{"as_of":"2026-08-13T16:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a8275bf0dc540ddfc84136e718457ed3770ba0c7a4eac9edf48b56a3065750f2","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T10:37:16.433741Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.00125/citation-record","integrity":"/paper/2412.00125/integrity","json":"/paper/2412.00125/citation-record.json","paper":"/paper/2412.00125"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.223752Z","title":"Improving language understanding by generative pre-training,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.223752Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:17fefa7af0062d08145be7c9a4541b58058317b869dfb94e66e6b66f9e71b0b2","observation_id":"d7ce0265-3151-491d-b4eb-a0b7a4e61c17","resolution":{"observed_at":"2026-08-12T10:37:16.223752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10683","last_updated":"2023-09-19T15:14:48Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-10-23T17:37:36Z","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10683","snapshot_observed_at":"2026-08-12T10:37:16.228916Z","title":"Exploring the limits of transfer learning with a unified text-to-text transformer,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.228916Z"},"links":{"cited_paper":"/paper/1910.10683","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:7086f0912a18429b84dce94550f4fcaf4ea27cbd0a55225e47ec9f50ce02bbe3","observation_id":"8ddedf2a-f1eb-4cf3-9441-da0b5df7462d","resolution":{"observed_at":"2026-08-12T10:37:16.228916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-12T10:37:16.234096Z","title":"Llama: Open and efficient foundation language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.234096Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:3d4de6b391308fd4a73f3cf190f30ac58e25d4b4285d5d1f229533210587fd69","observation_id":"c2736408-ae6d-4529-b52b-6fd6a4ee2831","resolution":{"observed_at":"2026-08-12T10:37:16.234096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05463","last_updated":"2023-09-11T14:01:45Z","snapshot_observed_at":"2026-08-02T22:47:03.212781Z","submitted_at":"2023-09-11T14:01:45Z","title":"Textbooks Are All You Need II: phi-1.5 technical report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05463","snapshot_observed_at":"2026-08-12T10:37:16.239362Z","title":"Textbooks are all you need ii: phi-1.5 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.239362Z"},"links":{"cited_paper":"/paper/2309.05463","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:0d9e79e67e96d1e9d4c472de4f0c99730585f9020e8d2d5f25a96e3a33010198","observation_id":"deaa18fd-04e3-40e7-b599-f307541da6fb","resolution":{"observed_at":"2026-08-12T10:37:16.239362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-12T10:37:16.244447Z","title":"Mistral 7b,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.244447Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:6701fd60c9ceb74a6af7900be5b3ef7d020eaa7d5cc446f327de8e363d6a166e","observation_id":"fa8ce26e-7e4e-4798-a71c-212516ace7e6","resolution":{"observed_at":"2026-08-12T10:37:16.244447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.249447Z","title":"A survey on evaluation of large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.249447Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:63838d7211fa35705d355a1bc9ee91bd591a2f7da177493af4eb43e9be0d3834","observation_id":"7a451dd3-6398-4042-a120-a682f474d0b9","resolution":{"observed_at":"2026-08-12T10:37:16.249447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.02233","last_updated":"2025-02-23T14:16:52Z","snapshot_observed_at":"2026-08-13T10:20:05.658378Z","submitted_at":"2023-09-05T13:39:38Z","title":"Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.02233","snapshot_observed_at":"2026-08-12T10:37:16.254536Z","title":"Augmenting black-box llms with medical textbooks for clinical question answering,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.254536Z"},"links":{"cited_paper":"/paper/2309.02233","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:badd6eaee54ebe67cde1d08e788eb6fea79dd80a800770de81beb8d31e676727","observation_id":"828b3f11-5194-4a57-8126-059e5473fb47","resolution":{"observed_at":"2026-08-12T10:37:16.254536Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:17.060670Z","title":"A survey on legal question–answering systems,","venue":null,"work_id":"5cf996bb-f646-4a8d-a440-31238b1ac1e1","year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.259354Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:0539bb921784eae1af69906cda9cae2fd033216516fd63b314c02c3c0b974f3e","observation_id":"30c10fd8-1142-4725-8d56-7e3ed1ca6868","resolution":{"observed_at":"2026-08-12T10:37:17.065549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-12T10:37:16.263741Z","title":"Retrieval-augmented generation for large language models: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.263741Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:65732479a959646dcfc347c90c777acfc200f4adc090d962b3e30ec4ac682fab","observation_id":"98a4a575-52b8-4cf7-a148-4c0691f204bc","resolution":{"observed_at":"2026-08-12T10:37:16.263741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.11517","last_updated":"2021-06-22T03:17:59Z","snapshot_observed_at":"2026-08-10T05:42:44.097246Z","submitted_at":"2021-06-22T03:17:59Z","title":"Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.11517","snapshot_observed_at":"2026-08-12T10:37:16.268339Z","title":"Fine- tune the entire rag architecture (including dpr retriever) for question- answering,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.268339Z"},"links":{"cited_paper":"/paper/2106.11517","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:73166b72dc96a8de260abb698fecefeec84b604623da50ae519b7e584dd36769","observation_id":"ce8db2f0-41a4-47a5-b375-9e2c8e89e09d","resolution":{"observed_at":"2026-08-12T10:37:16.268339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.04906","last_updated":"2020-09-30T21:27:13Z","snapshot_observed_at":"2026-07-06T09:11:26.109763Z","submitted_at":"2020-04-10T04:53:17Z","title":"Dense Passage Retrieval for Open-Domain Question Answering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.04906","snapshot_observed_at":"2026-08-12T10:37:16.273049Z","title":"Dense passage retrieval for open-domain question answering,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.273049Z"},"links":{"cited_paper":"/paper/2004.04906","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:9f6ce6071cb2de6d881d424c1c0c75dcb1c260680e1f208cd24e3ba76cdaec84","observation_id":"cbd34d30-cf9d-4679-a4a2-5fca8d7b276d","resolution":{"observed_at":"2026-08-12T10:37:16.273049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-07-30T09:12:38.100527Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-12T10:37:16.277757Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.277757Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:002a703c08626256c9b4b5f8ca8cb24fef6ffa6f87c2c1d850622adb7a7a2ae3","observation_id":"dce883d4-0560-4c80-8660-b9f0fb723d18","resolution":{"observed_at":"2026-08-12T10:37:16.277757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.13461","last_updated":"2019-10-29T18:01:00Z","snapshot_observed_at":"2026-07-06T08:33:12.534026Z","submitted_at":"2019-10-29T18:01:00Z","title":"BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.13461","snapshot_observed_at":"2026-08-12T10:37:16.282853Z","title":"Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehen- sion,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.282853Z"},"links":{"cited_paper":"/paper/1910.13461","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:8b374857f7e3d4a6806a4a180514954981b9abd9c1c2a44be5d27b2f81823c23","observation_id":"c6cd61d0-eb2b-4e40-90ea-1c4f8b6ad3a7","resolution":{"observed_at":"2026-08-12T10:37:16.282853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:17.045718Z","title":"Ai-ta: Towards an intelligent question-answer teaching assistant using open-source llms,","venue":null,"work_id":"314fc714-cc44-428f-9700-89840f9d2f67","year":null},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.287518Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:266cc392d90976a3e5bbaf84ab5b044e3f2da522c6a23413aa9eef820ddaa2d9","observation_id":"5303843d-63a9-453b-b8e2-9fcd1d12546b","resolution":{"observed_at":"2026-08-12T10:37:17.050667Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:17.031468Z","title":"Buddybot: Ai powered chatbot for enhancing english language learning,","venue":null,"work_id":"6901933d-0146-4feb-99a0-30999f5c56d5","year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.296813Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:eeea448707ba618a51992aac17d580ca10ea4dcaf5c7e46ae39412534174696e","observation_id":"ca0e7a4e-780a-4e7d-bd87-65f19c614a4d","resolution":{"observed_at":"2026-08-12T10:37:17.036147Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:17.017113Z","title":"Llama-lora neural prompt engineering: A deep tuning framework for automatically generating chinese text logical reasoning thinking chains,","venue":null,"work_id":"f98f5313-285a-462b-a68c-44c4aba27530","year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.301047Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:47270d3d2770e01082c44763ddda96d68df02324a55ff43884f6c2e1a36d65d9","observation_id":"b7751073-56b0-4b04-b7f7-e90b609dd821","resolution":{"observed_at":"2026-08-12T10:37:17.022028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-08-13T04:50:35.316687Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-12T10:37:16.305350Z","title":"Fine-tuning and utilization methods of domain-specific llms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.305350Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:89e96cb0c4666794ac53566e04642301d71da849c62e4d3cc215e0728c06accf","observation_id":"df824e5e-c767-40af-961e-2945b62619fb","resolution":{"observed_at":"2026-08-12T10:37:16.305350Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:17.003150Z","title":"Customising general large language models for specialised emotion recognition tasks,","venue":null,"work_id":"85aa100c-ce7c-464b-9bb8-43115cd631d3","year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.310894Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:eeba16071eb84b52f0b870edaa7cafab1b367f7cf6c8edcde625e69f1f152ca0","observation_id":"97147f63-3314-4aef-8463-0e2502b52cfa","resolution":{"observed_at":"2026-08-12T10:37:17.008004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.315266Z","title":"Lora: Low-rank adaptation of large language models,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.315266Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:84ec47f4fdcf655c013d063c79f2d2b95c0b1f82f15c2b7a0030f268a7926134","observation_id":"86b87d51-7c08-4322-b229-18ac87312d29","resolution":{"observed_at":"2026-08-12T10:37:16.315266Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15127","last_updated":"2024-04-19T09:40:04Z","snapshot_observed_at":"2026-08-13T04:34:06.262325Z","submitted_at":"2024-01-26T13:15:24Z","title":"Evaluation of LLM Chatbots for OSINT-based Cyber Threat Awareness","version":3},"cited_work":{"arxiv_id":"2401.15127","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.15127","snapshot_observed_at":"2026-08-12T10:37:16.663265Z","title":"Evaluation of LLM Chatbots for OSINT-based Cyber Threat Awareness","venue":"cs.CR","work_id":"77388522-9f03-4a65-9a9b-75be5341bfbc","year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.324639Z"},"links":{"cited_paper":"/paper/2401.15127","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:9739c1ed885f4f141ac31ffff9cacbfabc4b317a1e9b8b991738a40d0ff8dd99","observation_id":"3efe435d-ade1-4e17-aa33-47775d718fb2","resolution":{"observed_at":"2026-08-12T10:37:16.668917Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.20320","last_updated":"2024-03-29T17:43:58Z","snapshot_observed_at":"2026-08-13T00:41:52.782149Z","submitted_at":"2024-03-29T17:43:58Z","title":"MTLoRA: A Low-Rank Adaptation Approach for Efficient Multi-Task Learning","version":1},"cited_work":{"arxiv_id":"2403.20320","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.20320","snapshot_observed_at":"2026-08-12T10:37:16.640171Z","title":"MTLoRA: A Low-Rank Adaptation Approach for Efficient Multi-Task Learning","venue":"cs.CV","work_id":"29f4ddd4-be19-4ca0-9d03-defc8988f1ab","year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.329061Z"},"links":{"cited_paper":"/paper/2403.20320","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:afe17f1c6efbbbd64775c5a95c077fd3f18714da47d234d6275b6c8e0487cc67","observation_id":"d6441c0b-cef4-40fb-88a3-2412fb202dd0","resolution":{"observed_at":"2026-08-12T10:37:16.647414Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.333685Z","title":"Qlora: Efficient finetuning of quantized llms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.333685Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:175732438967686c4a87da174c63b8ba4568a8d09d29de33af8aa73ed5cda0df","observation_id":"9989d700-1183-4825-bc0f-7aefb918bdfe","resolution":{"observed_at":"2026-08-12T10:37:16.333685Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.972309Z","title":"Available: https://huggingface.co/docs/bitsandbytes/main/en/ index","venue":null,"work_id":"f7b7f674-639d-4d1d-be09-ec694c94e96a","year":null},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.337839Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:e84f712da09103f8da6000df53f5da2f5d7a4f39104e294dbe5d203fb5e95552","observation_id":"dd7cc50e-8000-4a28-8903-eb7fb71092e2","resolution":{"observed_at":"2026-08-12T10:37:16.976684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10779","last_updated":"2024-03-23T13:25:01Z","snapshot_observed_at":"2026-08-13T08:40:30.501578Z","submitted_at":"2024-03-23T13:25:01Z","title":"Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10779","snapshot_observed_at":"2026-08-12T10:37:16.342195Z","title":"Fine tuning llm for enterprise: Practical guidelines and recommendations,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.342195Z"},"links":{"cited_paper":"/paper/2404.10779","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:39c16a8c079d0602c61ea54897185f24a3f8f8f20e64c701d2dd2c9ee8cc6a77","observation_id":"741ba306-09bc-46d3-8526-d3f8846b9298","resolution":{"observed_at":"2026-08-12T10:37:16.342195Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1907.11692","last_updated":"2019-07-26T17:48:29Z","snapshot_observed_at":"2026-07-31T22:31:37.910868Z","submitted_at":"2019-07-26T17:48:29Z","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.11692","snapshot_observed_at":"2026-08-12T10:37:16.346872Z","title":"Roberta: A robustly optimized bert pretraining approach,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.346872Z"},"links":{"cited_paper":"/paper/1907.11692","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:2add813902daae94ffd14e406f4e42dd2e7feef5882e751906ec20639a84ec4e","observation_id":"86f1537a-8c0b-41c7-888d-fd3f12d1571e","resolution":{"observed_at":"2026-08-12T10:37:16.346872Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.03299","last_updated":"2022-11-16T16:38:18Z","snapshot_observed_at":"2026-08-13T00:16:02.335397Z","submitted_at":"2022-08-05T17:39:22Z","title":"Atlas: Few-shot Learning with Retrieval Augmented Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.03299","snapshot_observed_at":"2026-08-12T10:37:16.351537Z","title":"Atlas: Few-shot learning with retrieval augmented language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.351537Z"},"links":{"cited_paper":"/paper/2208.03299","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:821d2ad845fdb98d72d2febb6c29c717294349003303ee74888d65fe63c09826","observation_id":"d049c9fa-2b03-4d16-84ea-0c1a015ce3e0","resolution":{"observed_at":"2026-08-12T10:37:16.351537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.11401","last_updated":"2021-04-12T15:42:18Z","snapshot_observed_at":"2026-08-07T05:44:30.677502Z","submitted_at":"2020-05-22T21:34:34Z","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.11401","snapshot_observed_at":"2026-08-12T10:37:16.356434Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.356434Z"},"links":{"cited_paper":"/paper/2005.11401","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:93602dd19c3306b4d447f8ccaaf77a8f7d16132ea643e00fee9fccf8e2eebf27","observation_id":"28de5033-a817-4575-ae76-3bbcb9b7a0e1","resolution":{"observed_at":"2026-08-12T10:37:16.356434Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.08909","last_updated":"2020-02-10T18:40:59Z","snapshot_observed_at":"2026-08-02T17:52:27.326803Z","submitted_at":"2020-02-10T18:40:59Z","title":"REALM: Retrieval-Augmented Language Model Pre-Training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08909","snapshot_observed_at":"2026-08-12T10:37:16.360910Z","title":"Realm: Retrieval-augmented language model pre-training,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.360910Z"},"links":{"cited_paper":"/paper/2002.08909","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:61f0d76a0c605a711facce044f609bf3c40aa0d2b7fa76f495aa0e377aef38b6","observation_id":"27694216-6d94-4ff1-a16e-4de975075095","resolution":{"observed_at":"2026-08-12T10:37:16.360910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.00083","last_updated":"2023-08-01T12:10:15Z","snapshot_observed_at":"2026-08-13T12:53:56.601584Z","submitted_at":"2023-01-31T20:26:16Z","title":"In-Context Retrieval-Augmented Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.00083","snapshot_observed_at":"2026-08-12T10:37:16.365333Z","title":"In-context retrieval-augmented language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.365333Z"},"links":{"cited_paper":"/paper/2302.00083","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:c2af9a374b57aa7cdbbd1500166dfd500f7f823b8e8ea5bc974ebc2428f7671c","observation_id":"8933fc54-8996-4233-a5c7-845db414187a","resolution":{"observed_at":"2026-08-12T10:37:16.365333Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.958642Z","title":"Available: https://e.huawei.com/en/talent/ict-academy/#/ ict-courses-list","venue":null,"work_id":"296ea3ee-152a-497a-a19d-48d0a0b88451","year":null},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.370071Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:f0f8ea63091f3fa254989b0f409414b219ce559c4e37a90bb13d283fdaf30e42","observation_id":"fcfd3b3e-b7ab-4476-bf71-b5256dc85482","resolution":{"observed_at":"2026-08-12T10:37:16.963286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-12T10:37:16.374851Z","title":"Gpt-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.374851Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:717413e3a9af1770ff72e0d58f61b3830405bca98a343a8fc35cd9e9dd5f2bc5","observation_id":"db98b27b-e720-4cd1-b82a-fa86191532d5","resolution":{"observed_at":"2026-08-12T10:37:16.374851Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.379445Z","title":"Transformers: State- of-the-art natural language processing,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.379445Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:0fdbc91657221029cbbe8501a4a122ae5168e2f1bfd95afa87ec51e9bf1091fa","observation_id":"77e185f4-897f-43d1-9f2b-c9c35908869c","resolution":{"observed_at":"2026-08-12T10:37:16.379445Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17081","last_updated":"2024-02-26T23:37:59Z","snapshot_observed_at":"2026-08-13T04:09:36.183888Z","submitted_at":"2024-02-26T23:37:59Z","title":"A Fine-tuning Enhanced RAG System with Quantized Influence Measure as AI Judge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17081","snapshot_observed_at":"2026-08-12T10:37:16.384000Z","title":"A fine-tuning enhanced rag system with quan- tized influence measure as ai judge,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.384000Z"},"links":{"cited_paper":"/paper/2402.17081","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:50dc85c264a72a5f878ba72a3431f30a615315fff144d42d157c24c704e7ace2","observation_id":"50807939-d50c-4ae2-989e-d6f420b9bde7","resolution":{"observed_at":"2026-08-12T10:37:16.384000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18137","last_updated":"2024-11-04T11:16:38Z","snapshot_observed_at":"2026-08-12T23:56:12.161392Z","submitted_at":"2024-05-28T12:51:01Z","title":"Exploiting LLM Quantization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18137","snapshot_observed_at":"2026-08-12T10:37:16.388559Z","title":"Exploiting llm quantization,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.388559Z"},"links":{"cited_paper":"/paper/2405.18137","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:6425e9abc53ff93f7c27e2601037b34dd328a531e9ec592bce21f900d650de0e","observation_id":"af729f7e-1b16-4599-8051-a83a42fbb2ee","resolution":{"observed_at":"2026-08-12T10:37:16.388559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14219","last_updated":"2024-08-30T21:17:17Z","snapshot_observed_at":"2026-08-10T14:07:02.234322Z","submitted_at":"2024-04-22T14:32:33Z","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14219","snapshot_observed_at":"2026-08-12T10:37:16.393346Z","title":"Phi- 3 technical report: A highly capable language model locally on your phone,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.393346Z"},"links":{"cited_paper":"/paper/2404.14219","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:8bb01a21fc39fa5c6447feb8a82c41899ec29b44e20c897398eb3a900fae6b92","observation_id":"3029e0e5-80fb-4603-b7b9-0b44d2cb3d51","resolution":{"observed_at":"2026-08-12T10:37:16.393346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07437","last_updated":"2024-07-03T04:59:32Z","snapshot_observed_at":"2026-08-13T00:09:14.643417Z","submitted_at":"2024-05-13T02:33:25Z","title":"Evaluation of Retrieval-Augmented Generation: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07437","snapshot_observed_at":"2026-08-12T10:37:16.398037Z","title":"Eval- uation of retrieval-augmented generation: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.398037Z"},"links":{"cited_paper":"/paper/2405.07437","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:b85ad072b9af43b50aa0e94621e9abb755cc1f3e56f5f81d62bb6c754178510f","observation_id":"34dc7b44-27e0-46e2-937b-5af46b1a5aee","resolution":{"observed_at":"2026-08-12T10:37:16.398037Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.934076Z","title":"Bleu: a method for automatic evaluation of machine translation,","venue":null,"work_id":"f987f42e-b009-42e4-8555-e366b2b1bade","year":2002},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.402740Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:438a790937294e6c554f44dbb6097fd6ef95311af8659fffd0cbac7953fabf97","observation_id":"a35b4346-7d77-43ac-99d6-8af33f54e332","resolution":{"observed_at":"2026-08-12T10:37:16.938823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.919862Z","title":"ROUGE: A package for automatic evaluation of summaries,","venue":null,"work_id":"cc02f3c8-7a25-4563-8fdb-afb00ac9a4eb","year":2004},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.407119Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:c360d0ade339c6d16393315915b4bcb6e63fc3fd2260eaab0f74318f9ab5f983","observation_id":"162e9a12-6bd9-48a7-98a0-acf4f6bab558","resolution":{"observed_at":"2026-08-12T10:37:16.924689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.906012Z","title":"METEOR: An automatic metric for MT evaluation with improved correlation with human judgments,","venue":null,"work_id":"08995ce5-32c5-418d-9f9b-106048fe3646","year":2005},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.411528Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:ee52fa41c576c6dc11a1cf552a9d885cdb3226d9065821c14ee7e1bcbdc1e727","observation_id":"f7b7be68-218f-4c92-b217-1b8e0757285a","resolution":{"observed_at":"2026-08-12T10:37:16.910516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.09675","last_updated":"2020-02-24T18:59:28Z","snapshot_observed_at":"2026-07-29T15:42:51.774083Z","submitted_at":"2019-04-21T23:08:53Z","title":"BERTScore: Evaluating Text Generation with BERT","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.09675","snapshot_observed_at":"2026-08-12T10:37:16.415873Z","title":"Bertscore: Evaluating text generation with bert,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.415873Z"},"links":{"cited_paper":"/paper/1904.09675","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:6d6c020bf94a944cd36a759820ab740317f2e81af1d47e1172c6c21f71fdaa84","observation_id":"0dd8d869-ba06-4070-b81d-4a7b46747453","resolution":{"observed_at":"2026-08-12T10:37:16.415873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.891603Z","title":"LangChain,","venue":null,"work_id":"b956e82e-097f-45cf-9c6d-214cbb8509e8","year":2022},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.420560Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:6730725a13c738396a7e57ca4a5f68ecad4bc754a981c3b7e8af2b374699beff","observation_id":"1f8a8c45-8ee7-47ad-bb05-21db598a6217","resolution":{"observed_at":"2026-08-12T10:37:16.896284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.877331Z","title":"Bitsandbytes,","venue":null,"work_id":"075fb688-9a04-4d25-accc-4a8e1536808a","year":2021},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.424762Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:838311ee0b7a04bf4679592f92f2614d03f322cf139c521a4936101bbbc2f6e9","observation_id":"0c558182-52c5-45ee-8c61-3d38e789152a","resolution":{"observed_at":"2026-08-12T10:37:16.881770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.429321Z","title":"The faiss library,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.429321Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:67cbe81feca9a556b890a8aefd3eaac339fa9c93c49e734633d2db5c1c991745","observation_id":"4f7e8acb-cc70-448d-8a08-501c0bef6ab2","resolution":{"observed_at":"2026-08-12T10:37:16.429321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:37:16.854914Z","title":"Assessing fine-tuning efficacy in llms: A case study with learning guidance chatbots,","venue":null,"work_id":"2ad63e9d-da53-4999-8414-a80568f72103","year":2024},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.433741Z"},"links":{"citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:9fb78b7185e7053e6bc80d615ca305e68f80069f6bd171a66df9c3aa95d101ce","observation_id":"2e94fd09-2ec7-416f-a694-0a93584af805","resolution":{"observed_at":"2026-08-12T10:37:16.859638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-11T08:20:29.798517Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-12T10:37:16.319907Z","title":"Available: https://arxiv.org/abs/2106.09685","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.319907Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:846b411bcfaf313db7452233ca7ba23b82842e012c5161d7bedbddc0da36943c","observation_id":"a67e2220-2b99-40a9-a0c0-4bf69db6a550","resolution":{"observed_at":"2026-08-12T10:37:16.319907Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.02775","last_updated":"2023-12-18T23:23:06Z","snapshot_observed_at":"2026-08-13T05:32:32.734727Z","submitted_at":"2023-11-05T21:43:02Z","title":"AI-TA: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.02775","snapshot_observed_at":"2026-08-12T10:37:16.292033Z","title":"Available: https://arxiv.org/abs/2311.02775","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T10:37:16.292033Z"},"links":{"cited_paper":"/paper/2311.02775","citing_paper":"/paper/2412.00125"},"observation_digest":"sha256:ac061048dc9d452777ebe3372c64c91038b69f8ef6edaa8d04ee43cf6fa7f7b2","observation_id":"1a1db1b7-5ce1-4e61-9706-d710dabd4ded","resolution":{"observed_at":"2026-08-12T10:37:16.292033Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.00125","last_updated":"2024-11-28T12:06:14Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-12T10:31:08.061590Z","submitted_at":"2024-11-28T12:06:14Z","title":"Efficient Learning Content Retrieval with Knowledge Injection"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":31,"verified_exact":2,"verified_fuzzy":13},"total_outbound_references":46},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2412.00125."}