2604.18563","citing_title":"Dual Alignment Between Language Model Layers and Human Sentence Processing","ref_index":295,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V","json":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V.json","graph_json":"https://pith.science/api/pith-number/IS7DZU2MDCOR47KTHZVUBZFG7V/graph.json","events_json":"https://pith.science/api/pith-number/IS7DZU2MDCOR47KTHZVUBZFG7V/events.json","paper":"https://pith.science/paper/IS7DZU2M"},"agent_actions":{"view_html":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V","download_json":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V.json","view_paper":"https://pith.science/paper/IS7DZU2M","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2106.08694&json=true","fetch_graph":"https://pith.science/api/pith-number/IS7DZU2MDCOR47KTHZVUBZFG7V/graph.json","fetch_events":"https://pith.science/api/pith-number/IS7DZU2MDCOR47KTHZVUBZFG7V/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V/action/storage_attestation","attest_author":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V/action/author_attestation","sign_citation":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V/action/citation_signature","submit_replication":"https://pith.science/pith/IS7DZU2MDCOR47KTHZVUBZFG7V/action/replication_record"}},"created_at":"2026-07-05T04:08:15.512722+00:00","updated_at":"2026-07-05T04:08:15.512722+00:00"}