{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZKZ55OMHSTASZJ2T5TOAHVRK7D","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":"a8322066e8633b355e4360a17ab10e56bcc630fcafd607a175aeed80786c15d5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-05T23:13:22Z","title_canon_sha256":"12590fb0153c78d2e2f84213fa8c8cb6fd515418a0d2320e04cf9bd0e9fd520b"},"schema_version":"1.0","source":{"id":"2506.05629","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05629","created_at":"2026-07-05T11:17:07Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05629v1","created_at":"2026-07-05T11:17:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05629","created_at":"2026-07-05T11:17:07Z"},{"alias_kind":"pith_short_12","alias_value":"ZKZ55OMHSTAS","created_at":"2026-07-05T11:17:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZKZ55OMHSTASZJ2T","created_at":"2026-07-05T11:17:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZKZ55OMH","created_at":"2026-07-05T11:17:07Z"}],"graph_snapshots":[{"event_id":"sha256:34efd53b416274a7f74c6349e2efc2eec3af5eec037042104a7fa3aa777b32fb","target":"graph","created_at":"2026-07-05T11:17:07Z","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/2506.05629/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The performance of large language models in domain-specific tasks necessitates fine-tuning, which is computationally expensive and technically challenging. This paper focuses on parameter-efficient fine-tuning using soft prompting, a promising approach that adapts pre-trained models to downstream tasks by learning a small set of parameters. We propose a novel Input Dependent Soft Prompting technique with a self-Attention Mechanism (ID-SPAM) that generates soft prompts based on the input tokens and attends different tokens with varying importance. Our method is simple and efficient, keeping the","authors_text":"Abhilash Nandy, Ananth Muppidi, Sambaran Bandyopadhyay","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-05T23:13:22Z","title":"Leveraging Self-Attention for Input-Dependent Soft Prompting in LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05629","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:ae1d761e2e117ea2fa6858e88bfce1494fa4dddca0d43b371e060524e0178da1","target":"record","created_at":"2026-07-05T11:17:07Z","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":"a8322066e8633b355e4360a17ab10e56bcc630fcafd607a175aeed80786c15d5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-05T23:13:22Z","title_canon_sha256":"12590fb0153c78d2e2f84213fa8c8cb6fd515418a0d2320e04cf9bd0e9fd520b"},"schema_version":"1.0","source":{"id":"2506.05629","kind":"arxiv","version":1}},"canonical_sha256":"cab3deb98794c12ca753ecdc03d62af8cac40d274ed2b3c435307832c2148045","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cab3deb98794c12ca753ecdc03d62af8cac40d274ed2b3c435307832c2148045","first_computed_at":"2026-07-05T11:17:07.121245Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:17:07.121245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mkRuwRD1Jm2N2IiCCq5BmHnwBGI9yRpOkJV/iAmMEMsKZp3RSoJWURVmEarXVCFQ1WV166ru3nqkE+loTiV3AA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:17:07.121793Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.05629","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ae1d761e2e117ea2fa6858e88bfce1494fa4dddca0d43b371e060524e0178da1","sha256:34efd53b416274a7f74c6349e2efc2eec3af5eec037042104a7fa3aa777b32fb"],"state_sha256":"a92bd683bda4d821dddf802582f5e18be5381f5769ec3e3ba42640ad7a76dbc3"}