{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2PPDFFXJLEB6PYC5K534ZZSD6T","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":"675afeaa999e4a85b97e2bcb85bf0048a07cd8e839de18e28fe578394f4523aa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T01:46:38Z","title_canon_sha256":"84ce46294b66bf332d4a52e2799855107032970bb2fca25a19e0a8d183c581c9"},"schema_version":"1.0","source":{"id":"2506.03483","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03483","created_at":"2026-07-05T11:15:28Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03483v1","created_at":"2026-07-05T11:15:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03483","created_at":"2026-07-05T11:15:28Z"},{"alias_kind":"pith_short_12","alias_value":"2PPDFFXJLEB6","created_at":"2026-07-05T11:15:28Z"},{"alias_kind":"pith_short_16","alias_value":"2PPDFFXJLEB6PYC5","created_at":"2026-07-05T11:15:28Z"},{"alias_kind":"pith_short_8","alias_value":"2PPDFFXJ","created_at":"2026-07-05T11:15:28Z"}],"graph_snapshots":[{"event_id":"sha256:612466d726955699ef2c964d59966e7a1514d87956fadce42513c7a3d848d9d4","target":"graph","created_at":"2026-07-05T11:15:28Z","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/2506.03483/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) often require domain-specific fine-tuning to address targeted tasks, which risks degrading their general capabilities. Maintaining a balance between domain-specific enhancements and general model utility is a key challenge. This paper proposes a novel approach named APT (Weakness Case Acquisition and Iterative Preference Training) to enhance domain-specific performance with self-generated dis-preferred weakness data (bad cases and similar cases). APT uniquely focuses on training the model using only those samples where errors occur, alongside a small, similar set o","authors_text":"Dong Jin, Jun Rao, Jun Yu, Lian Lian, Min Zhang, Shengjun Cheng, Xiaopeng Ke, Xuebo Liu, Zepeng Lin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T01:46:38Z","title":"APT: Improving Specialist LLM Performance with Weakness Case Acquisition and Iterative Preference Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03483","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:c239953c07076a285d376f13fe36ecc3c53f41db182486f89f930470f3f19684","target":"record","created_at":"2026-07-05T11:15:28Z","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":"675afeaa999e4a85b97e2bcb85bf0048a07cd8e839de18e28fe578394f4523aa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T01:46:38Z","title_canon_sha256":"84ce46294b66bf332d4a52e2799855107032970bb2fca25a19e0a8d183c581c9"},"schema_version":"1.0","source":{"id":"2506.03483","kind":"arxiv","version":1}},"canonical_sha256":"d3de3296e95903e7e05d5777cce643f4fb2741e93fa7bb1d296bcfeb53b32939","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d3de3296e95903e7e05d5777cce643f4fb2741e93fa7bb1d296bcfeb53b32939","first_computed_at":"2026-07-05T11:15:28.596045Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:15:28.596045Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0rHnJwikUU8CD4aelPbjcAjXLqbGr7FEhyb2tGw876b6xeKhXQKKEmC5F690DoVYVHMFf/BrpGORwRoZn2+rDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:15:28.596585Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.03483","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c239953c07076a285d376f13fe36ecc3c53f41db182486f89f930470f3f19684","sha256:612466d726955699ef2c964d59966e7a1514d87956fadce42513c7a3d848d9d4"],"state_sha256":"80d51624efed3461bc221895ddaf8610e581dd0bbd01b20d1ae5ca33735a52de"}