{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:RH2RGGQ4T2E3P4KRLQ5PZ5LTAC","short_pith_number":"pith:RH2RGGQ4","canonical_record":{"source":{"id":"2411.09073","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-13T22:56:00Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"9c79b7df97a0b579dd91011038c7fd2cbae8251112f22d522092ba58f03d6c51","abstract_canon_sha256":"925a58262afd76bab7ea560a62c70b143b94d7d5fad31b8ef79a2eafcf404f0c"},"schema_version":"1.0"},"canonical_sha256":"89f5131a1c9e89b7f1515c3afcf573009fe6e963e20b66b82dcc534a1401fd0d","source":{"kind":"arxiv","id":"2411.09073","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.09073","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"arxiv_version","alias_value":"2411.09073v3","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.09073","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"pith_short_12","alias_value":"RH2RGGQ4T2E3","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"pith_short_16","alias_value":"RH2RGGQ4T2E3P4KR","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"pith_short_8","alias_value":"RH2RGGQ4","created_at":"2026-07-05T11:34:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:RH2RGGQ4T2E3P4KRLQ5PZ5LTAC","target":"record","payload":{"canonical_record":{"source":{"id":"2411.09073","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-13T22:56:00Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"9c79b7df97a0b579dd91011038c7fd2cbae8251112f22d522092ba58f03d6c51","abstract_canon_sha256":"925a58262afd76bab7ea560a62c70b143b94d7d5fad31b8ef79a2eafcf404f0c"},"schema_version":"1.0"},"canonical_sha256":"89f5131a1c9e89b7f1515c3afcf573009fe6e963e20b66b82dcc534a1401fd0d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:34:01.899686Z","signature_b64":"SHoVj1a/Q53WpL0CbOD8BpM/fZQk0pB0C3nRm3jt/4qhLGRrb3Icn71Xuxrcl48PHqoNF2EJvub63VSBCgCNBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"89f5131a1c9e89b7f1515c3afcf573009fe6e963e20b66b82dcc534a1401fd0d","last_reissued_at":"2026-07-05T11:34:01.899187Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:34:01.899187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.09073","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:34:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+EtX9M/mQafMDPwbd1wOp+49OhyR7o4GZFPzK0OZa5wbgSj91xo3MSK0KTdFoWubLcSYj5FPgaJAqmsinuxTDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T01:18:01.033392Z"},"content_sha256":"8285874d3eac1ffe1c46aac4879e92fae462b9724504bfed334db1cd972fa064","schema_version":"1.0","event_id":"sha256:8285874d3eac1ffe1c46aac4879e92fae462b9724504bfed334db1cd972fa064"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:RH2RGGQ4T2E3P4KRLQ5PZ5LTAC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Aditya Majumdar, Amulya Yadav, Wenbo Zhang","submitted_at":"2024-11-13T22:56:00Z","abstract_excerpt":"Large Language Models (LLMs) have demonstrated remarkable capabilities across various NLP tasks but struggle with code-mixed (or code-switched) language understanding. For example, prior work benchmarking the performance of multilingual LLMs on code-mixed translation tasks has demonstrated that current state-of-the-art multilingual LLMs are ineffective in dealing with code-mixed languages. However, the question of how to improve the capability of multilingual LLMs to handle code-mixed language has not received any attention to date. In this paper, we tackle this research gap by proposing CHAI,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.09073","kind":"arxiv","version":3},"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/2411.09073/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:34:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"myukO2kKsLwBawM6TWLi9Q8l2sKxz4dpSEMAaZFZTOIiUYMT+iuMOaSgUz+kjDLhD+z7cqfvQJnn7hbLdWz5Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T01:18:01.034209Z"},"content_sha256":"762fe9d890210f23200465129297772fdcd869113740dd778204656aa3d5aed3","schema_version":"1.0","event_id":"sha256:762fe9d890210f23200465129297772fdcd869113740dd778204656aa3d5aed3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RH2RGGQ4T2E3P4KRLQ5PZ5LTAC/bundle.json","state_url":"https://pith.science/pith/RH2RGGQ4T2E3P4KRLQ5PZ5LTAC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RH2RGGQ4T2E3P4KRLQ5PZ5LTAC/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-07T01:18:01Z","links":{"resolver":"https://pith.science/pith/RH2RGGQ4T2E3P4KRLQ5PZ5LTAC","bundle":"https://pith.science/pith/RH2RGGQ4T2E3P4KRLQ5PZ5LTAC/bundle.json","state":"https://pith.science/pith/RH2RGGQ4T2E3P4KRLQ5PZ5LTAC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RH2RGGQ4T2E3P4KRLQ5PZ5LTAC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RH2RGGQ4T2E3P4KRLQ5PZ5LTAC","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":"925a58262afd76bab7ea560a62c70b143b94d7d5fad31b8ef79a2eafcf404f0c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-13T22:56:00Z","title_canon_sha256":"9c79b7df97a0b579dd91011038c7fd2cbae8251112f22d522092ba58f03d6c51"},"schema_version":"1.0","source":{"id":"2411.09073","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.09073","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"arxiv_version","alias_value":"2411.09073v3","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.09073","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"pith_short_12","alias_value":"RH2RGGQ4T2E3","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"pith_short_16","alias_value":"RH2RGGQ4T2E3P4KR","created_at":"2026-07-05T11:34:01Z"},{"alias_kind":"pith_short_8","alias_value":"RH2RGGQ4","created_at":"2026-07-05T11:34:01Z"}],"graph_snapshots":[{"event_id":"sha256:762fe9d890210f23200465129297772fdcd869113740dd778204656aa3d5aed3","target":"graph","created_at":"2026-07-05T11:34:01Z","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/2411.09073/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated remarkable capabilities across various NLP tasks but struggle with code-mixed (or code-switched) language understanding. For example, prior work benchmarking the performance of multilingual LLMs on code-mixed translation tasks has demonstrated that current state-of-the-art multilingual LLMs are ineffective in dealing with code-mixed languages. However, the question of how to improve the capability of multilingual LLMs to handle code-mixed language has not received any attention to date. In this paper, we tackle this research gap by proposing CHAI,","authors_text":"Aditya Majumdar, Amulya Yadav, Wenbo Zhang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-13T22:56:00Z","title":"CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.09073","kind":"arxiv","version":3},"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":"sha256:8285874d3eac1ffe1c46aac4879e92fae462b9724504bfed334db1cd972fa064","target":"record","created_at":"2026-07-05T11:34:01Z","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":"925a58262afd76bab7ea560a62c70b143b94d7d5fad31b8ef79a2eafcf404f0c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-13T22:56:00Z","title_canon_sha256":"9c79b7df97a0b579dd91011038c7fd2cbae8251112f22d522092ba58f03d6c51"},"schema_version":"1.0","source":{"id":"2411.09073","kind":"arxiv","version":3}},"canonical_sha256":"89f5131a1c9e89b7f1515c3afcf573009fe6e963e20b66b82dcc534a1401fd0d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"89f5131a1c9e89b7f1515c3afcf573009fe6e963e20b66b82dcc534a1401fd0d","first_computed_at":"2026-07-05T11:34:01.899187Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:34:01.899187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SHoVj1a/Q53WpL0CbOD8BpM/fZQk0pB0C3nRm3jt/4qhLGRrb3Icn71Xuxrcl48PHqoNF2EJvub63VSBCgCNBg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:34:01.899686Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.09073","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8285874d3eac1ffe1c46aac4879e92fae462b9724504bfed334db1cd972fa064","sha256:762fe9d890210f23200465129297772fdcd869113740dd778204656aa3d5aed3"],"state_sha256":"683263542ca5f75360b57a9907caa5588480414d5cf9036b515b70b7a9758450"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tNDVaeCPlWKyFPzRu5B/Jla2ctuAMyKz6mh7JffnTjIkwjg1imd/FX9iwwUOb+7Ig+SreM/pPQc8eEHvjPf4BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T01:18:01.039618Z","bundle_sha256":"df44854aa0ef3a147e7e8dec409c10561d1934c0959bcce8b6661d70d704b195"}}